Abstract:Consensus mechanism is the core of the cryptocurrency system which is based on the block chain technology. This paper analyzes and compares the three typical consensus mechanisms to provide references and suggestions for the design of consensus mechanism for block chain developers. The basic idea, operation process and advantages and disadvantages of the three mainstream consensus mechanisms, PoW, PoS and DPoS, are analyzed. Then the characteristics of each consensus mechanism are summarized from the aspects of fairness, running cost and sustainability. And then we analyze and compare them from the credit to the degree of decentralization, authorization and other aspects, consider the consensus needs under the different application scenarios. From the application scenario, two or more consensus mechanisms are used in combination to find a suitable balance point between the complete de-centralization and the centralization, which is more in line with the application requirements of the future consensus mechanism.

Abstract:Geosteering while drilling is a high-quality application of complex reservoirs development, and 3D visualization of wellbore is one of the essential and indispensable technologies for it. The methods of modeling wellbore which have equable or unequable radius are researched, and the visualization of geological properties is achieved by using imaging principle, based on the well inclination data and well logging data getting from LWD. Then the 3D wellbore model and the imaging information would be combined together, which means showing the drilling stratum attributes in the wall of the wellbore. A system model is implemented based on OpenInventor, of which running tests show that attributes of drilling stratum from wellbore can be observed vividly and accurately, and it laies a solid foundation for the implement of geosteering while drilling.

Abstract:Some scholars have already proposed a lot of dominance relation and corresponding rough models under incomplete information system in order to deal with the problem of preference decision which has incomplete information. It is uncertain that no matter use which method to contrast two objects as long as there is missing value. According to this defect, this article analyzes the factors that influence the gray scale, defines the concept of the gray and the difference coefficient in the dominance relation, and gives the calculation method and establishes an index to measure the degrees of the contrast between two objects. Therefore, the dominance relation based on grey system and its rough approximation model is presented. Through the comparison analysis, the precision and quality of the rough set model based on the grey dominance relation are improved. The given example proves the practicality and effectiveness of the grey dominance relation and its rough approximation model.

Abstract:In the era of big data, the research on data-intensive computing is becoming more and more popular both at home and abroad. As a typical branch of big data, remote sensing data is characterized both by the variety of the data sources and the huge data quantity. One of the biggest challenges facing the remote sensing application is how to find out a data-intensive computing method which aims at the automation of the business processions of remote sensing images. In this paper, a new data-intensive computing method for the procession of remote sensing images is proposed. After a deeply study focusing on the automation of the business processions of remote sensing data, a new systematic architecture using workflow is introduced which can coordinate the work among different algorithm models. In addition, in the pre-processing of the remote sensing images, a new computing architecture with five different types of parallelism and a stage of acceleration is also adopted. The computing method proposed in this paper has been tested in many products in real production environment in order to testify its effectiveness. The results show a significant improvement on the efficiency of the pre-processing of remote sensing data in the condition of ensuring the processing precision.

Abstract:The fault characteristics of complex equipment are characterized by uncertainty, nonlinearity and so on. For the uncertain fault prediction, we design a method of fault prediction，which combines intuitionistic fuzzy sets with grey model to predict fault. The new method uses the membership function to describe the normal system with the normal intuitionistic fuzzy sets and the abnormal system with the abnormal intuitionistic fuzzy sets, uses grey model to calculate predictive value, and uses membership function to calculate the membership degree. Then the fault prediction is implemented by calculating the closeness degree of predicted value of the normal membership degree with normal and abnormal intuitionistic fuzzy subset. This method predicts the fault of the three-tank-system when T2 tank starts to increase or decrease and the crack of the UH-60 planet gear plate when it starts to increase. The feasibility of the proposed method is verified by experiments, which can predict the failure of the system in time.

Abstract:In view of the problems of lag, one-sided and homogeneous financial information service in big data era, this paper designs and implements a financial information service platform based on big data analysis and complex event processing. The multi-source data acquisition, extraction and cleaning are implemented by multi-channel data acquisition and shallow semantic processing technology on the platform. And the data is analyzed by the financial network sentiment analysis technology. The platform provides timely, accurate, personalized financial information services for securities investors, investment adviser and institutions and achieves good application results.

