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Network traffic classification has become an important part of network management, which is beneficial for achieving intelligent network operation and maintenance, enhancing the network quality of service (QoS), and for network security. Given the rapid development of various applications and protocols, more and more encrypted traffic has emerged in networks. Traditional traffic classification methods exhibited the unsatisfied performance since the encrypted traffic is no longer in plain text. In this work, we modeled the time-series network traffic by the recurrent neural network (RNN). Moreover, the attention mechanism was introduced for assisting network traffic classification in the form of the following two models, the attention aided long short term memory (LSTM) as well as the hierarchical attention network (HAN). Finally, relying on the ISCX VPN-NonVPN dataset, extensive experiments were conducted, showing that the proposed methods achieved 91.2 percent in accuracy while the highest accuracy of other methods was 89.8 percent relying on the same dataset.

International audience; Fischer-Tropsch synthesis (FTS) is an essential approach to convert coal, biomass, and shale gas into fuels and chemicals, such as lower olefins, gasoline, diesel, and so on. In recent years, there has been increasing motivation to deploy FTS at commercial scales which has been boosting the discovery of high performance catalysts. In particular, the importance of support in modulating the activity of metals has been recognized and carbonaceous materials have attracted attention as supports for FTS. In this review, we summarised the substantial progress in the preparation of carbon-based catalysts for FTS by applying activated carbon (AC), carbon nanotubes (CNTs), carbon nanofibers (CNFs), carbon spheres (CSs), and metal-organic frameworks (MOFs) derived carbonaceous materials as supports. A general assessment of carbon-based catalysts for FTS, concerning the support and metal properties, activity and products selectivity, and their interactions is systematically discussed. Finally, current challenges and future trends in the development of carbon-based catalysts for commercial utilization in FTS are proposed.

As a critical supplementary to terrestrial communication systems, low-earth-orbit (LEO) satellite communication systems have been gaining growing attention in recent years. In this paper, we consider an LEO system where a number of Internet of things (IoT) gateways need to send their collected data to LEO satellites. The highly dynamic topology of satellite systems and the limited connection status between satellites and gateways pose challenges to the problem of gateway association and data scheduling. To address this problem, we define system transmission delay as the number of time slots needed for all gateways to upload their collected data, and formulate the joint gateway association and data scheduling problem as a system transmission delay minimization problem. To solve the problem, we first consider a relatively simple case, i.e., a single gateway case, and propose a greedy method-based single gateway association and data scheduling algorithm. We then extend the solution to the case of multiple gateways and propose a transmission priority-based joint gateway association and data scheduling algorithm. Simulation results show that the proposed algorithm is superior to the algorithm proposed in previous work.

Depth maps captured by Kinect or time of flight (ToF) cameras have an active role in many visual applications. However, a brutal truth is that these depth maps are often contaminated with compound noise, which includes intrinsic noise and missing pixels. In addition, depth maps captured with ToF-based cameras are low in resolution. As these depth maps carry rich and critical information about 3D space, high quality post-processing is crucial for supporting subsequent visual applications. Previous works were proposed via the guiding of the registered color image and bicubic interpolation as an initialization for the up-sampling task, where challenges arose from texture coping and blurry depth discontinuities. Motivated by these challenges, in this paper, we propose a new optimization model depending on the relative structures of both depth and color images for both depth map filtering and up-sampling tasks. In our general model, two self-structure priors for depth and color images are constructed individually and used for the two tasks. For overcoming the texture coping problem, the color-based and depth-based priors are used near the depth edges and at the homogeneous regions respectively. To this end, we further propose a confidence map at every task for managing where every prior is used. Experimental results on both simulated and real datasets for Kinect and ToF cameras demonstrate that the proposed method has a superior performance than benchmarks.

The integration of large-scale renewable energy makes the power system face challenges, and the micro-grid is one of the important research directions for utilizing new energy. The development of distributed power has alleviated grid pressure to some extent, but there are new problems in electronic power systems. In the micro-grid, the power distribution control between parallel distributed power sources generally uses voltage droop control technology. The key to the technology is the coordinated control between multiple power converters, which requires the bus voltage and frequency to be within the rated range and the load power to be properly distributed to ensure safe and reliable operation of the power system. This paper proposes a control strategy that can make the characteristics of the grid-connected converters excellent, and verify them by Matlab/Simulink to prove the feasibility of the strategy.

