bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimal controller design based on minimum principle
Authors: Da Huang , ShuCai Huang
Published: June 2018

Optimal control theory is the foundation of the modern control theory, the minimum principle in optimal control theory has a very important position, using the minimum principle to design an adaptive controller, the controller integration advantages of the principle of minimum is not affected by the control system of linear or nonlinear constraints, and the end state and free time, is accused of quantity can be controlled and are free to wait for a characteristic, using the minimum controller application example and simulation, the results show that the minimum principle of the designed controller has the ideal control effect.
Research on SQL injection detection technology based on SVM
Authors: Chen Zhuang , Guo Min , zhou Lin
Published: June 2018

SQL injection, which has the characteristics of great harm and fast variation, has always ranked the top of the OWASP TOP 10, which has always been a hot spot in the research of web security. In view of the difficulty of detecting unknown attacks by the existing rule matching method, a method of SQL injection detection based on machine learning is proposed. And the author analyses the method of SQL injection feature extraction, f Finally, the word2vec method is selected to process the text data of the HTTP request, which can effectively represent the SQL injection features containing the attack payload. Training and classification of processed samples with SVM algorithm, The experiment shows that this method effectively solves the problem of SQL injection to the mutation and the high leakage rate of the rule matching. By comparing with the classification results of statistical features, this SQL injection classification model has a higher detection rate.
Short-term Load Forecasting Model for Microgrid Based on HSA-SVM
Authors: Aoyang Han , Litao Yu , Shuhuai An , Zhisheng Zhang
Published: June 2018

Short-term load forecasting for microgrid is the basis of the research on scheduling techniques of microgrid. Accurate load forecasting for microgrid will provide the necessary basis for cooperative optimization scheduling. Short-term loadforecasting model for microgrid based on support vector machine(SVM) is constructed in this paper. The harmony search optimization algorithm(HSA) is used to optimize the parameters of the SVM model, because it has the advantages of fast convergence speed and better optimization ability. Through the simulation and test of the actual microgrid load system, it is proved that the short-term loadforecasting model for microgrid based on HSA-SVM can effectively improve the prediction accuracy.
An Improved Speculative Strategy for Heterogeneous Spark Cluster
Authors: Zhang Pengfei , Guo Zonghuai
Published: June 2018

Apache Spark is an open-source in-memory cluster-computing framework. Spark decomposes an application into numerous tasks and assigns them to computing nodes for higher efficiency. However, in heterogeneous environments, some tasks become stragglers because of poor performance of some computing nodes, data skew, etc. These stragglers can affect cluster performance seriously since a job completes just when the last undertaking completions. To mitigate stragglers, Spark uses speculative execution which recognizes slow tasks and picks the node to run speculative task, but the low accuracy in identification and simple way of backing up will further extend the execution time. Then we develop an improved speculative strategy, DBMTPE (Data-Based Multiple Phases Time Estimation), which selects stragglers by estimating their remaining time and chooses a proper way to run speculative task according to the cause. Experiment results show that DBMTPE can run applications up to 10.5% faster over Spark-Native and save computing resource at the same time.
Shape Modeling Based on Convolutional Restricted Boltzmann Machines
Authors: Wang Xi-Li , Chen Fen
Published: June 2018

This paper proposes a kind of shape model based on convolutional restricted Boltzmann machines(CRBM), which can be used to assist the task of image target detection and classification. The CRBM is a generative model that can model shapes through the generative capabilities of the model. This paper presents the visual representation, construction process and training method of the model construction. This paper does experiments on the Weizmann Horse dataset. The results show that, compared with RBM, although the training time of this model is slightly longer, the test time of the model is similar, and it can better shape modeling, modeling of the details of the shape can be well expressed. The samples generated from CRBM look more realistic. The difference between the shape and the original shape generated by Euclidean distance measurement shows that the model has a strong ability to model shapes.
Energy Flow Hybrid Petri Nets Model of Steel Enterprises
Authors: Ye-Qing Zhao
Published: June 2018

As the urgency of current energy-saving and discharge reduction task and difficult of related advance technology in breaking through, a new energy flow network system model was built based on modelling elements and rules of hybrid Petri nets to adapt to the system requirements through analyzing the basis features of energy flow network, and meet the demand of developing energy flow network efficiency of iron and steel enterprises. The dynamic rules and behaviour mechanism of energy flow network system for iron and steel enterprises were studied by utilizing the model combined with the historical data, the results show that the modelling method is effective and satisfactory, and provide guidance for optimizing the energy system and exploring the relation of material flow and energy flow.
A Novel Fast Voltage Sequence Component Detector of Unbalanced Three-Phase System
Authors: Jiang Baohong , Li Xinian
Published: June 2018

The fast and accurate voltage sequence component detection of unbalanced three-phase system is of major importance for the industrial continuous processing. The traditional method is to calculate the voltage in dq synchronous reference frame. This results in low order harmonics and long detection time. A novel fast voltage sequence components detector is proposed in this paper. It is to calculate the sequence component projection on dq rotating reference frame with h times the fundamental angular velocity. Simulation results demonstrate the validity of the algorithm.
Standard Description of Common Element Model Data Type Based On XML Schema
Authors: Qi Yang , Zhulin Wang , Hongyun Wang
Published: June 2018