Abstract:Business systems become larger and more complex with the development of information. System development and maintenance are facing enormous challenges. To solve this problem, this paper proposes an application development platform based on micro-services architecture, focusing on the micro-service architecture design and business system practice. This platform implements a standard development framework to generate micro-services engineering, by introducing micro-services building technology and distributed service registry technology. These technologies help to solve problems such as the long development cycle, difficulty to quickly respond to the needs of users and provide a strong support for the system development.

Abstract:For solving the problem of lack of large medical data computing ability in some hospitals presently, a medical mega data analysis system based on Hadoop is designed. The system can provide two functions of auxiliary diagnosis and medical data statistics, combing with the technology of multi-node distributed computing. So, the preliminary diagnosis results can be concluded immediately according to patient's medical data. And at the same time, the proposed system also has more efficient analysis capability than the traditional hospital information system.

Abstract:According to the actual needs of the pilot, directing and adjusting subsystem, battlefield environment subsystem, missile trajectory calculation subsystem, CGF subsystem, command subsystem and audio subsystem are developed. The above-mentioned subsystems and networking modified flight simulators are integrated based on HLA network. Flight simulator networking training system is built. Multiple flight simulators joint training function is realized in the local area.

Abstract:With the development of surveying and mapping technology, it has become a tendency of modern surveying and mapping technology to use airborne 3D laser scanner to obtain point cloud data, and extract the model information from the point cloud data. Relevant applications of point cloud data processing are also increased quickly, but the point cloud data processing softwares are uneven, and the demand and functions are different as well. In view of the above problems, using PCL to develop the 3D laser scanner point cloud data processing software based on the QT programming platform, the dissertation focuses on processing point cloud data in a software system. The system is composed of point cloud data reading and writing module, three-dimensional display module, point cloud filtering module, mesh reconstruction module, point picking, point cloud segmentation and NARF key points extraction functions. Each module uses the object-oriented thought, in which the function is easy to expand to complete further surveying and mapping work. Practice shows that the system has good engineering practical value and can quickly complete the data processing of airborne 3D laser scanner.

Abstract:Based on the project of “design and implementation of internet of things and GIS software platform”, we design a museum collection intelligent management system based RFID and GIS, in view of business process for museum collections management. Through the management of museum indoor map and recorded location of cultural relics in the registration and inspection of them, the system achieves the goal of realizing the online map visualization of cultural relics. And the system also can use RFID technology to realize the real-time location of inspectors and assess the inspection work of the inspectors. Combined with these two technologies, the system implements functions of auto-collect and real-time transmission of collection information and achieves the goal of unified and efficient management of the museum collections. Compared to the conventional way of collection management, this system improves the efficiency and convenience of collection information collection, and realizes the real-time dynamic intelligent management of the collection.

Abstract:In order to solve the problem of interference and inconvenience due to the use of wired signal transmission between the driving cab and the power supply car of the electrical excavator, the wireless signal transmission solution is proposed. With STM32 microcontroller as the core, use Modbus protocol to collect data of power supply car, and obtain the electric state and data of the electric excavator. ZigBee communication protocol is applied to transmit the data to the STM32 micro control panel in the cab for display, at the same time to receive the speed and other instructions of the cab to command the inverter of power car. Experimental results show that the working states acquisition and the wireless bidirectional data transmission is stable and reliable, and the various functions are realized successfully. It can be prospected that such a wireless bidirectional data transmission solution will be used in a wide range of applications.

Abstract:In order to overcome the disorder of the geographical distribution in the construction of power distribution system and islands of information in information interconnection, and provide users with more convenient service, an architecture and application of operation and maintenance in intelligent power distribution system based on the “Internet+” technology is discussed in this paper. The transformation and upgrading of traditional industry of power distribution system on the basis of “Internet+” technology provide great support for optimization of operation and maintenance in power distribution system, fine analysis for operation of power distribution system, and improvement of efficiency in operation and maintenance. Therefore it can improve the reliability and economy of power distribution system and achieve the optimal commercial and social value.

