Abstract:In the indoor environment, the previous artificial landmark design scheme is complex in recognition algorithm with low accuracy, and it is hard to meet the real-time requirements. In view of such problems, two new kinds of artificial landmarks are designed in this paper:location artificial landmark and correction artificial landmark, which can not only help the indoor mobile robot to navigate and rectify, but also have the advantages of simple and rapid identification. The robot can identify location artificial landmark in real time, and adjust its position and movement direction according to the correction artificial landmark, so that the robot can move forward smoothly along the planned path. Experiments show that in dark, moderate, strong light indoors, the recognition of two kinds of artificial landmark is highly accurate and fast, which can meet the requirements of real-time navigation.

Abstract:In the application of Credit algorithms, the VCPU awakened by the I/O transaction is in the highest priority BOOST state, which gives it priority to gain access to the PCPU resources and improves the response speed of the I/O operation, but that will cause long time delay and destroy fairness principle, when multiple virtual machines are doing the operation of I/O at the same time. To solve this problem, SEDF algorithm, Credit algorithm, Credit2 algorithm are analyzed and L-Credit scheduling algorithm is proposed to reduce the response delay caused by multiple virtual machines' concurrent I/O operation. By monitoring I/O device ring sharing page to get the number of requests, which can further refine the sort in the I/O state BOOST operation, so that sparse type I/O operation can the implementation before the I/O intensive operations. According to the comparison report of the L-Credit algorithm and Credit algorithm in the same application scenario experiment, L-Credit algorithm can improve the performance of the I/O response, and inherits the Credit algorithm load balance and the characteristics of proportional fair sharing.

Abstract:With the rapid development of the crowd-funding, the rapid increase in the number of such projects costs investors a lot of time and effort. This paper aims to help investors select high-quality crowd-funding projects with the least time. Under the assumption that there is a positive correlation between the quality of public projects and the completion ratio of financing(Ratio), the model in this paper is modeled using the CART regression tree algorithm based on the JD Crowd-funding data with R² reaching 0.746. The results show that investors should focus on the Target Amount (TA), the Follower, the Progress and the Topic. The results of this paper are only applicable to reward-based crowd-funding projects. For other types of Crowd-funding, the independent variables should be re-selected for model building, but the decision tree model can still be applied.

Abstract:Aiming at the defects of CERNET in network planning, construction and management, this paper analyzes the main factors of network security management, network security management maturity gradient model division, and puts forward the maturity of the five levels-five gradient matrix, which constructs a network security management maturity model. This model can not only detect the security vulnerabilities in the management of CERNET network, but also improve the safety management level, which is proved by the analysis of defects from Sichuan Vocational College of Information Technology campus network security management with the model, the results of which show that the Academy reaches maturity specification level.

Abstract:With the promotion of "Made in China 2025", the supply in industrial power is in a growing demand for large aluminum electrolytic capacitors. Capacitor failure can interrupt the industrial assembly line, causing a great loss. The prediction of RUL (Remaining Useful Life) of industrial capacitors is hence very important. In this paper, based on the analysis of the EIS of the aluminum electrolytic capacitor, a quantitative model of the state of the capacitor is established. Based on the quantitative data, the degradation prediction model of ARMA capacitor degradation is established. Finally, the equivalent series resistance EIS spectrum data set was verified by NASA. The results show that the short term ARMA capacitor degradation model is accurate in the prediction of the state of aluminum electrolytic capacitors.

Abstract:The application of genetic BP neural networks used in early warning of the risk of bulk commodity electronic trading marketplace is studied. According to the risk characteristics of bulk commodity electronic trading marketplace, an early warning model (GA-BPNNM) based on genetic algorithm and BP neural networks is being built by the Matlab toolbox functions. The risk assessment index system is established based on the marketing research and the optimal training functions and number of nodes of the hidden layers are determined by the experiment. With the combinatorial optimization of genetic algorithm and BP neural networks, the difficulty of traditional risk analysis because of the ambiguity of definition and variety of causes could be overcome and the problems of premature phenomenon of genetic algorithm falling into local minima and slow convergence speed of BP neural network could be solved. The results of simulation test show that the GA-BPNNM prediction is better than BP neural networks and is feasible and effective in the early risk warning of bulk commodity electronic trading marketplace.