AI-ESTATE standard uses EXPRESS language to describe its diagnostic knowledge, but EXPRESS is not a programming language, which makes it difficult to implement diagnostics using EXPRESS language description. This makes it difficult to share and reuse diagnostic knowledge; XML language with its good flexibility, readability and extensibility, it has brought great convenience to information exchange. Mapping the EXPRESS language to XML Schema is of great significance for the sharing of diagnostic knowledge. First, the data types of the EXPRESS language and XML Schema are analysed; then, mapping mechanism of the simple data types, aggregate data type, and structural data types to XML data types in EXPRESS are studied separately. Finally, based on the analysis of the AI-ESTATE standard common element model data type, the process of describing the diagnostic knowledge of the common element model using XML Schema standardization is studied, and the diagnostic knowledge can be portable and reused.
Research on Multi-UAV Collaborative Search in Dynamic Environment
Authors: Jia ZHAN , Wenjun XIE , Qing GUO
Published: June 2018

Combine the uncertainty of dynamic targets, a multi-UAV reconnaissance scheduling problem model was constructed under dynamic environment, take advantage of the characteristics of dual evolution, the insertion point operator and reverse sequence operator are improved, and the problem is solved by the artificial bee colony algorithm based on the semi-random search strategy. Finally, the simulation experiment was done in the background of South China Sea, and the experimental result shows the effectiveness and feasibility of the proposed algorithm for solving the multi-UAV reconnaissance scheduling problem.
Calibration-Free Robot-Sensor Calibration approach based on Second-Order Cone Programming
Authors: Wei Li , Naiguang LU , Mingli Dong , Xiaoping Lou
Published: June 2018

In order to overcome the restrictions of traditional robot-sensor calibration method which solve the tool-camera transformation and robot-world transformation rely on calibration target, a calibration-free approach that solve the robot-sensor calibration problem of the form AX = YB based on Second-Order Cone Programming is proposed. First, a Structure-From-Motion approach was used to recover the camera motion matrix up to scaling. Then rotation and translation matrix in calibration equation were parameterized by dual quaternion theory. Finally, the Second-Order Cone Programming method was used to simultaneously solve the optimal solution of camera motion matrix scale factor, the robot-world and hand-eye relation. The experimental results indicate that the calibration precision of rotation relative error is 3.998% and the translation relative error is 0.117% in defect of calibration target as 3D benchmark. Compared with similar methods, the proposed method can effectively improve the calibration accuracy of the robot-world and hand-eye relation, and extend the application field of robot-sensor calibration method.
UAV Flight Stability Control Method Based on Steady - state Error Correction0
Authors: Qing-Xiu Lu , Xing-Hua Lu , Ling-Feng Wang
Published: June 2018

UAV flight stability control system is a multivariable, non - linear, strongly coupled system, the steady-state error is easy to occur with the traditional fuzzy control method. An UAV flight stability control method is proposed based on steady - state error correction, the steady state dynamic model of UAV flight is constructed, and the control constraint model is constructed with the roll angle, the pitch angle, the longitudinal inclination angle and the acceleration as the constraint parameters. The construction of UAV flight stability control objective function is obtained, and the linearization treatment is carried out near the equilibrium point of the flight of the unmanned aerial vehicle, and the equivalent control law of the sliding mode surface is constructed. Based on the conventional synovial surface, an integral term of tracking error is added to reduce the steady-state error and realize adaptive correction of flight parameters. The simulation results show that the stability of the flight control of the UAV is better by the method, and the self - adaptive correction capability of the flight state parameters is strong.
A Study of Integrated Driver fatigue Judging Algorithm Based on Principal Component Analysis
Authors: Ma Zhipeng , Yao Shuwan , Li Junxian
Published: June 2018

As the number of vehicles increases, the probability of fatigue driving rises accordingly, resulting in a boost in the accident rate. Based on principal component analysis, the paper presents a fatigue monitoring algorithm that integrates with facial, EEG, EMG and ECG. First of all, based on the edge detection method, the eyes are positioned and then it has an assessment through the Perclos fatigue. EEG, EMG, ECG indicators evaluate the fatigue with the corresponding fatigue characteristics. Subsequently, the related values of the above four indexes are normalized, and the principal component analysis method (PCA) is utilized to reduce the dimension and merge to get the comprehensive fatigue eigenvalue, and then we get the fatigue level referring to the fatigue level standard. Analyzing the measured data, the algorithm accuracy is 76%.
An Algorithm of Enemy Flight Area in Fleet Air Defense
Authors: Fei Long , Jingdong Sun , Shaobo Tang
Published: June 2018