Objective. This study aimed to explore the laboratory markers associated with perforation in children with acute appendicitis.Methods. This retrospective study reviewed 1895 children (3–18 years old) with confirmed acute appendicitis from 2007 to 2017. Clinical (demographic characteristics, symptoms, and signs) and laboratory data (white blood cell count, C-reactive protein (CRP), procalcitonin, D-lactate, platelet count, bilirubin, aspartate aminotransferase, and alanine aminotransferase) were collected and compared between perforated and nonperforated groups. The logistic regression analysis was performed to identify independent risk factors.Results. Of all patients, 613 children were perforated. Children with perforation had significantly longer duration of symptoms, higher white blood cell count, CRP level, and neutrophils percentage, and lower serum sodium level. Elevated white blood cell count with CRP level and elevated neutrophils percentage with CRP level were found to be associated with risk of perforation.Conclusions. White blood cell count with C-reactive protein and neutrophils percentage with CRP are important markers in distinguishing perforated appendicitis from nonperforated appendicitis in pediatric subjects.

Accurate recognition of hand motions is the prerequisite for control of prostheses for upper limb using surface electromyographic (sEMG) signals. In order to get better recognition of hand motions using sEMG signals, this paper developed a three-channel system to acquire sEMG signals from forearm muscles. The method of Power Spectral Density(PSD) for feature extraction was employed, recognize nine kinds of hand motions based on support vector machine (SVM). SVM performance based on cross validation and genetic algorithm(GA) was compared. The results show that using GA to optimize SVM has better performance, the recognition rate can reach 99.37% of training set, while the recognition rate can reach 90.33% of testing set. Based on the results, this method is a promising technique for prostheses control using sEMG signals.

The huge AC power girds of China have been all connected by dozens of HVDC links now. To understand the behavior of the complicated network and mechanism of interaction between AC and DC, there is a demand for a more precise simulation technology. Traditional power system analysis tools, such as electromechanical transient program and off-line electromagnetic transient program, the models of DC control and protections are simplified to some degree. Sometimes the simplification may not reflect the same act that grid may do as in the field. In order to get a detailed, panoramic view, it is believed that simulating the large-scale network model by electromagnetic transient software in real-time with actual DC control and protection devices linked will give a better performance. In this way, the simulation time step should be small enough so that the physical DC controllers can be connected to realize hybrid simulation. Normally, microsecond level is applied. However, running a tremendous AC/DC grid model of thousands of buses with a time step of microseconds is the precondition of digital-analog hybrid simulation, and also a great challenge to all experts in the field of power system real-time simulation of the world. Based on task mapping and parallel computing technology, power system real-time simulator HYPERSIM and supercomputer SGI UV300 are used in this paper to achieve the goal. Considering of the processor’s computational capability, on account of naturally decoupling by long distributed parameter lines, this paper optimizes the method of large-scale grid decoupling, splits the sophisticated region grid model into distributed tasks reasonably. Exploring the automatic task mapping function in HYPERSIM, a synthetic method about multiple auto-assigned parameters optimization is proposed. Eventually, an electromagnetic transient network model of 17746 single phase buses can be operated in real-time, which is a breakthrough on scale expanding of real-time simulation. The precision of AC/DC grid simulation makes a step further. The realization of massive grid model real-time operation gives a new technical means for characteristic cognition, system planning, operating, decision-making and failure reproduction of Chinese future power system.

In this paper, the optical fiber sensing technology is taken as the research object. Firstly, according to the demand of the sensing layer of the power Internet of things, a transmission line environment online monitoring system is proposed based on the multi risk monitoring of external breakage, fire, icing, galloping and so on of the cable (overhead line), the composition and deployment of the monitoring system are introduced. Secondly, based on the research of temperature field and stress field distribution of optical fiber, combined with big data and artificial intelligence, the important environmental parameters of the line can be monitored. Finally, taking different monitoring scenarios as examples, this paper expounds the different monitoring functions of the environmental monitoring system of the Internet of things for transmission lines, which provides useful reference for environmental monitoring of transmission lines.