Abstract:Compared with traditional monolithic architecture, microservice architecture has many advantages, such as flexible technology selection, independent scalability, high availability and so on, and is more suitable for the current needs of the Internet age. But microservice architecture also introduces new problems, such as cross-process communication, service registration, service discovery, and distributed session management. On the basis of analysis and comparison between the traditional framework and microservice framework, this paper shows one implementation method of microservice framework. First, we design a scheme of microservices architecture framework and the functional framework, and then give the solutions of some key issues that microservice architecture introduces. With this scheme, developers only need to focus on the development of business functions, service registration, discovery, monitoring and session management provided by the framework to simplify the development and improve development effectiveness.

Abstract:With the rapid development of economic, industrial and agricultural production have gradually changed from the technology of traditional manual techniques to the production of large-scale industrial, and the traditional data acquisition technology of agricultural environment has not been adapted to the rapid development of industrial and agricultural production. Hence, the new intelligent remote environmental data collection technology emerges. The system uses the open-source Arduino microcontroller, with its characters such as powerful ability to adapt to the environment, low cost, to make data accurately collected and transformed. The microcontroller gets the real-time data through ports after data acquisition, and processes it by the procedures, after that the data will be transformed through the established networks, which could achieve data storage into a remote database. And the client can get data directly from the database, and administrators can query and analyse data through the client, mining the important data for the model.

Abstract:Due to the amount of 4K video data is large, and the traditional CPU software decoder technology cannot meet the performance requirement. The 4K video playback system based on combination of hard and soft decoding mode is designed, which uses DirectShow and CUDA hardware decoding technology. And the system includes functions of hardware system information acquisition, video source reader, video hard decoding, and video display. Experimental results show that this system can achieve good effect and greatly reduce the CPU occupancy rate when playing 4K video.

Abstract:This paper presents a new scheme for face recognition, namely face recognition using null-space combined with nearest space distance classifier. By constructing the null-spaces and the subspaces of different types of human face images, different types of human face images are distinguished at the maximum degree. This idea considers that a test image has the shortest distance from its own class-specific subspace and has the farthest distance from its own class-specific null-space. The proposed classifier is evaluated on ORL database and AR database. Experiments on these databases demonstrate that the proposed scheme is more effective than some discriminants used by common classifiers, such as nearest distance used by nearest neighbor classifier, nearest space distance used by nearest space classifier and nearest-farthest subspace distance used by nearest-farthest subspace classifier.

Abstract:Aiming at the shortcomings of traditional SDG model diagnostic, such as low resolution, slow speed and low efficiency, this paper proposes a fault reasoning method based on fuzzy hierarchical SDG model. Firstly, build system's SDG model, and then layer. Using fuzzy variable to represent node variables, we express qualitative causal relationship by conditional probability table between nodes. Finally we use Bayesian inference and backtracking search to find out fault source candidates, and sort candidate solutions. By using the proposed method, the fault diagnosis of certain type aircraft engine fuel control system is carried out, and the results show that the method can improve the resolution and efficiency of diagnosis, the diagnosis results are accurate and complete.

Abstract:In dynamic multi-pedestrian environments, while a service robot navigates only relying on its own sensors with the first-person perspective, both the uncertainties of robot localization and the estimation of people's states are increased, which hinder the navigation decision of a service robot. To solve this problem, a local collision avoidance method based on the optimal reciprocal collision avoidance (ORCA) is proposed. In this method, the states of multiple pedestrians are estimated by a variant of particle-PHD filter, i.e. NP-PHDF for multi-target tracking. NP-PHDF is a combination of Kalman particle filter and PHD filter and has their advantages. So it can not only track time-varying number of targets with sudden motion changes such as abrupt acceleration/deceleration or steep turn, but also resist block among pedestrians. Meanwhile, similar as robot localization which uses particle filter, the uncertainties of estimation for pedestrians can be represented by the distribution of particles. To reduce the uncertainties, an encircling-particles method is proposed to refine the true states of robot and pedestrians from the probabilistic particle distribution. The effectiveness of the proposed technique is demonstrated through experiments in real environments.