Aiming at the algorithm of the enemy flight area when the enemy launches air-to-ship missiles in fleet air defense, this paper analyzes the position situation of both parties. On the basis of the analysis, it describes the shape of the enemy flight area, and establishes the calculation model. Finally, a demonstration verification program is developed and the application examples in various cases are given. This algorithm can not only accurately calculate the enemy flight area, but effectively assist the commander to form scientific air defense plans.
Multi-agent ant colony optimization for vehicle routing problem with soft time windows and road condition
Authors: Huang Gewen , Cai Yanguang , Cai Hao
Published: June 2018

In this paper we consider two important objects of transportation, cost and customer satisfaction. The latter mainly depends on vehicle arrival time and expecting time of the customer. Whereas in the reality, road conditions varies at different time periods and affect the vehicle travelling speed. Meanwhile, transport cost, including fuel consumption, relate to load of vehicle. Correspondingly, mathematical model of vehicle routing problem with soft time windows and road factor (VRPSTWRF) was established in which transport cost, fuel consumption and customer satisfaction are considered. Multi-agent ant colony optimization is proposed in which the features of agent perceiving and reacting to the environment are applied reasonably. Adaptive information heuristic factor and pheromone expectation heuristic factor changing mechanism is used to improve global convergence ability. Pheromone is updated adaptively, the fuel consumption rate also considered, to ensure the convergence speed. 3-opt strategy was introduced to improve local search ability. Thus, multi-agent ant colony optimization (MACO) was constructed and used to solve 40-customer VRPSTWRF model. Experiments show that MACO proposed is feasible and valid.
A Review of Smart Grids and Their Future Challenges
Authors: Tian Wen
Published: June 2018

With the development of science and technology and the increasing emphasis on renewableenergy, smart grids are being vigorously developed in many countries and regions including Europe, theUnited States and China. The smart grid is the main practice trend of efficient transmission of modernpower resources. It has the advantages of good power transmission, low resource loss and strong correlationof resources transmission. Therefore, it occupies an important position in large-scale utilization of powerresources. Thus, this paper, based on the theory of smart grid, discusses the research direction, practicalinnovation and application of smart grid, provides theoretical reference for the comprehensive utilization ofpower resources in China, and promotes the intelligent exploration of domestic electric resource application.
Design of Intelligent Vehicle Monitoring System Based on ZigBee
Authors: Ma Jiandong
Published: June 2018

In order to meet the needs of real-time positioning and remote dispatching of vehicle, this paper designs a ZigBee-based embedded vehicle terminal and the corresponding ZigBee-GPRS information communication network in hardware and software. With LPC2366 processor and CC2430 RF chip as core, the vehicle terminal acquires the vehicle‘s status in cycle, and completes the vehicle monitoring and scheduling by transmitting data to communication nodes by ZigBee and passing the data on to the monitoring center by GPRS. This vehicle terminal is characterized by small size, low energy consumption and ideal communication distance, which makes the monitoring center effectively monitor and schedule the vehicles.
The Cause and Eliminate Method of Self-excited Oscillation in Long Cable Amplifier Circuits
Authors: Wang Can , Huang Ming , Peng Zhaomin , Cui Jinbao
Published: June 2018

SMA long cable distributed capacitance is easy to trigger broadband amplifier circuit’s self-oscillation. In this study we design an amplifier circuit based on OPA691 chip, discuss the influence of long cable’s distributed capacitance, then prompt a solution to add 50Ω compensation resistor between the output terminal and the load capacitance. According to the Tina simulation analysis, when 50Ω compensation resistor is added, bode diagrams show amplitude characteristic is smaller than 0 dB at -180 ° phase. The selfoscillation also disappeared in actual circuit measurement, which verify the rationality of this solution.
Hybrid methods for composite scattering from conductive target above a rough surface
Authors: Tian Gui-Long , Tong Chuan-Ming , Liu Hao , Long Zheng-Guo , Wang Jian-Jun
Published: June 2018

A hybrid method combining the method of moment (MoM) and physical optical (PO) is used to compute the scattering from 3D conductive target above a rough sea surface in this paper. Firstly, the composite model of 3D conductive target above the sea surface is constructed. The rough sea surface is simulated by the Pierson-Moscowitz spectrum and Monte-Caro method. The target is divided into MoM region and the rough sea surface is divided into PO region. Then, the current on the facet of target is obtained by MoM method and the current on the facet of rough surface is obtained by PO approximation. Compared to the method of moment, the hybrid MoM-PO method proves to be high accurate and efficient. Finally, composite scattering under different condition are studied in detained.
A Control Strategy of a Single-phase H6-type Grid-connected Inverter with Low Harmonic Current
Authors: Chunxu Lin , Chunhua Zhou , Wei Li , Rui Chen
Published: June 2018

In order to reduce the total harmonic distortion (THD) of the grid-connected current caused by the high-frequency switching of the inverter, this paper combines the high efficiency single-phase H6-type inverter with LCL filter. The double closed-loop control method that consists of grid-connected current outer loop and capacitor current inner loop is put forward, by which a resonance peak of a low damping LCL filter is eliminated. In the grid-connected current outer loop, quasi proportion resonant (QPR) controller is adopted to overcome the steady-state error and weak anti-jamming capability in traditional PI controller. Finally, a simulation model is built in SIMULINK to verify the research. The simulation results show that, based on the single-phase H6-type inverter and LCL filter, the double closed-loop QPR control strategy can achieve the static error free tracking control of grid-connected current, which makes the system more stable and reduces the THD of grid-connected current effectively.
Single-ended method to accurately calculate UHV AC transmission line frequency parameters
Authors: Fan GAN , Nana ZHANG , Yun-ge LI , Zhouxing Fu
Published: June 2018