The Proceedings of the 24th International Solvay Conference on Chemistry comprise contributed short personal statements and transcripts of in-depth discussions on "Catalysis in Chemistry and Biology" from a by-invitation-only select group of 48 eminent scientists, including four Nobel Laureates, from all parts of the world. The theme of the conference was presented in six sessions, along which the Proceedings are organized. The first session on "Homogeneous Catalysis," chaired by Professor Robert Grubbs, is devoted to basic research on catalysis in homogeneous solutions and applications thereof. "Heterogeneous Catalysis and Characterization of Catalyst Surfaces," chaired by Professor Gerhard Ertl, includes extensive references to industrial applications of catalysis on solid supports, and discussions on the experimental techniques used in this field. "Catalysis by Microporous Materials," chaired by Professor Mark E. Davis, is devoted to a detailed characterization of this particular class of solid support catalysts, with special emphasis on model analysis of the processes catalyzed by these materials. "Catalysis under Extreme Conditions: Studies at High Pressure and High Temperatures — Relations with Processes in Nature," chaired by Professor Henk N W Lekkerkerker, broadens the scope of the two preceding sessions with exciting illustrations. The sessions on "Catalysis by Protein Enzymes," chaired by Prof. JoAnne Stubbe, and "Catalysis by Ribozymes in Molecular Machines," chaired by Prof. David Lilley, present at the same time an exciting extension of and a contrast to the initial four sessions. The combination of the six sessions provides an impressive overview, giving innovative insights into relationships between catalysis in chemical processes and in biological systems, and a unique outlook to anticipated developments in the coming years and the more distant future.

The dynamic strain and vibration acceleration are two key parameters in the monitoring of vibrations that can damage track and affect the safety of railway traffic. This paper presents a remote measurement system for the online monitoring of train-induced vibration responses in rail tracks. A precision data acquisition node is designed for the conditioning and monitoring of the vibration signals generated by trains traveling at full speed. The monitored data is remotely acquired using a wireless sensor network. Furthermore, the use of solar power significantly increases the long-term service life of the system. The system is validated using both laboratory tests and a field deployment over a period of several months on an in-service high-speed railway. The obtained results indicate that the remote measurement system can accurately collect dynamic strain and vibration acceleration signals in a rail; these signals can be processed and analyzed to allow timely maintenance actions.

We propose a practical general method, called the linear time-over-threshold (linear TOT) scheme, for nuclear pulse amplitude digitization aiming at providing a high degree of integration for a high-channel count detector system. The most critical technique in the scheme is that for a different particle detector and diverse pulse shaping, how to produce the time-varying dynamic threshold voltage, which enables the linear conversion from the peak amplitude of nuclear pulse to the TOT time width. Compared with the normal time-over-threshold method for pulse height digitizing, the linear TOT has a strict linearity, large measurable signal dynamic range, and good signal-to-noise ratio. Using the scheme, we design a prototype of a field-programmable gate-array (FPGA)-based 64-channel data-acquisition (DAQ) system for a continuous crystal poistron emission tomography detector. The system only consists of 64-channel active RC integrators and voltage comparators, a shared dynamic threshold generating circuit, and an FPGA. The physical size of the system is so small that it could be attached on the base of the PMT. The preliminary test results show that the nonlinearity between pulse amplitude and TOT time width is about 0.01%, and the prototype could achieve an energy resolution of 12.3% by 22Na coincident spectrum measurement, which is better than the result (14.6%) obtained using our previous homemade DAQ system designed with a normal analog-to-digital converter technique. The design proves that the linear TOT scheme is an effective solution for a high-channel count digitizing system in nuclear detection, not only for its high performance, but also for a high degree of integration.