Abstract:The cabin system is an important part of the civil aircraft avionics system, mainly consisting of the cabin core system, the airborne entertainment system and the external communication system. This paper designs an integrated network architecture to cover all cabin typical business senarios through the analysis of the typical cabin business services, the principle of cabin network design and the common devices in cabin application based on the existing ethernet technology. Then it also states detailed function requirements about important communicated devices in cabin networks, and uses OPNET software to get the simulation result to demonstrate the feasibility and superiority of the integrated network architecture designed in this paper.

Abstract:The establishment of natural disaster prediction model to predict and analyze the occurrence of natural disasters is conducive to enhance the technical level of disaster prevention and mitigation. We present a design and implementation of natural disaster forecasting system based on association rules and the Web text mining technology. The system uses a mature open source crawler framework to capture the unstructured natural disaster information from the authoritative disaster information release platforms. By using the Chinese word segmentation technique the data are cleaned up and organized into a structured natural disaster database, and mining association rules of natural disaster events are worked out from improved association rule algorithm. And then by monitoring the front-end information of association rules in real time, the prediction of natural disasters can be achieved. Experimental results show that the system can effectively mine the association rules of natural disaster information with high confidence.

Abstract:The Intelligent transportation system is a real-time, accurate and efficient integrated transportation management system, with the LPR(License Plate Recognition) as one of its key technologies. In order to realize the real-time detection of license plate in the embedded systems, the license plate detection, location and recognition technology based on TMS320DM642 are studied. This paper proposes a kind of license plate location algorithm by combining texture detection with the Adaboost classifier. The system design combining with DM642 is based on EMCV and Opencv image processing library to come true coding porting. The system avoids the non-directional under the condition of only texture detection and the non-integrity under the condition of only Adaboost Classification, it also improves the accuracy of the positioning. In addition, the license plate image which has been located can be sent to the PC server by the TCP protocol. Then the license plate location and monitoring of remote vehicles can be realized.

Abstract:According to the E-commerce demands of small and medium sized companies, this paper puts forward a scheme for the border construction of third party E-commerce platform. It introduces the tag warehouse based on the ASP.NET(C#) and the design and realization of the tag analyzing engine, demonstrating the feasibility of the scheme through the development of a website building system. Besides the function of website building, we can extend the platform of third party E-commerce by adding new functions using tags.

Abstract:With the urbanization and the improvement of people's living standards, the number of private cars in recent years has been increasing. It is difficult to find cars in parking lots, and the service is poor, which poses more demands on the automation of the intelligent parking lots and the service quality. Mainly serving for management and testing functions, traditional intelligent parking lots are inadequate in the vehicle guidance and customer service. To this end, this article builds an intelligent parking lot in embedded platform, which offers machine vision-based space detection, human intelligent RFID smart guide, and a complete management system and convenient WeChat public services.

Abstract:The traditional traffic light systems are poor in flexibility and intelligencefor their fixed timing modes. In view of the above problems, a machine-vision-based traffic congestion evaluation system is presented to evaluate the current situation of traffic jams in this paper based on the collected video intelligent analysis and processing. Vehicle counting is firstly realized by HOG-feature analysis, AdaBoost method and RFID technology. Traffic states are evaluated in the Spark platform. The result of the experiments shows that our system can realize adjusted transformation time of traffic lights according to actual situation of the current traffic environment, then achieve the purpose of relieving traffic pressure dynamically.

Abstract:In view of the complexity in terrain of Sichuan Province, the large number of meteorological stations as well as the fact that the meteorological information network system was seriously damaged in various natural disasters, this study introduces the application of IRF method to upgrade transformation of virtual technology to the new provincial meteorological information network system. The MAD BFD detection is used to improve the reliability and stability of the network system through the integration of resources, ultimately ensuring the meteorological business efficiency. In the upgrading of equipment, the whole network link bandwidth and QoS also have a new design, achieving the integration of meteorological information network systems at three levels:provincial, city, and state level. Results show that the system is stable and reliable, and it embodies more advantages of virtualization framework. In short, it meets the needs of meteorological service to the network over the next few years.