The power frequency parameter of transmission line is the basic parameter of line over-voltage calculation. It is necessary to get the parameters of 1000kV AC double-circuit line on the same tower in order to guide the operation of the project. In this paper, a method of accurately calculating UHV transmission line parameters is proposed. The length of the line is known, the voltage and current at the head of the line are measured, and the zero sequence, positive sequence total impedance and total capacitive reactance are obtained. Based on the distribution parameters Calculation formula, the line unit capacitance, resistance and inductance parameters can be obtained. The method of this paper is compared with the simulation of transmission line parameters in ATP simulation. And Through the actual measurement of the frequency parameters of Yu-heng 1000kV transmission line, it is verified that this method is suitable for the calculation of distribution parameters of UHV transmission lines.
Acquisition and Registration of Human Point Cloud Based on Depth Camera
Authors: Wang Huibai , Wang Shengyu
Published: June 2018

Registration of human cloud points is a key step in 3D human reconstruction. So, this paper proposes using depth camera to acquire human point cloud. Then, using feature matching and PnP (Perspective-n-Point) to solve the camera pose.Finally, use least square to optimize camera pose and implement point cloud registration. Experimental results show the effectiveness of this method.
Analysis of surface temperature characteristics of multiscale fusion based on convolution neural network
Authors: Meng Yixue
Published: June 2018

Intelligent detection of surface temperature 1, describing macro characteristics of microcosmic combination, promotes the cross fusion of geoscience, thermodynamics, climatology, geological science, and so on. However, there are still two notable problems to be solved. One is the model lacks characterization capability, and the other is that the precision of surface temperature’s monitoring and prediction is low. To solve these problems, we propose an algorithm to predict surface temperature characteristics of multiscale fusion based on convolution neural network. Firstly, after researching the multiscale disturbance characteristics of surface temperature, we draw a conclusion based on analyzing time change, spatial change, casual change. To improve the parameter correlations among surface temperature characteristics, a neural network about compensating and optimizing analysis of surface temperature characteristics is proposed on the fundamental of multivariate surface temperature characterization models. By designing cluster input layer, dynamic hidden layer and visual output layer of neural network, the precise of predict data has been improved by 53.3% on average, and 76.0% on variance compared with remote sensing data. What’s more, the data consumption of this model has promoted by 17.2% in contrast to grey theory on predictive complexity and precision, and 10.8% compared with BP neural network.
Research on Metonymy of Cognitive Linguistics from Corpus Approach of Computer Science
Authors: LUO Ruifeng
Published: June 2018

The rapid development of computer technology and corpus linguistics has realized the large-scale corpus’s collection, arrangement, annotation and processing. The corpus linguistics combines description with empirical analysis, and qualitative research with quantitative research that the various language phenomenons can be fully explained. The paper makes use of corpus-based approach to study Metonymy of Cognitive Linguistics and draws real data from Center for Chinese Linguistics Peking University of China (CCL), which makes the research more convincing.
Recommender systems based on opinion mining and deep neural networks
Authors: Li Jia , Yang YongJian
Published: June 2018

To address rating sparsity problem, various review-based recommender systems have been developed in recent years. Most of them extract topics, opinions, and emotional polarity from the reviews by using the techniques of text analysis and opinion mining. According to existing researches, review-based recommendation methods utilize review elements in rating prediction model, but underuse the actual ratings provided by users. In this paper, we adopt one lexicon-based opinion mining method to extract opinions hidden in reviews, and also, we combine opinions with actual ratings. In addition, we embed deep neural networks model which breaks through the limitation of traditional collaborative filtering. The experimental results based on two public datasets indicate that this personalized model provides an effective recommendation performance.
Review on the Evaluation Frameworks of Non-academic Impact of Scientific Research
Authors: Jin Xuehui , Xi Guiquan , Cong Lin
Published: June 2018

Assessing the academic impact of scientific research had made great achievement, but non-academic impact had been neglected for long time in China. This paper used documentary research to analyze representative evaluation frameworks and then summarize the corresponding relation between different evaluation frameworks and their guiding theories. This paper believed that people need to analyze the different conditions when using them because of different frameworks with different background. At last this paper advocated the non-academic impact of research should be paid attention to knowledge consumers from the wider social class, not only to decision makers. It was also well worth studying the timing of non-academic impact of research.
Research on User Identity Authentication Based on Two-way Confirmation in Data Transmission
Authors: Li Qin , Liu Caiming , Jing Siyuan , Du Lijun
Published: June 2018