A micro-fabrication method for thin nickel plates was explored by Wire-cut Electrical Discharge Machining(WEDM).A series of experiments of WEDM for the meso-scale structure of a thin nickel plate with a thickness of 0.6 mm were carried out.Then,a trial cutting test was performed using existing machining parameters in the machine,and the dimensional accuracy and surface quality of the thin nickel plate after cutting were measured and analyzed.On that basis,the machining process was improved by changing the discharge energy,flushing pressure and the cutting speed.The method of multiple cutting within a 200 μm narrow slit was discussed as well,and reasonable optimization and merger for cutting times were carried out.Experimental results indicate that the WEDM can cut the meso-scale structure with a thickness less than that of machine original setting in steady for the thin nickel plate.The surface quality can be improved after multiple cutting for the 200 μm narrow slit,and the final surface roughness Ra is 0.54 μm after fifth cutting.With the machining surface quality guaranteed,the final surface roughness Ra is 0.62 μm when the cutting times are merged from 5 into 3,by which the machining time is shortened by 30%.The method proposed can also apply to meso-scale structures of other materials.

Neurotrophic factor (NF) and Trk signaling mechanisms underlying the promotion of motor recovery following acute spinal cord injury (SCI) in rats were investigated. Thirty-six adult Sprague-Dawley rats of both genders were randomly divided into three groups: Sham-operated, model, and NF/Trk. Each group consisted of 12 rats, with four subgroups in each group: 1, 3, 5 and 7 days. Sham-operated rats received a laminectomy without SCI, while in model group rats, SCI was induced using an improved version of the Allen's method. After analepsia, sham-operated and model group rats were given normal saline via gavage, while the NF/Trk group received NFs and Trk. Lower limb function was measured using the Basso, Beattie and Bresnahan scale 1, 3, 5 and 7 days before and after surgery. Results were analyzed statistically. Six rats from each group were randomly selected for sacrifice at 1, 3, 5 and 7 days after the operation. Morphological changes in motor neurons in the anterior gray column were observed by hematoxylin and eosin, and Nissl staining. Brain-derived expression of NF (BNDF) and neurotrophin-3 (NT-3) was detected by immunofluorescence, and the number of positive cells was counted. Expression of Trk B and Trk protein C receptor was measured by western blotting. In the NF/Trk group, the expression of NF/Trk pathway components remarkably increased. In addition, the morphology of motor neurons in the anterior gray column was improved. Expression of BNDF and NT-3 was significantly increased in motor neurons of the anterior gray column in NF/Trk rats compared with those of sham-operated and model rats (P

A combined prediction method based on weather type index and Gaussian Process Regression(GPR) improved by linear weight reduction PSO algorithm was proposed to deal with the problem of forecasting of short-term PV generation. Firstly, the samples, according to the weather type index, was built, and then three types were classified based on daily mean temperature and humanity; the different GPR model, considering different highly correction factors, which measuring combined covariance functions and taking LinW-PSO to optimize the hyperparameters of model, were built; The corresponding computer code was programmed in MATLAB. Seen from simulation results of forecasting of the PV station in XinJiang, the given classification method and LinW-PSO-GPR combination predicting method enable the rate of convergence and the accuracy of results improved.

This paper provides a detailed simulation of commutation failures in line-commutated thyristor converters. Theoretical analysis of commutation failure is presented. Influencing factors (such as voltage drop, voltage decreasing velocity, phase shift over zero of commutation voltage, HVDC controller) of both AC system and HVDC system on commutation failure are discussed in this paper. Then improvement of the characterization of the firing angle control is used to avoid commutation failure. Theory validation by simulation is also given.