Abstract:In-situ sensor is an important data source of intelligent urban construction, which plays a decisive role in urban resource coordination, disaster early warning, dynamic monitoring analysis and other fields. The present sensor observation access method does not consider the flow characteristics of sensor data with no uniform access model resulting in a failure of unified filtering of time and space under the observation and poor reusability of the sensor access components. In this paper, an in-situ sensor observation access method based on storage and computation separation is proposed. Upon the station-based observation access uniform model, the in-situ sensor access process is divided into three parts:data acquisition, observation filtering and observation storage. The experimental results show that the method can effectively access the heterogeneous in-situ sensor station based on the sensor observation access uniform model and realize the attribute filtering in the specific time and space scenes of the multiple in-situ sensor observation results.

Abstract:With the development of intelligent transportation technology, the increasing traffic data volume has reached TB or even PB level. The intelligent transportation field has begun to use big data technology to analyze deeply the massive traffic data, to build a comprehensive intelligent traffic information Service platform. In this paper, an intelligent information service platform based on traffic big data is proposed. The paper mainly analyzes this platform from the overall architecture, application architecture and data center design of the system. Through the test, the platform can meet the early needs of the users. The platform-based hierarchy and sub-module design can be a good response to the user needs change later on.

Abstract:Commonly, the distributed storage cluster support ISCSI protocol for compatibility and scalability. But, the high availability of ISCSI services is mainly achieved through a master slave remote system which wastes resources and easily makes the server overload. This paper uses raft consistency algorithms to implement a high availability cluster of ISCSI service based on the advantages of Ceph. In order to implement the high availability, the cluster supports load balancing using sensible selection policy and services migration after detecting the failover of the server. The experiments show that the proposed scheme is effective, and can achieve services migration, and ensure the load balancing.

Abstract:The identification of geological specimens is a basic skill that must be possessed by students of geoscience. However, due to the great variety, different attributes and scarcity of geological specimens, it is very difficult for students to study in full. In this paper, from the perspective of software engineering, the characteristics of geological specimens are presented as the starting point to determine the basic functional requirements of the platform. The paper designs the system architecture and function modules, discusses the main technologies and characteristics of the system, and finally carries out the system. Through the construction of the virtual simulation platform of geological specimens, the advanced software and hardware technology can be used to realize the retrieval of geological specimens, attribute browsing, three-dimensional display and other functions, to provide students with a new learning method to improve their identification skills. Practical application shows that the system can effectively enrich the students' understanding of geological specimens and improve the students' ability of discrimination.

Abstract:A Remote Control System for the new type of absorption refrigeration unit is designed which gains access to the cloud platform. The system is designed to solve the problem of distributed sensors, multi-protocol of heterogeneous networks and cloud platform access for local devices, which achieves the data sharing and remote monitoring between cloud platform and control filed. Through field bus technology, the intelligent node is designed and the CAN sensor network is constructed in the control field. Through the embedded technology, an embedded cloud gateway is designed which uses the data cache frame as the buffer for the multi-protocol conversion. The wireless module is used to establish the access to the cloud platform and use the EDP protocol to connect the control field with the cloud platform. In the cloud platform, the cloud monitoring platform of the refrigeration unit is designed. Through the registration of device and monitoring interface design, the access equipment is mapped in the cloud platform, and the data from the control field is automatic updating in the cloud platform. The system uses the method of cloud platform access for local devices, which completes the experiment data sharing and remote monitoring for new absorption refrigeration.

Abstract:In view of the complexity of traditional industry process monitoring system(SCADA) architecture, the inconsistency of the development technology and communication protocol between front and backend of application which could not process high concurrent requests, the innovated application which combines the SCADA and microservice framework Seneca based on Node.js server platform is developed which uses unified Node.js programming model and standardized REST API protocol. The application has low cost, high performance, easy maintenance and security of SCADA enterprise.