User identity authentication is the foundation of data transmission in the complicated network environment. Moreover, the key issue is the effective identity authentication of both sides in data transmission. An authentication method for user identity based on two-way confirmation in data transmission is proposed in this paper. The public key, private key, information of traditional identity authentication, one-time transmission key, timestamp, authentication lifecycle for timestamp and other authentication elements are constructed. Based on guaranteeing the timeliness of data transmission, the two-way user identity authentication process for sending terminal and receiving terminal is set up through using the information of traditional identity authentication and one-time transmission key.
A Method for Recommending Bug Fixer Using Community Q&A Information
Authors: Wei Qingjie , Liu Jiao , Chen Jun
Published: June 2018

It is a very time-consuming task to assign a bug report to the most suitable fixer in large open source software projects. Therefore, it is very necessary to propose an effective recommendation method for bug fixer. Most research in this area translate it into a text classification problem and use machine learning or information retrieval methods to recommend the bug fixer. These methods are complex and overdependent on the fixers’ prior bug-fixing activities. In this paper, we propose a more effective bug fixer recommendation method which uses the community Q & A platforms (such as Stack Overflow) to measure the fixers’ expertise and uses the fixed bugs to measure the time-aware of fixers’ fixed work. The experimental results show that the proposed method is more accurate than most of current restoration methods.
Blind separation of PCMA signals based on neural network
Authors: Chi WEI , Hua PENG , Zeyu QIU
Published: June 2018

For paired carrier multiple access (PCMA) signals, a new single-channel blind separation on neural network was proposed. Firstly, the sample waveforms (three symbols) which contains different bit information are constructed, secondly, the time-frequency spectrum of each sample under the different influences of the trailing symbols is Intercepted, finally, the characteristic data of the spectrum as the input data, and the two-bit sequence in each sample as the output data to be trained, network trains these data repeatedly to complete the construction of separation model. The receiver carries on window truncation to the time-frequency spectrum of PCMA signal, neural network recognize the characteristic data of these spectrums to realizes the separation of bit sequences. Experimental results show that this algorithm has lower complexity than PSP algorithm, and the accuracy of it is close to PSP algorithm (L=5).
Multi-Level Attribute-Based Encryption Access Control Scheme for Big Data
Authors: Li Zhao , Huan Shuiyuan
Published: June 2018

There are many security threats such as data’s confidentiality and privacy protection in the new application scenario of big data processing, and for the problems such as coarse granularity and low sharing capability existing in the current research on big data access control, a new model to support fine-grained access control and flexible attribute change is proposed. Based on CP-ABE method, a multi-level attribute-based encryption scheme is designed to solve fine-grained access control problem. And to solve the problem of attribute revocation, the technique of re-encryption and version number tag is integrated into the scheme. The analysis shows that the proposed scheme can meet the security requirement of access control in big data processing environment, and has an advantage in computational overhead compared with the previous schemes.
Time-frequency Analysis of Multicomponent LFM signal based on Hough and Chirplet Transform
Authors: Zhang Xueqin , Liu Ruolun
Published: June 2018

The Chirplet Transform (CT) is effective in the characterization of IF for mono-component linear-frequency-modulated signal. However, During the initialization process, using the peak of the time-frequency map of the short-time Fourier transform to fit the line is greatly affected by noise. For the multi-component signals, it is more difficult to distinguish and fit different IF lines. Since the Hough is good at a common algorithm for the line detection, the ridge edge fitting is replaced by the Hough transform in this paper. The experiment results show significant improvement in the obtained time-frequency representation.
Detecting Concept Drift in Resource-Service Sequence for Collaborative Task
Authors: Lin Tangquan , Li Haibo , Sun Yingchuan
Published: June 2018

To discover the bottleneck of business caused by the changing of market, especially in collaborative tasks, an approach is proposed to detect concept drift in the usage of resource services in business processes. Firstly, influence degree, described as features, is measured in a Resource-Service Sequence (RSS). Secondly, by mining business dataset, the influence relationship between resource services is resolved according to different time window. Then, the influence degrees are clustered as different clusters, called concept drift. Finally, RSSs with concept drift are derived from the feature sequence. The simulation results show the validity of the proposed approach.
Visualization for compressed natural gas(CNG) secondary station refilling behaviors
Authors: Li Yang , Zhao Yulian , Shao Jian
Published: June 2018

Data visualizations are recently used for providing an access to complex data and information. In this paper, the visualization method is adopted to find possible ways of improving CNG secondary filling station’s refilling efficiency. Based on single attribute of volume, initial and final pressure, the visualization results show that one possible way to improve refilling efficiency is to by avoid abnormal inefficient refilling behaviors with small volume, higher initial pressure or lower final pressure. Based on time, the visualization results, considering the periodic property of refilling behaviors, present another possible way to improve refilling efficiency through reducing inefficient use of time. From the refilling log’s visualization, it is found that there is room for improvement in refilling efficiency and possible improving ways are primary studied. But the reasons of these abnormal actions are needed to be studied in future research.
An expression recognition algorithm based on convolution neural network and RGB-D Images
Authors: binghua HE , zengzhao CHEN , gaoyang LI , lang JIANG , zhao ZHANG , chunlin DENG
Published: June 2018