Use of inactivated poliovirus vaccine (IPV) in Jinan during the polio eradication endgame has not been previously documented. Two IPV-containing vaccines were made available as an option for Jinan parents in 2009. We describe coverage levels and patterns of use of IPV over time using data from the Jinan Childhood Immunization Information Management System (JNCIIMS).Children born between January 2010 and December 2014 who were registered in JNCIIMS were included in this study. Vaccination records were obtained from JNCIIMS on April 30, 2015. JNCIIMS distinguishes among available poliovirus vaccines; doses administered data were used to describe IPV usage over time. We identified the polio vaccination sequences used by children in the 2012 and 2013 birth cohorts. Coverage estimates were analyzed by birth cohort and migration status. We developed 3 categories for analysis: "resident child," "migrant child" and "other child" according to migration status.In total, 12,354 (11.7%) IPV, 5,893(5.6%) DTP-IPV-Hib vaccine and 87,054(82.7%) OPV doses were administered to children in the 2010 to 2014 birth cohorts. The proportion of children using an IPV-only schedule increased each year, consistent with the introduction of IPV that is called for by the Polio Eradication Endgame Strategic Plan 2013-2018. During this time, 4.7% children used a schedule containing both IPV and oral poliovirus vaccine (OPV). In the 2012 to 2013 birth cohorts, 14.4% children used an IPV-only schedule; 5.7% children used a sequential schedule, and 79.9% used OPV-only schedule. Use of IPV only schedules was higher among migrant children than among resident children. Among those sequential schedule using both IPV and OPV, 87.2% children used IPV for the first dose and 12.8% used OPV for the first dose.JNCIIMS provided a mechanism for tracking IPV and OPV vaccination patterns, and showed areas in need of improvement. Ensuring appropriately sequenced IPV and OPV supports reduction of risk of vaccine associated paralytic polio.

At present, the technology of data mining and analysis of practical stronger and stronger, the connotation of analyzing large data mining technology, characteristics, and according to the characteristics of classification is a series of challenging projects. Hardtop cloud computing can be used in large data mining platform system architecture is analyzed, the paper will be of HDFS and graphs processing technology is introduced in detail.

The current database and artificial intelligence are hot topics in the study of data mining technology, this paper stands in the basis of concept and key technology of cloud computing, Web data mining technology of cloud computing methods, the method to realize the mining technology accordingly.

To update school websites, incorporating personality and ease of maintenance and management, the authors propose the use of a Content Management System (CMS). A CMS is a self-publishing Website platform for university information resources. The system has many features, such as self-service, fast station, self-service custom modules, dynamic replacement site style template, flexible adjustment of dynamic website contents and structures, search engine optimization (SEO) measures, and so forth. Each institution can customize according to their own information platform needs. A CMS greatly shortens the development cycle of the site and promotes the development of information technology on campus.

This paper employs chaos theory into power load forecasting. Lyapunov exponents on chaos theory are calculated to judge whether it is a chaotic system. Delay time and embedding dimension are calculated to reconstruct the phase space and determine the structure of artificial neural network (ANN). Improved back propagation (BP) algorithm based on genetic algorithm (GA) is used to train and forecast. Finally, this paper uses the load data of Shaanxi province power grid of China to complete the short-term load forecasting. The results show that the model in this paper is more effective than classical standard BP neural network model.

Spherical aberrations of the thermal lens of the active media are severe when solid state lasers are strongly pumped. The fundamental mode proflle deteriorates due to the aberrations. Self-consistent modes of a resonator with aberrations are calculated by using the Fox{Li difiraction iterative algorithm. Calculation results show that the aberration induced fundamental mode beam quality deterioration depends greatly on the resonator design. The tolerance of a ∞at{∞at resonator to the aberration coe‐cient is about 30‚ in the middle of stability, where ‚ is the wavelength of laser beam. But for a dynamically stable resonator, 2‚ of spherical aberration will create difiraction loss of more than 40%, if inappropriate design criteria are used. A birefringence compensated laser resonator with two Nd:YAG rods is experimentally studied. The experimental data are in quite good agreement with simulation results.

Different types of FACTS devices are set at the second channel from Xinjiang to Northwest power network, which are close to Qinghai-Tibet HVDC. The action of FACTS may impact on Qinghai-Tibet HVDC. In this paper, the digital-analog hybrid real-time simulation model of the second channel from Xinjiang to Northwest power network is built, which includes FACTS devices and Qinghai-Tibet HVDC system. The physical HVDC protection devices are used, which have the same characteristic with the actual device. Researches are carried out on the impact of the FACTS action on the AC system and Qinghai-Tibet HVDC at the steady state. The impact of FACTS operating condition and switching MCR on power system and Qinghai-Tibet HVDC are studied. Studies show that FACTS can adjust correctly according to the design requirements during steady state and transient process. The network and Qinghai-Tibet HVDC can be in stable operation under different FACTS operating conditions and the MCR switching process. It can provide technical support on the safety and stability of Northwest China grid and Qinghai-Tibet HVDC link.