Abstract:In order to solve the low recognition rate of template matching method in license plate character recognition, especially the problem that the similar characters cannot be identified accurately, this paper proposes a method of license plate character recognition based on the fusion of local HOG and layered LBP feature. Firstly, we use the template matching method for preliminary identification of all the characters of license plate. Then, a small edge feature of the biggest difference in the similar characters of the license plate and the template is extracted by using HOG operator, and then the layered texture feature of the same area block of HOG in the similar characters of the original license plate and the template is extracted by using LBP operator. Next, serial feature vectors are constructed with serial fusion of the edge feature and the layered texture feature. Finally, according to the Chi square distance between the feature vectors, we measure the similarity of the license plate characters and the template characters, and then complete the second recognition. The recognition performances of the 11 algorithms are compared through experiments. The results show that this method is very effective to solve the problem of false recognition of similar characters and the recognition rate is improved significantly at the same time, which is as high as 99.52%.

Abstract:With the current rapid development of mobile Internet, the information overload problem that people face is particularly serious, which makes it a big challenge to do particular users' personalized recommendation in the big data scenario. In order to further improve the timeliness, accuracy of recommendation and ease the problem led by large amount of data, we propose a optimized matrix decomposition recommendation algorithm under the environment of big data in this paper. This algorithm integrates users and the similarity computation of items on the basis of the traditional matrix decomposition algorithm. In the process of training objective function, we enhance the recommendation accuracy by taking in account of users and k nearest neighbors' similarity computation of items. Taking Spark's advantage on memory computing and iterative computing, we design an algorithm using matrix decomposition and nearest neighbor fusion under the Spark framework. Experiments conducted on the classical MovieLens dataset show that our proposed algorithm can deal with data sparseness well, improve recommendation accuracy to some extent, and has a better computational efficiency in the comparison with traditional matrix decomposition recommendation algorithms.

Abstract:For the traditional Gaussian mixture model, it is prone to detect the background as the foreground region and has poor effect in complex background, so this paper puts forward an improved algorithm combined with three frame difference method. First, we use the three frame difference method to improve adaptation of the revealed background region. Second, we use the means of background neighborhoods update to improve the resistance to complex background noise. The experiments prove that compared with the traditional method, the improved algorithm reduces large amount of noise and shortens learning cycle, and improves resistance to the weather and camera shake, optimizing the noise caused by background region revealed.

Abstract:In the field of underwater acoustic communication, communication technology based on OFDM (Orthogonal Frequency Division Multiplexing) is one of the most direct and effective means. But the underwater acoustic communication channel is changeable and complicated. In the process of transmission, it may be affected by the multipath propagation, the limited available bandwidth and the high noise, which cause the original data not been recovered. So it is very important to ensure the reliability of data transmission. On the basis of the original OFDM communication, this paper adds the weaving technology, chirp spread spectrum technology, the window and the chirp synchronization technology. And through the simulation and analysis of MATLAB, the feasibility of the system is verified. At last, the performance of the system and the ability of anti-jamming are illustrated by comparing the error rate curves of adding noise, multipath and Doppler effects.

Abstract:In order to avoid the iterative computations in passive location, based on the nonlinear observation equation of multi station passive location, a closed calculation is presented by converting the nonlinear measurement equations into the pseudo-linear equalities, utilizing Logarithm Likelihood Estimation method. First, a mathematical model for the pseudo-linearization of two dimensional nonlinear angle measurement equations is formulated and then the closed form solution for the target location algorithm is derived. Subsequently, we realize precisely tracking and location of objects based on current statistical model. Their theoretical location performances are proved to be able to attain the corresponding Cramér-Rao bound (CRB) and the simulation experiments are conducted to verify the effectiveness of the theoretical analysis in this paper.