Abstract:To gather the operation state of automatic sapphire crystal growth in real time, this paper designs a monitoring system based on IOT Android development platform. The Android mobile device as a client receives the data from the PC server and achieves the function of data visualization for real-time parameter monitoring, including heating power, voltage and current, cooling water temperature, rotational speed, crystal weight and growth speed and so on. Firstly, the monitoring needs of Sapphire Crystals Growth is introduced in the paper, and then the composition of the system and the design of each module's functions are described in detail. Finally, using the development method of SQLite, Socket communication and others, the client for Sapphire Crystals Growth based on IOT Android platform are designed and implemented.

Abstract:The Hybrid App combines the advantages of Native development and Web development, which takes more and more proportions in the mobile application development and desktop application development. This paper realizes bidirectional communication mechanism between WebView and Native, set up development framework for Hybrid App, and optimizes the performance of Hybrid App by means of off-line storage for Web data and delta update based on byte stream for Web files. Finally, the development framework and optimization mechanism are actually tested and the collected data are analyzed, and the experimental results reveal that development framework and optimization mechanism have good feasibility and practicability.

Abstract:Face recognition is active in the field of computer vision and pattern recognition and has extremely wide-spread application prospect. However, the problem that both training images and testing images are corrupted is not well solved in face recognition task. To address such a problem, this paper proposes a novel Discriminative Low-Rank Dictionary Learning for Low-Rank Sparse Representation algorithm (DLRD_LRSR) aiming to learn a pure dictionary. We suggest each sub dictionary and sparse representation be low-rank for reducing the effect of noise in training samples and introduce a novel discriminative reconstruction error term to make the coefficient more discriminating. We demonstrate the effectiveness of our approach on three public face datasets. Our method is more effective and robust than the previous competitive dictionary learning method.

Abstract:The optimal path planning algorithm and implementation of 3D map based on A * algorithm in mountainous environment are studied in this paper. It considers the condition of poor coverage of 3D mountain-free network information coverage, improves the A * algorithm and uses 3D terrain DEM data to calculate a relatively smooth and short three-dimensional path. The improved algorithm can improve the shortest path evaluation criterion in three-dimensional space from the original spatial distance accumulation to the shortest distance, and then calculates whether the distance is the shortest. At the same time, the global gradient information of the surroundings of the search point is considered as the heuristic information to reduce the probability that the path the algorithm looks for is steep. Experimental results show that the proposed algorithm can improve the smoothness and shortest path of the three-dimensional optimal path, which accords with the walking habits of human beings.

Abstract:Social awareness network (SAN) is becoming a new application normal form. To explore and evaluate the availability of the awareness, based on the traits of social awareness process in e-government IoT application, this paper extracts the hierarchical awareness structure by typical SAN. It focuses on analyzing the influence of sociality participation on awareness information. By synthesizing the functions of actors in the hierarchical structure of social awareness IoT and describing the node of SAN, it presents a hierarchical structure and availability evaluation modules for SAN. And the hierarchical social perception process is simulated and the idea of the model is verified graphically by computer software means. The results show that the model can express the comprehensive attributes of physical structure and social participation, and there is dynamic connection between nodes states and application requirements in SAN.

Abstract:To improve the diversity and convergence of Pareto front generated by multi objective particle swarm optimization, a detection mechanism for evolutionary state of multi objective particle swarm optimization is presented in this paper. The evolutionary state of the algorithm is assumed by detecting the updating situation of the external Pareto set to get the feedback information to adjust the evolutionary strategy of the algorithm dynamically. It enables the algorithm to take the diversity and convergence of the approximate Pareto front into account in the process of the evolution. Finally, the proposed algorithm shows a good performance compared with other four kinds of equivalence algorithms in the ZDT series test function.

