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Since the media era, online public opinion is cross-spreading in multiple social networks, and studying the law of public opinion dissemination in coupled social networks is beneficial to the governance of public opinion. It first uses the scale-free network to construct Weibo and WeChat networks, and the Weibo and WeChat two-layer coupled social networks were constructed by setting specific node connection methods and network coupled rates. SEI2R model is established, and the propagation law of the public opinion WeChat and Weibo coupled double-layer network is studied through matlab simulation. Experiments show that the constructed SEI2R can better simulate the public opinion dissemination process in the network. The dissemination of public opinion information on the two-tier network enhances the influence of public opinion, the network coupling rate, the inter-layer transmission probability, and the direct immunity rate of netizens It has a significant impact on the spread of public opinion.

Essentially, array signal processing should jointly consider array design and array element design. However, conventional array structure based signal processing technologies separate multi-stream signals by the different receptions among uncorrelated array elements, which utilize the array processing gains only and ignore the antenna processing gains. When the array aperture is limited, the receiving signal matrix is illconditioned with reduced rank and the signal-separation capability cannot be further improved by increasing the number of array elements. This paper propose the space-time isomeric array, in which each element has different receiving pattern varying with time independently, to provide more precise observations on different signals in the sight of multi-path channels. Furthermore, a unified receiving signal model is derived to verify how space-time isomeric array increases the real degree of freedom (DoF) achieve and full rank signal matrix. The simulation shows space-time isomeric array can separate multi-stream signals with limited array aperture and limited number of antennas.

In recent decades, IGBT power modules have developed towards high power density, high integration, and high reliability. The junction temperature of the IGBT power module will increase under input current, which will reduce the reliability of the IGBT power module. Aiming at the thermal properties of the IGBT power module packaging structure, this paper proposes an asymmetrical double-sided heat dissipation IGBT power module with reduced size of the top DBC substrate. Using heat transfer theory and ANSYS finite element analysis method, the effect of DBC substrate structure on the thermal properties of high-power IGBT modules was researched and analyzed. We concluded by simulation experiments that compared with the symmetrical structure IGBT module, the junction temperature of the single-sided heat dissipation IGBT power module has increased by 46.9%. While the junction temperature of the asymmetrical structure IGBT module has increased by only 1.6%. Therefore, the asymmetric structure IGBT module proposed in this paper has excellent thermal conductivity and has the advantages of reducing the size, weight and cost of the module. When the single-sided heat dissipation structure cannot meet the heat dissipation requirements of the high-power IGBT module, it is suggested to use an asymmetric structure double- sided heat dissipation structure.

With the proliferation of positioning mobile devices, people’s trajectory data are posted on the net including spatial locations and semantic contexts such as in the form of text like twitter posted text. How to organize or fuse the raw spatial trajectories and context semantic data into a structured whole for analysis further is a problem, the focus of which is mostly how to annotate episodes in raw trajectories. In this paper we examine a structured and partially self-describing way for semantic organization and fusion of trajectory data. We annotate episodes with structured sentiments, events, or topic words, where sentiments given in a self-describing way and events are represented using the form from the natural language processing literature. Besides, all the data in the whole model are represented with JSON.

In this paper, molecular dynamics simulation method was used to simulate the change in optical properties of organic silicon materials after adsorption H 2 O by using Materials Studio simulation software. The results show that after the H 2 O are adsorbed by the silicone material, the main chain of the silicone material molecules breaks and the silicone material molecules react with the H 2 O to form new chemical bonds. After the water molecules are adsorbed, the reflectance of the material to visible light increases and the transmittance decreases. The more H 2 O are adsorbed, the smaller light transmittance of the silicon material. In addition, the diffusion characteristics of H 2 O at different temperatures of silicon materials with different concentrations of water molecules were analyzed. The results show that the molecular thermal motion is aggravated by the increase of temperature, the activity of molecular chains increases in the silicon material model, and the diffusion coefficient of H 2 O increases with the increasing temperature. At the same temperature, the diffusion coefficient of H 2 O is determined by the concentration of H 2 O in the silicone material. This study content is of great significance for analyzing the aging mechanism of silica gel and improving LED reliability.