Aiming at the problem of recognition effect is not stable when 2D facial expression recognition in the complex illumination and posture changes. A facial expression recognition algorithm based on RGB-D dynamic sequence analysis is proposed. The algorithm uses LBP features which are robust to illumination, and adds depth information to study the facial expression recognition. The algorithm firstly extracts 3D texture features of preprocessed RGB-D facial expression sequence, and then uses the CNN to train the dataset. At the same time, in order to verify the performance of the algorithm, a comprehensive facial expression library including 2D image, video and 3D depth information is constructed with the help of Intel RealSense technology. The experimental results show that the proposed algorithm has some advantages over other RGB-D facial expression recognition algorithms in training time and recognition rate, and has certain reference value for future research in facial expression recognition.
Research of Intersection Groups Optimization Control Method Based on Critical Path Identification
Authors: Liu Ying , Fang Lv , Shen Jiayan
Published: June 2018

An optimal intersection groups control method based on critical path identification is proposed. The control algorithm uses a binary search to gradually determine the scope of the intersection groups, uses the duality method to express the intersection groups, uses breadth-first search algorithm to solve the critical path, and finally uses the branch-and-bound method to solve the lane canalization, realizes the optimized output of phase-sequence and timing of intersection control signals. The control algorithm is realized using C++ language, including the following functional modules: intersection range dynamic definition, critical path identification, space-time resource optimization, and online timing adjustment of signal timing parameters and so on. Finally, the control algorithm is verified by the actual road network of Changzhou City of China, the result shows that, the efficiency of traffic operation is significantly improved.
Application of Wavelet Analysis Model Based on Hilbert Transform in Measles Outbreak Period
Authors: Tan Wang , Yang Qianqian , Nie Rencong
Published: June 2018

Objective To study the trend of cycle activity of measles epidemic from 1950 to 2014 and establish a model to predict the national incidence of measles in the future. Methods Using the national measles monitoring data from 1950 to 2014, we establish a information database. Then, we set up the wavelet analysis model based on Hilbert transform to study the cycle of measles incidence. Finally, we establish the ARIMA model of measles risk level to predict the incidence of measles by SPSS software. Results Wavelet analysis shows that the outbreak cycle of the incidence of measles is getting longer in the time dimension. ARIMA model analysis shows that national incidence of measles will fluctuate and decline in the next 36 years, which is may related to the improvement of medical standards and people’s awareness of the measles prevention. Conclusions The national incidence of measles is declining. It is cyclical and its outbreak cycle is getting longer. Data shows that the incidence of measles will gradually decrease in the future, and gradually achieve the global goal of eliminating measles.
Research on the internal influence factors of the text multi-classification problem
Authors: Mingqiang Wu , Chang Furong , Zhang Kui
Published: June 2018

This paper mainly deals with the classification of text type data. The statistics show that more than 8000 articles have been reached in all kinds of documents retrieved by the optical network. However, there are few papers on the factors that affect the classification of text. The text classification method used is important, but the internal factors sometimes play a great role, and even affect the success or failure of the whole text classification. In order to make up for this deficiency, this paper selects the Rocchio algorithm as the classification method, mainly from the category clustering density, class complexity, category definition, stop words and document’s length five internal factors, we tested their influences on text classification by the experiment. Experiment shows that the clustering density is higher and the complexity of the lower class, class definition is higher, the higher the accuracy of text classification, text classification effect is better, and better effect to text stop words, the length of the text does not directly affect the effect of text classification, but according to the text classification algorithm is more suitable to choose the length of the document.
A Broadband Spectrum Sensing Algorithm in TDCS Based on ICoSaMP Reconstruction
Authors: Yang Liu , Qinghua Ren , Bingzheng Xu , Xiazhao Li
Published: June 2018

In order to solve the problem that the wideband compressive sensing reconstruction algorithm cannot accurately recover the signal under the condition of blind sparsity in the low SNR environment of the transform domain communication system. This paper use band occupancy rates to estimate sparseness roughly, at the same time, use the residual ratio threshold as iteration termination condition to reduce the influence of the system noise. Therefore, an ICoSaMP(Improved Compressive Sampling Matching Pursuit) algorithm is proposed. The simulation results show that compared with CoSaMP algorithm, the ICoSaMP algorithm increases the probability of reconstruction under the same SNR environment and the same sparse degree. The mean square error under the blind sparsity is reduced.
The Method of MMC Redundancy Optimization Allocation Based on Multi-objective Optimization
Authors: Jin Enshu , Zhang Yagu
Published: June 2018

When the modular multi-level converter of the sub-module faults, which will cause the unbalanced system, affect the normal operation of the system, so to the MMC arm configuration redundant sub-module is necessary, if the sub-module faults, redundant sub-modules will replace the fault sub-module maintaining the normal operation of system. In this paper, we propose a reasonable and effective method for the configuration optimization of redundant sub-module based on the three indexes, namely, efficient utilization of redundant sub-module, the number of redundant sub-module and the reliability of the system MMC, considering the three factors, establishing a multi-objective optimization function of redundant configuration, By calculating the optimal value to accurately calculate the number of redundant sub-module of MMC, based on the proposed redundancy configuration optimization method, building a simulation model of MMC 5 level in PSCAD, the results verify the rationality and feasibility of the proposed optimization method.
Fault Ride Through Strategy for Offshore Wind Farm Integration System via MMC-HVDC
Authors: Lijun Zhang , Yujun Zhong , Rui Chen , Yikai Sun , Jing Zhang , Ke Jia
Published: June 2018