Abstract:For architecture of BWDSP, this paper analyzes the implementation of the optimizations, based on vectorization and software pipelining of parallel optimization technique, including special memory access instruction, zero-overhead looping instruction of improving efficiency in the loop, Instruction-level Parallelism(ILP), combined with the specific function of loop characteristics, expansion for the string and memory function of instruction level parallel mining. The experimental results show that the optimization rates of most functions of the theory have a running time of 1.5 times on hardware platform, which is of great importance to enhance the platform performance of BWDSP.

Abstract:In order to more scientifically evaluate science and technology projects to check their acceptance levels, the improved acceptance processes are proposed in this paper. Aiming at the Industrial projects in Guangdong Province, the Financial and Technical evaluation index system of the project acceptance is established by using the fuzzy comprehensive evaluation method. The proposed evaluation system is testified with given real cases and the results yield a reasonable effect. Compared with the traditional expert meeting approach, the fuzzy comprehensive evaluation method is more appropriate to be applied for the science and technology project acceptance.

Abstract:Text classification is the foundation of information retrieval and text mining. Naive Bayes can be applied to text classification as it is simple and efficient classification. But the two assumption about Naive Bayes algorithm that its attribute independence is equal to its attribute importance are not always consistent with the reality, which also affects the classification results. It is a difficult problem to disapprove the assumptions and improve the classification effect. According to the characteristics of text classification, based on text mutual information theory, a Term Weighted Naive Bayes text classification method based on mutual information is proposed, which uses the mutual information method to weight the feature in different class. The effect of two assumptions on classification is partially eliminated. The effectiveness of the proposed method is verified by the simulation experiment on the UCI KDD data set.

Abstract:In view of the complex identification and inaccurate disturbance location of distribution network transient power quality, a disturbance self recognition and localization method based on S-transform matrixes and classification rule tree is proposed. The method analyzes signals by the S-transform and extracted four characteristic quantities from them, then the classification of disturbance signals is performed by use of a rule-based decision tree; and then the disturbances' amplitude change and start-stop time are detected using the amplitude envelope algorithm and amplitude square sum algorithm of S-transform matrixes. The simulation results show that the method is fast and accurate to identify and locate the disturbance signal with low complexity.

Abstract:In recent years, wireless sensors are widely used in various fields, and the research about energy-efficiency strategies is emerging in an endless stream. As a key technology of information sharing and distribution, the energy-efficiency research about caching technologies has been one of research hot spots. Based on the cache replacement algorithm and the basic thought that adopts the replacement cost study, this research analyses the existing cache replacement algorithm firstly, then integrates the two cache replacement algorithms based on low energy consumption or high cache hit and refines one cache replacement algorithm that combines both advantages, which follows the on-demand cache placement policy based on dichotomy and the cache replacement strategy in wireless sensor network. At last, the simulation proves that, this algorithm has varied degrees of advancement in the following three aspects:the average delay time, energy consumption and cache hit.

Abstract:In view of the common hexahedral voxel grid 3D geological model, we introduce a 3D geological model partitioning algorithm. In the process of cutting, the cut surface will intersect with the edge of the hexahedral element. Firstly, the geological model and the cut plane are projected into the same 2D plane at the same time, the process of portioning between geological model and cut plane in the 3D is converted to an operation that looks for the intersection point between the line and the quadrilateral grid. In order to reduce the number of judgement intersections, we would find out the possible intersection area by the Line slope direction of cutting plane, then judge whether there is an intersection carefully. Next, we find other points of intersection that could not be got by projection, and connect the node coordinates according to certain rules form the quadrilateral grid and triangulation. Finally, we display the TIN. Experimental results prove that this method is feasible.

Abstract:Traditional data integration solutions in the presence of the structure are not precise. During the integration period, the integrated result due to various reasons has many abnormal outliers, which cannot be detected and avoided with effective measures. This paper proposes an improved three stage outlier detection algorithm based on angle, which is mainly to detect the results after data integration, and effectively solve the problem of a large number of suspected outliers. This improved algorithm reduces the possibility of outliers in the traditional algorithm, taking into account the factors of dynamic changes in the data, verifying the abnormal real situation of suspected outliers for two times. This paper is backgrounded on the project of production accident emergency rescue system.