Mutation strategy is an important issue of differential evolution (DE). The efforts of developing new mutation strategies have received more attention. In this paper, a univariate marginal distribution resampling differential evolution algorithm with multi-mutation strategy (UMDE-MS). Univariate marginal distribution algorithm continuous (UMDAc) has been proved to be efficient in nonseparable problems and it is less influenced by the correlation between variables. In the suggested algorithm, a univariate marginal distribution resampling mechanism inspired by this feature of UMDAc is proposed to reinitialize the population when evolution comes to a standstill. Moreover, two novel adaptive mutation strategies are proposed and integrated to build a mutation strategy pool. A parameter pool which consists of four popular F and Cr settings is employed in UMDE-MS. Finally, the proposed algorithm is tested on the CEC2019 100-Digit challenge benchmark problems. Experimental results demonstrate the effectiveness of UMDE-MS compared with other state-of-the-art algorithms.

The automatic control system is an important part of oil-gas-water experimental facility, which is mainly used for surveillance and control. The oil-gas-water multi-phase flow control system of this paper designed consists of host monitor and slave machine. The S7-200 PLC has been developed by the slave machine to control the valve opening and pumps' start and stop, accomplish sensors data collecting and processing. The host monitor selects Kingview software to develop monitoring interface. The software can realize locale real-time monitoring and controlling in the form of picture, data and animation. The host monitor communicates with the slave machine by serial port. The actual application shows that the control system based on S7-200 PLC and Kingview software is cheap, economical and highly reliable, which can effectively accomplish the monitoring task in real time.

Because its low sintering temperature, high melting point, excellent mechanical reliability, high electrical and thermal conductivities, silver nanoparticle sintering has the potential to be applied in high power electronic packaging as an alternative lead-free chip attach material. In this paper, IGBT simulation model of the double-sided cooling package is built, and the different chip attach materials of traditional Sn/Ag materials and silver nanoparticle sintering materials are compared.ANSYS is applied to simulate and analyze thermal distribution of the model. Results show that the IGBT module which adopts silver nanoparticle sintering material in the same boundary conditions, and the maximum chip temperature of the module is 77.1907 °C, 14.14% lower than the traditional Sn/Ag material. This analysis can be further applied that the thermal properties of Silver nanoparticle sintering materials are better than that of traditional Sn / Ag materials.

As for the industrial area, the control of VOCs emission has attracted a lot of attentions of researchers for several decades. Appropriate control strategies are fundamental tools to restrain the emission of VOCs. Based on empirical data extracted from the complete set of sources, control strategies for reducing VOCs emission process are proposed in this paper, which are obtained by performing numerical analyses. Empirical data are applied into the proof of theoretical results. Complete sources including industrial source, traffic source, living source and agricultural source are considered. The impacts of output value of general equipment in the industrial source, passenger throughput in traffic source, the size of population in living source and agricultural source on VOCs emissions are discussed. Additionally, control strategies for VOCs emissions are summarized by analyzing extremum of characteristic values obtained from sample sets. Finally, the features of various VOCs emission sources are concluded to guide the adjustment of treatment process, especially the treatment equipment of VOCs.

CANDECOMP/PARAFAC (CP) decomposition has been widely used to deal with multi-way data. For real-time or large-scale tensors, based on the ideas of randomized-sampling CP decomposition algorithm and online CP decomposition algorithm, a novel CP decomposition algorithm called randomized online CP decomposition (ROCP) is proposed in this paper. The proposed algorithm can avoid forming full Khatri-Rao product, which leads to boost the speed largely and reduce memory usage. The experimental results on synthetic data and real-world data show the ROCP algorithm is able to cope with CP decomposition for large-scale tensors with arbitrary number of dimensions. In addition, ROCP can reduce the computing time and memory usage dramatically, especially for large-scale tensors.

With the rapid development of Internet technology in China, digital online learning has become a new way for people to receive education. The scale of online education users has been growing rapidly as well as online education industry, which has broad and large market prospects. Many online education enterprises began to consider an important issue that how to attract and maintain users and make online education become more commercial. Under the backgrounds, this study takes the commercial online education platform as the research object, and based on previous researches, it integrates Echnology Acceptance Model (EAM), Expectation Confirmation Model (ECM) and Unified Theory of Acceptance and Use of Technology (UTAUT), and constructs impact factors model. Based on the results, this study also puts forward some targeted operational strategies to improve the user's intention.