Abstract:Traffic flow detection is an important part in Intelligent Traffic Control System. A traffic flow detection algorithm based on gray threshold is presented in this paper. When a traffic accident occurs on the neighboring lanes of the same cross section in a three lane road, the traffic flow on the other lane (inside lane or outside lane) where no traffic accident occurred is detected by using this algorithm. And the difference between the traffic flow in inside lane and in outside lane is tested by t test. The results show that the accuracy of traffic flow is more than 95% when using this algorithm, which indicates that this algorithm is feasible and effective. When a traffic accident occurs on the neighboring lanes, the difference between the traffic flow in inside lane and in outside lane is significant.

Abstract:The customer oriented catalog segmentation problem assumes that one customer is interested in at least a certain number of items in the catalog, and then calculates the number of customers that are covered by the catalog. Hence, the result of catalog segmentation is assessed according to it. In order to ensure that the catalog covers customers as many as possible, the existing segmentation algorithm ignores the effect of the results of the catalog segmentation. Aiming at this problem, this paper constructs a new data storage structure CFP-Tree for storing customer transaction data, and presents a new algorithm Effective-Cover to solve the problem of catalog segmentation. The algorithm uses tree depth traversal method to select catalog products. The experimental results show that the algorithm can obtain better catalog segmentation results.

Abstract:Data repairing based on editing rules and master data can automatically and exactly fix inconsistent data, but editing rules mainly relies on the definition by professional staff at present. To achieve data cleaning automatically in the whole process, the techniques for discovering data rules become a hot research topic in recent years. The algorithms for mining CFDs mainly involve CFDMiner, CTANE, FastCFD. Based on the above techniques, we provide a mining algorithm for editing rule, which is based on sample inputs and master data under the extension definition of CFD and the definition of edit rules. The main ideas is as below: Mining CFD from sample inputs firstly; then according to the domain similarity between input samples and master data, we can get the corresponding properties of input samples from the master data, forming editing rules with pattern group. The algorithm can effectively discover edit rules. And the mined edit rules can effectively repair the data in accordance with the semantic of the rules.

Abstract:According to the problems of extracting more false corners and large computation problems in harris corner detection, this paper proposes an improved algorithm based on harris corner detection. In order to reduce the number of false corners and improve the algorithm efficiency, a pre-selection strategy is embedded to pick out potential corners before the normal routine. When calculate the horizontal and vertical gradients, the pixels with smaller horizontal and vertical gradients are pre-processed. In order to improve the auto-adaptive of algorithm, an auto-adaptive threshold is adopted, finally using USAN to make further selection. The result shows that the improved algorithm not only can improve the precision and efficiency of corner detection, but also is robust to noise to some extent.

Abstract:For the images captured in the bad weather like fog or haze, the atmospheric scattering effect not only seriously affects the visual appearance of the image, but also hinders the image feature extraction. Therefore, it needs de-fog technology for image enhancement and restoration, to improve the visual effects and convenience of post-processing. Because that dark colors prior algorithm is time consuming and has poor treatment effect etc., we put forward an improved algorithm of boundary constraints defogging algorithms. At the same time, we introduce information entropy and average gradient to evaluate the algorithm objectively. Comparison of experimental results shows that this method has a high computing speed, and better effects on the deal.

Abstract:ECC-MIMLSVM⁺ is an algorithm of multi-instance and multi-label learning framework. This algorithm proposes a method based on classifier chain, but it does not consider the dependencies between labels. When the number of tags increases, the length of the sub classifier chain also increases, making the error propagation problem prominent. Therefore, this paper presents a kind of improved algorithm, combining ECC-MIMLSVM⁺ algorithm and the label dependencies. ELDCT-MIMLSVM⁺ algorithm is designed, which is based on ensembles of label dependencies classifier chain to avoid the information loss and improve the classification accuracy. The experiment results show that the algorithm has good effect.

Abstract:When the sensor nodes collect data in the forest or water environment, the signal intensity and the signal transmission speed are affected by the obstacles or transmission media, which affects the measurement accuracy of localization algorithm based on the signal information. Taking into account the cost of nodes and the dynamic nature of nodes, DV-Hop positioning algorithm has excellent applicability and practicality. This paper analyses the factors influencing the accuracy of DV-Hop algorithm, proposes a formula for measuring the degree of uniformity of nodes, optimized the algorithm. The simulation results show that the optimized algorithm has higher positioning accuracy.