Abstract:The trading amount of P2P network lending is rising, and the research of P2P trading data receives much attention. The factor analysis of the success rate of network loan is one of the important research topics. The previous papers on this issue mainly adopt multi-linear regression method, ignoring the problem of multi-collinearity between the variables and the finding of "optimal" regression model. This paper uses the Lasso regression method to establish the regression model with optimal subset of variables, which can analyze the factors that affect the success rate of network borrowing, avoiding the multi-collinearity of the model interference and improving the prediction accuracy of the model. This paper empirically analyzes the borrowing and lending data from the Lending Club platform, and the result shows that our method is significantly superior to the compared approach in the aspects of fitting precision of the model and avoiding the multi-collinearity.

Abstract:In order to identify the panic crowd behavior with a more accurate and effective method, a new scheme is proposed which can utilize the intersection density of motion vector in the video to judge the abnormal panic crowd behavior. This algorithm is based on LK optical flow to extract information of motion vector from moving people, and to obtain the intersection between two motion vectors, then uses divided image blocks to get the intersection density which is the key to identify abnormal crowd. Experiments on several datasets show that this algorithm can identify the panic crowd behavior with high accuracy.

Abstract:The access control policy defines the rights and privileges for different users on database objects. In order to maintain the security of these database systems, the database security should be controlled to protect the contents of the access database, as well as to preserve the integrity and consistency of the data. In order to achieve consistent database access control strategy, in this paper, we propose a temporal reflection database access control (TRDBAC), a new access control strategy, aiming to eliminate the limitations of RDBAC. To express the time limit our new strategy has demonstrated the results of a case study on a student information system, where strategies are written in the reflective database access control (RDBAC) for extended time based. Finally, we analyze the behavior of the new model.

Abstract:The accurate prediction on airline passenger flow plays an important role in sales policy for aviation enterprises. Based on the data of Sanya-Beijing route of a particular airline in 6 years, this paper uses the regression analysis, gray forecast method to analyze the passenger flow in 2016.The result shows the Grey forecasting method of airline passenger flow forecasting is more accurate than others, which sets a significantly guiding model for airlines sales policies.

Abstract:Panoramic image mosaic technology is a 360-degree circular image that combines the images of some overlapping areas to describe a particular scene. In this paper, a novel image sorting algorithm based on SIFT (Scale Invariant Feature Transform) feature matching is proposed to achieve the orderly arrangement of images. Aiming at the problem that the image mosaic has many mismatch points and takes a long time,the FAST algorithm is used to extract feature points. And then, an auto-correcting operation is adopted for the brightness difference between the adjacent ordered images to reduce the brightness difference, and the modified Ransac algorithm is used to eliminate the mismatching points. Finally, the Weighted Equalization Algorithm is used to realize the Fast fusion of the image. The experimental results show that the algorithm is stable and efficient.

Abstract:In order to solve the problem of massive orders scheduling in the cloud logistics environment, this paper proposes a scheduling algorithm based on orders clustering. Firstly, aiming at the single center multi vehicle scheduling problem, an optimal scheduling algorithm based on the single parent genetic algorithm is proposed. On this foundation, considering the location of the city distribution centers, the vehicles and the distribution points, the type and the demand of goods, an order clustering model based on distribution center is built by using the ant colony algorithm.

Abstract:In the development of Android application, the access to the storage is extremely frequent, but different versions of Android are in a muddle in supporting storage, with some versions of Android even without public API support for extended storage access. After conducting a study on Android's built-in and external storage devices, we propose to divide storages into three types:internal storage, external storage and extended storage. What's more, we have analyzed the characteristics and access modes of various types of storage, especially the extended storage access mode. We use JAVA reflection mechanism to obtain extended store directory of Android platform. We solve the compatibility problem that different versions of the android access the storage device. Through the analysis tool we have analyzed the efficiency of reflection mechanism in this application, and has tested it on multi-model equipment.