Cuff-less blood pressure (BP) estimation using pulse transit time (PTT) is a promising method for long-term BP monitoring. However, state-of-art PTT models are unable to trace the change of pressure baseline in subjects, which limits their application in long-term BP tracking. This study investigated the relationship between the change of pressure baseline and pulse waveform in long-term BP monitoring. In the study, a total of 36 subjects received daily monitoring of systolic BP (SBP) and PTT for over one month. Linear regression was used to develop the SBP-ln(PTT) model for each subject. SBP predictions with regression differences greater than + SD (7.63 mmHg) were assumed to be with positive/negative baseline offset. For each subject, 12 features extracted from pulse waveform were obtained and their values were converted to standard scores to quantify pulse waveform variation. Independent two-sample t-test showed five pulse wave features changed significantly when subjects' pressure baseline varied. Furthermore, the consistency of pulse waveform variation was validated over the change of pressure baseline in subjects. In summary, this study demonstrated that pulse waveform could indicate baseline offset in PTT-based BP estimation. By highlighting five pulse wave features, this study provides novel insights to overcome the challenge of frequent calibrations in long-term PTT-based BP monitoring.

A reciprocal recommender system for graduates' recruitment (RRSGR) is presented in this paper. RRSGR makes full use of the historical information in university about graduates and former graduates. Both collaborative filtering and content-based filtering are incorporated in RRSGR, which help to achieve a win-win situation between graduates and employers. Probabilistic neighborhood selection and priority k-medoids clustering are adopted to improve the diversity of recommendation results. A preliminary evaluation has been conducted based on the real data of Shandong Normal University. Experiments and user survey show that RRSGR is effective to improve the accuracy and diversity of recruitment recommendation.

Moving objects, for example vehicles, vessels, people, are being instrumented with Internet of Things devices such as GPS, environmental sensors, mobile cameras that produce big streaming data with spatial-temporal features enabling application innovations in many industries for autonomous driving, usage based insurance, fleet management, etc. We introduce an analytics framework to streamline the insights discovery from such big data on top of geographic map by pulling together a list of commonly required high performance functions with service-oriented architecture. Supported by a service composition approach, comprehensive applications intelligently managing moving objects could be built effectively. Example applications in connected vehicle domains are presented to illustrate the effectiveness of such a framework.

A simple exposition was carried out for the power train's structure of the electric vehicle. Based on this, another simple exposition was designing the electronic differential which was based on various control theories. And detailed exposition was made upon the structure, the object and the control strategy of the electronic differential. Then, the combined simulation of distributed driving electric vehicle with Carsim/Simulink is determined. Detailed exposition was interface settings of the distributed electric drive system and the properly configured vehicle, the setting of key parameters for modeling. The effectiveness of the electronic differential system is verified by the test results and the simulation platform for the study of electronic differential system of electric vehicle.

With the rapid development of cloud computing and big data processing, more and more application frameworks are being considered to run in "cloud way". This brings about several challenges to the cloud computing platform, e.g., being able to run most existing heterogeneous applications, providing scalability and elasticity support for newly emerged frameworks, and most importantly, sharing cluster resources effectively. In this paper, we propose a new service model that is suitable for medium and small-sized data center to solve these problems in a relatively easy and general way - ClaaS (Cluster as a Service). The idea is virtualizing the cluster environment for application frameworks. Most applications can directly run in the virtual cluster environment without any modification, which is a great advantage. Based on lightweight containers, we implement a real system of ClaaS named Docklet in order to prove the feasibility of this service model. In the meantime, we preliminarily design the definition of applications to make them easy to deploy. Finally, we present several examples and evaluate the whole system.

When a mobile node moves into a new network, it should get a new care-of address. The new care-of address must be verified to be unique before used. The process of verifying the uniqueness of a care-of address is called the Duplicate Address Detection (DAD) and is estimated to take 1000 milliseconds or more. It is unacceptable for real-time applications. In this paper, the MD5 algorithm is applied on the IPv6 address auto-configuration to generate an IPv6 address and the numerical result shows that generated IPv6 addresses are expected to be uniformly distributed. Consequently the probability of the IPv6 address collision of generating the same IPv6 address is expected to be much less. A simplified DAD is then proposed to reduce the processing time of the DAD and then to improve the handover performance of IP mobility protocols.