During the measurement and analysis of micro-total analysis system (μ-TAS), the bulk of the sample injected is about nano-liter, so that the study of microfluidic sensor has been becoming an important aspect of the analytical instrument. According to the principle of the thermal distribution pattern, a microfluidic sensor based on silicon is fabricated with the microelectronic technique and micromechanical process in this paper, including a micro-heater and two temperature sensors. Under the operational mode of the constant heating power, the characteristics of the microfluidic sensor are analyzed. The experimental results indicate that the measurement range of the microfluidic sensor is from 10 to 700 μl/min.

The traversal rate for the liquid medium near a point-of-care testing (POCT) device microfluidic channel edge is faster than that through the body of the channel, which makes the fluid front meniscus becomes concave rather than convex or flat. The concave front is unwished due to its influences on quantitative analysis accuracy and the possibility to generate air bubbles. Here, a unique method, named hydrophobic marking line, is demonstrated. This method used a soft pen with hydrophobic ink to draw two lines along the edges of the channel of a POCT device. Results have shown that the marking lines will eliminate the edge effects and generate convex liquid front. The curvature of the liquid front can be changed by adjusting the marking line width or ink solutions.

Power IGBT module is widely used in high power conversion applications in various fields because of the advantages of high voltage and high current applications. In order to avoid the influence of temperature rise to the device measurement, pulse test method is widely used to test its static and dynamic parameters, So there are single high pulse voltage source and single pulse high current source in power IGBT modules test instruments. For now in the metrology field, how to calibrate its Single High Pulse Voltage source is a difficult problem. Now the amplitude of single high pulse voltage source is above 7kV with the pulse width as 50 microseconds. Based on detailed research on the test principles of the power IGBT modules test instruments, the pulse high voltage divider and the data acquisition unit are used to setup a calibration device for Single High Pulse Voltage source to calibrate the amplitude of Single High Pulse Voltage source. Resistors are usedto develop the pulse high voltage divider, and did carefully research on the pulse response time, voltage dispersion, voltage regulation of the pulse high voltage divider. Also the data acquisition unit with 20MHz bandwidth and 100MS/s acquisition rate is evaluated through tests including vertical accuracy test, bandwidth test, rise time test, comparison test and etc.. Through above relevant test results, with the comprehensive consideration of the influence of each measurement uncertainty component, It have finished that the evaluation of the uncertainties of the amplitude measurement for Single High Pulse Voltage source. The uncertainty of measurement is better than 2% with the coverage factor as 2.

Aiming at the issues of session persistence and load balancing in large-scale power consumers access, this paper studied the cookie session persistence mechanisms on Web applications, and proposed a session persistence mechanism, which includes a session persistence strategy to realize load balancing combing session sever with cookie. Experiments show that the mechanism could effectively solve the problem of large-scale power consumers access, and the performance on response time is acceptable. The practical values of this mechanism are good.

Here we present one design based on OWDP for secure high-speed IP network performance monitor system. Based on the analysis of OWDP protocol and the high-speed IP network performance's real-time monitor infrastructure, the paper illustrates the potential security problems in OWDP and its possible weakness when applied in the monitor infrastructure. One secure improvement design based on Otway-Rees authentication protocol is put forward, which can improve the security of the implementation of OWDP and the monitor architecture. Having kept OWDP's simplicity and efficiency, the design satisfies the real-time demand of high-speed network performance monitor and will effectively safeguard the monitor procedure against intensive attacks.

Brain-Computer Interface (BCI) systems support direct communication and control between brain and external devices without use of peripheral nerves and muscles. A typical Electrocorticography (ECoG) based invasive BCI system was off-line analyzed in this paper. Firstly, Band Power (BP) features were used for channels selection, and 11 channels with distinctive features were selected from 64 channels. Then, BP features were used for feature extraction of 11 channels ECoG, and feature vectors of 22 dimensions were got. Finally, k Nearest Neighbor (kNN) was used for classification of two different mental tasks (imaged movement of left finger or tongue). The off-line analysis results show that this method has got good classification accuracy for the test data set.