Abstract:To improve the accuracy and eliminate the error of aircraft assembly, the fixture layout for aircraft frame component with complicated process feature is optimized. In terms of process constraints, a generalized mathematical model of constraints is constructed and a theoretical repairing method is proposed. Additionally, an improved Genetic Algorithm is proposed based on the repairing method. In the example of fixture layout optimization of reconfigurable flexible fixture for frame component, the improved algorithm performed stably and the flexible position error, as a consequence, had reduced dramatically, at around 93.08%. The theoretical analysis and simulation result show that the improved Genetic Algorithm adapts to various kinds of constraint optimization and is feasible for its fast convergence rate and stability.

Abstract:In order to reflect the automatic analysis and understanding of the auditory scene content by the auditory attention neural information processing computational mechanism, this paper presents a top-down extraction model of the auditory saliency attention, based on the perceptual characteristics of human ear to frequency transformation, and combined with the speaker identification using the depth belief network and the auditory significant model. The simulation results show that the proposed model is feasible, and it can effectively highlight the significant degree of the target speaker in the speaker identification technology using the depth belief network.

Abstract:The application of network video has become a new research hotspot with the development of network technology. After analyzing the traditional technical architecture of live video broadcast and the mechanism of storage and dispatch, a storage and distribution mechanism of scalable video coding is proposed based on hybrid cloud in this paper in view of the problem of both the heterogeneity of user request and resource allocation. Finally, conclusions are confirmed through the simulation data that the mechanism can significantly reduce the network delay in the video streaming system.

Abstract:In order to further describe the virus propagation of real-life complex networks, this paper improves the traditional construction methods of weighted scale-free networks model which considers two key factors:flow bandwidth and individual resistance. Using mean-field theory to simulate the process of the virus transmission, this article analyses the experimental data and verifies the validity of the new model. Most real-life complex networks are known to us with only the local topology information and the traditional virus immunization strategies are based on global network topology information. In condition of knowing local topology information, this paper proposes the immunization strategy of virus spreading based on the local optimum in weighted scale-free networks. Compared with the random immunization strategy and target immunization strategy about the efficiency of virus spreading in weighted scale-free networks, the local optimum immunization strategy is verified to be valid through the dynamic simulation of virus propagation.

Abstract:In view of the traditional positioning defects based on received signal strength, a new K-NNC location algorithm is proposed for IOT, based on K- neighbor node coverage (K-NNC). K-NNC is divided into two stages, select neighbor nodes and positioning stage. In order to reduce the influence of long distance nodes on the positioning, by adjusting the transmit power to select the nearest K neighbor node. In positioning stage, the node calculates the weight by the received signal strength of the K beacon node. The coordinates of the nodes are calculated by the weighted sum. Using the self-correcting method the position coordinates are compensated. The K-NNC positioning model can effectively avoid the influence of environmental factors on the positioning, and the positioning algorithm is simple. Experiment shows the K-NNC positioning model positioning is highly accurate.

Abstract:This paper introduces the basic idea of distributed source coding and the construction method of classical distributed source coding. It discusses the joint channel distributed source encoding method with the new polar code. It realizes the joint polar code-distributed lossless source encoding system and finally applies the method to the image transmission and the simulation experiment proves its feasibility.

Abstract:As a database based on distributed file storage, with powerful single table query language, and extensible high performance data storage, MongoDB is very popular among users. But is does not fully support the transaction, leaving the uses of the MongoDB passive. In order to improve the mongo compatibility of transaction management, a solution of supportting MongoDB transaction management and perfecting its function is proposed. The communication between daemon processes and MQ are utilized to make daemon processes clean up the dirty data after a transaction commits or rolls back, ensuring the availability and security of MongoDB in terms of transaction management.

Abstract:With the continuous development of cloud computing technology, more and more enterprises begin to use OpenStack to build a private cloud or public cloud platform. Cloud platform is gradually replacing the traditional server, to undertake the enterprises and user IT business. In order to guarantee the service quality of the cloud platform, this article designs the interactive operation page of monitoring and alarming function for the virtual machine of cloud platform, based on the OpenStack alarm function interface--Ceilometer Alarm API. Using this function, users can monitor the running state of the virtual machine, ensuring the reliable operation of the cloud platform.