Quad flat no-lead (QFN) packages are widely used in portable electronic products due to its excellent performance and lower cost. The electrical connection of QFN package is accomplished through solder-paste printing and it includes an exposed thermal pad to improve heat transfer. In addition, with the development of package technology, the pitches of QFN packages are designed smaller and multi-row QFN are becoming more and more popular. However, the reliability of QFN packages has not been well studied, especially those with multi-row I/O and fine pitch size. In this paper, two AAQFN packages (the I/O pads were replaced by solder balls) and two QFN packages were tested in temperature cycling according to JEDEC standard. All these four packages are molded and the two QFN packages has two-row I/O and with different package sizes. In order to compare the reliability of AAQFN and QFN, Weibull curves were drawn and their characteristic lives were obtained. Furthermore, failure analysis was carried out to find out the failure modes of the AAQFN and QFN packages.

Cloud computing is a new paradigm for the delivery of IT services. It has enabled many promising opportunities for features that cannot be easily implemented in traditional IT environments, such as elastic scalability, self-service deployment, resiliency and recovery, and so forth. Benchmarking the cloud requires a well-defined set of cloud performance metrics that should be able to sensitively distinguish the capabilities of cloud systems that enable those features. One way of defining benchmark metrics is based on observations of the internal mechanisms in a cloud. For example, an elasticity evaluation may be based on measuring a resource provisioning interval in the cloud. However, a more meaningful evaluation should be based on user-centric metrics. In this article, we will introduce a set of performance metrics that can be directly measured, calculated and compared by the cloud users, including workload consumers and the users who deploy and manage the workload life cycles. We will also discuss ways to organize the user-centric metrics, with different emphasis, into a benchmark that represents different use cases.

In this paper, we introduce a miniature robotic end-effector called LaserBot, which can manipulate a beam of ultra-short pulse laser along a planned trajectory to cut a decayed tooth to realize clinical dental preparation operation. When performing trajectory tracking control, conventional PID control strategy will cause unwanted fluctuation of the scanning speed of laser focus, which leads to the poor shape accuracy of the prepared tooth. In order to alleviate the negative influence of the speed fluctuation, a new trajectory tracking control strategy is proposed which combines PID control with virtual damping and velocity feed-forward. The virtual damping can reduce the speed fluctuation, and the velocity feed-forward is added to eliminate the negative effect on the response performance of the control system caused by the virtual damping. Simulation and experiments on motor control and laser ablation are implemented to verify the performance of the proposed control strategy. Results of the experiments indicate that the proposed trajectory tracking control strategy can reduce the fluctuation of scanning speed and improve the surface accuracy of the prepared tooth.

The dyadic sensors are of current interest in a number of applications. After the output correlation matrix of the dyadic sensor in the isotropic noise field is derived, the processing gains of conventional beamformer (CBF) and optimum gain beamformer (OGBF) based on single dyadic sensor are duduced. The results of several examples indicate that the dyadic sensor can obtain much more bigger processing gain with a small package, its optimum gain can reach 9.5 dB and its conventional processing gain is about 5.7 dB.

Generalized function projective synchronization of coupled chaotic systems with parameter mismatch, time-delay and stochastic perturbation is investigated. The synchronization is realized by analyzing the stochastic stability of the error system. According to the invariance principle of the stochastic differential equation, the unknown parameters update laws and the control laws are proposed. The generalized function projective synchronization of coupled chaotic or hyper chaotic systems is realized. At last, a numerical example is presented to show the effectiveness of the theoretical results.

The bleaching process of wheat straw was studied. NaHSO3 as bleaching main agent, selected concentration, temperature, ultrasonic frequency, time mainly on the factor orthogonal experiment, borrow SPSS13.0 software for statistical analysis, the impact factor on the process factors were optimized by the range analysis and variance analysis, determine suitable wheat straw bleaching optimum process parameters and confirmatory testing. The results showed that: NaHSO3 significant bleaching of wheat straw; The optimum process parameters: concentration 3 %, temperature 40 °C, frequency 45 KHz, time 60min.