When offshore wind power is transmitted to ac grid through MMC-HVDC, the current and voltage will be quite different from those in traditional ac grid during grid side fault. This paper sets up an offshore wind farm integration system via MMC-HVDC and designs control strategies for each unit in the system. The fault ride through strategy of the system is proposed and its effectiveness has been verified. Thus, the AC bus voltage on wind farm side will stay stable during AC side fault. Once the chopper resistance is set properly, the output power and current of the wind farm can basically remain unchanged, which can successfully achieve fault isolation. The simulation results based on PSCAD have verified the theoretical analysis.
Anomaly Detection for Hyperspectral Images Based on Anisotropic Spatial-Spectral Total Variation and Sparse Constraint
Authors: Huihui Ju , Zhigang Liu , Jiang Jiangjun , Wang Yang
Published: June 2018

A novel anomaly detection method for hyperspectral images (HSIs) is proposed based on anisotropic spatial-spectral total variation and sparse constraint. HSIs are assumed to be not only smooth in spectral dimension but also piecewise smooth in spatial dimension. The proposed method adopts the anisotropic spatial-spectral total variation model which combines 2D spatial total variation and 1D spectral variation to explore the spatial-spectral smooth property of HSIs. Meanwhile, the sparse property of anomalies is exploited for its low probability in the image. To utilize both the spatial and spectral information of HSIs, we preserve the original cubic form of HSIs and divide the HSIs into three 3D arrays, each representing the background, the anomaly, and the noise respectively. By using anisotropic spatial-spectral total variation regularization on the background component and sparse constraint on the anomaly component, this anomaly detection problem has therefore been formulated as a constraint optimization problem whose solution has been derived by alternately using Split Bregman Method and Go Decomposition (GoDec) Method. Experimental results on hyperspectral datasets illustrate that our proposed method has a better detection performance than state-of-the-art hyperspectral anomaly detection methods.
A Design of Trusted Computing Supporting Software based on Security Function
Authors: Jing LENG , Fan HE
Published: June 2018

Most of existing TCSS have defined the functional interface of software in accordance with TCG specification. However, there is no clear definition of the security functional requirements and security targets that TCSS needs to meet in TCG specification. An implementation scheme for TCSS was proposed, and a TCSS prototype on the basis of Common Criteria (CC), combining with TCSS security function division and practical application demands was implemented. The experimental results show that the proposed software prototype can support the interface call of the TPM 2.0 and the SM4 cipher algorithm of China.
Analog Circuit Fault Diagnosis Based on Adaptive Gaussian Deep Belief Network
Authors: Ying-chen WANG , Xiu-sheng DUAN
Published: June 2018

Aiming at the problem that the traditional intelligent fault diagnosis method is overly dependent on feature extraction and the lack of generalization ability, deep belief network is proposed for the fault diagnosis of the analog circuit; Then, by analyzing the deficiency of deep belief network application, a Gaussian deep belief network based on adaptive learning rate is proposed. The automatic adjustment learning step is adopted to further improve fault diagnosis efficiency and diagnosis accuracy; Finally, particle swarm support vector machine to extract the fault characteristics to identify. The simulation results of circuit fault diagnosis show that the algorithm has faster convergence speed and higher fault diagnosis accuracy.
Heterogeneous Network Access Network Selection Algorithm Based on Analytic Hierarchy Process and Improved Variable Weight
Authors: Juanping Cui , Jinsha Yuan , Zhixiong Chen , Huale Zhang , Dongsheng Han
Published: June 2018

Aiming at the problem that the weights of constant weights cannot be changed once they are determined, this paper proposes a network access selection algorithm based on analytic hierarchy process and improved variable weight. The algorithm calculates the weights of indexes based on the analytic hierarchy process, and then introduces the improved punishment variable weight theory. According to user and traffic preferences, the indexes are prioritized. When indexes are flawed, different levels of indexes are subject to different levels of punishment. The algorithm can change the constant weight based on actual parameter values and user preferences, which makes the final decision-making result more scientific and reasonable.
Wer hat Recht?
Authors: Büssing Arndt
Published: June 2018

Woher kommt eigentlich unsere Gewissheit, dass das, was wir tun und denken, richtig ist? Womit ist eigentlich unsere Überzeugung begründet, dass unsere Sichtweise der Dinge die richtige und dass diese „alternativlos“ ist?
Fachbibliotheken und Literaturdatenbanken als Quellen der Evidenz in der Integrativen Medizin
Authors: Raak Christa , Ostermann Thomas
Published: June 2018

Trotz einer wachsenden Zahl wissenschaftlicher Publikationen im Bereich der Integrativen Onkologie ist es immer noch schwierig, einen Überblick über die publizierte Evidenz zu erhalten. Fachbibliotheken und Literaturdatenbanken können dabei als Quellen zur Evidenzbasierung herangezogen werden. Dieser Artikel zeigt nach einer Einleitung in das Thema die Möglichkeiten auf, die CAMbase und Arthedata bieten, zwei online verfügbare Literaturdatenbanken für Therapeuten, Ärzte und Wissenschaftler. Sie sind kostenlos und ohne Registrierung nutzbar.
Diabetes mellitus vor und nach Nierentransplantation
Authors: Guthoff Martina
Published: June 2018

Der Diabetes mellitus stellt heutzutage die häufigste Ursache für eine terminale Niereninsuffizienz dar. Ein manifester Diabetes limitiert für die Patienten oft
den Zugang zur Transplantation als bestem Nierenersatzverfahren und ist für die Prognose nach erfolgreicher Transplantation weiter entscheidend. Ein Diabetes
nach Transplantation (PTDM) hat ebenfalls erhebliche prognostische Implikationen für das Patienten- und Transplantatüberleben. Nach Transplantation weisen mehr
als 50 % der Patienten einen gestörten Glukosestoffwechsel auf. Präventive Strategien sind daher unabdingbar und umfassen alle Phasen der Transplantation. Sie
lassen sich aus den bekannten Risikofaktoren ableiten und beinhalten insbesondere die strukturierte Lebensstilintervention sowie Maßnahmen zur
β-Zell-Protektion. Konsequentes Screening und frühzeitiges Eingreifen sind für die Patienten nach Nierentransplantation von entscheidender Bedeutung, um sowohl
das Patienten- als auch das Transplantatüberleben langfristig zu verbessern.
Synergistic Anti-proliferative Effects of Metformin and Silibinin Combination on T47D Breast Cancer Cells via hTERT and Cyclin D1 Inhibition
Authors: Chatran Mina , Pilehvar-Soltanahmadi Younes , Dadashpour Mehdi , Faramarzi Leila , Rasouli Sara , Jafari-Gharabaghlou Davoud , Asbaghi Navid , Zarghami Nosratollah
Published: June 2018

Background There is a growing body of data that chemotherapeutic combination strategies would be more effective in reducing drug toxicity, inhibiting tumor progression in comparison to either drug alone.

Objective To explore a chemopreventive strategy for improving breast cancer treatment efficacy, the anticancer effects of a combination of Metformin (MET) and Silibinin (SIL) were investigated in T47D breast cancer cells.

Materials and Methods Cytotoxicity of the drugs individually and in combination was evaluated using MTT assay. The precise nature of the interaction between MET and SIL was further analyzed through the median-effect method. In addition, qRT-PCR was applied to determine the expression levels of hTERT and cyclin D1 genes after 48 h drug exposure.

Results MTT assays showed that MET and SIL individually inhibited the cell viability in a dose and time-dependent manner, and the obtained combination indices (CIs) were<1 for all the combination treatments, indicating that the anticancer agents synergistically induced growth inhibition in the breast cancer cells. qPCR findings revealed that the drug combination also synergistically down-regulated the expression levels of hTERT and cyclin D1 at all used concentrations compared with the drugs used alone after 48 h treatment (P≤0.05).

Conclusion The results provide evidence that synergistic antiproliferative effects of MET and SIL, linking to the down-regulation of Cyclin D1 and hTERT genes, and propose that MET+SIL may have therapeutic value in breast cancer therapy.
Perfluorinated Ammonium and Phosphonium Ionic Liquids
Authors: Christoffers Jens , Alpers Torben , Muesmann Thomas , Temme Oliver
Published: June 2018

Ammonium and phosphonium ionic liquids with perfluorinated side chains were prepared as hybrid materials for surface impregnation. Melting points of the triflimide salts range up to 95 °C. The key feature of this investigation are relatively short perfluorohexyl residues as the fluorinated part of the cations, making the target compounds beneficial alternatives to established products because of their enhanced degradability and therefore lower bioaccumulativity. In the ammonium series, pyrrolidinium, piperidinium, morpholinium triflimides as well as the dication derived from DABCO were prepared. Mono-phosphonium triflimides were obtained from triphenyl- and diphenylphosphane. Diphosphonium bistriflimides were obtained from bis(diphenylphosphano)alkanes, Ph2P(CH2)nPPh2 with n = 2–5. As alkylating reagents, n-C6F13CH2CH2OTf and n-C6F13CH2CH2I were applied.
Metal-free Reduction of Nitro Aromatics to Amines with B2(OH)4/H2O
Authors: Zhou Haifeng , Uozumi Yasuhiro , Chen Danyi , Zhou Yanmei , Liu Sensheng , Liu Qixing , Zhang Kaili
Published: June 2018

A metal-free reduction of nitro aromatics mediated by di­boronic acid with water as both the hydrogen donor and solvent under mild conditions has been developed. A series of aromatic amines were obtained with good functional group tolerance and in good yields.