Abstract:Aiming at the problem that hand gesture recognition system based on ordinary camera is susceptible to the different lighting conditions and complex background, a fingertip detection and hand gesture recognition algorithm based on Kinect depth image is proposed. First, we get depth image by Kinect sensor. Then the hand region is extracted by putting the depth of thresholds on hand point detected by using OpenNI library. Fingertip detection based on convex hull and curvature is proposed. After the number of fingertips and the location of fingertips being detected, it calculates a feature vector including the number of fingers, the angles between fingertips and horizontal of the hand, the angles between two consecutive fingers, and the distance between fingertips and hand center point. Finally, a support vector machine(SVM) is applied to identify nine scheduled number hand gesture. Five experimenters are invited to perform 9 different hand gestures in the complex environment, which each gesture is repeated at thirty times and the angle of hand gesture is different every time. The experiment results show that this algorithm can detect the number and location of fingertips, and the recognition rate of nine hand gesture is 97.1% on average. This proposed method uses simple features and has good robustness, also it is real-time.

Abstract:A very important reason for low quality results of XML keyword searching is that it is difficult to reflect the user's query intent. In this paper, setting keywords weight could resolve this problem to a certain extent. A new method of query results sort based on keywords weight and keywords structure is proposed. This method sets keywords weight and sets nodes weight for every node that contains keywords, according to keywords weight. The importance of the SLCA node is estimated according to the nodes weight in the relation tree and the relationship between keywords. The query results are sorted on the importance of SLCA nodes. The experimental results show that the proposed method has higher accuracy for sorting.

Abstract:The problem of consumers choosing smart phone is discussed in this paper. The influencing factors of purchasing smart phone are analyzed according to the Delphi method, and 11 evaluation indexes are initially established. Then, rough set attribute reduction principle is used to reduce the 11 evaluation indexes and the 6 core evaluation indexes are obtained. Finally, the entropy weight method is used to empower these evaluation indexes, and the comprehensive evaluation model of the smart phone is established. The selection of those 12 smart phones is evaluated. The results show that this method is effective and reasonable.

Abstract:Elevator safety supervision system is the system aiming at implementing all-weather operation monitoring, fault information recording, alarm-and-warn processing, maintenance management, and other functions of the elevators, using several independent sensors which collects the running data of the elevators uninterruptedly all-day, and then uploads these data to the operation monitoring platform of the elevators real-timely through wireless module. Focused on this issue of long response time of traditional elevator safety system, a new type of elevator security system based on the Internet of things is designed and implemented. In the system, a new high speed data transmission communication model is designed on the platform of management. This model interacts down with the underlying gateway by GPRS, and interacts up with the business layer by message queuing service of ActiveMQ based on JMS, greatly shortening the response time.

Abstract:To predict the repast number accurately can reduce the cost of school canteen and improve students' satisfaction. A novel method based on Markov model to predict repast number is proposed according to the consumption situation of campus card system. Firstly, an initial probability is obtained by calculating the eating behavior of breakfast. Secondly, two transfer probability matrices are computed, one is the transfer probability between the behaviors of students having breakfast and having lunch; the other is the transfer probability between the behaviors of students having lunch and having supper. Finally, a Markov model is constructed according to the initial probability and the two probability transfer matrices to forecast the number of diners. The average prediction error of the proposed method is 1.31%, which has a good prediction performance. The experimental results show that the proposed Markov method can capture the students' dining behavior accurately. It may provide valuable information for the school logistics department, contribute to the construction and management of school and meet the needs of students better.

Abstract:Node.js is one of the most popular technologies at present, and it is the JavaScript execution environment running on the server. With event-driven mechanism Node.js JavaScript plus high-performance V8 engine, it's easy to achieve high-performance Web services. When Node.js deals with the problem of asynchronous, it generally uses callback method, but there are Callback Hell problems in the way of callback. Whether reading or debugging is very inconvenient, it is even impossible to get the code stack. Based on Node.js platform, using Promise method, we realize a Web crawler application. We describe in detail how to use the Promise approach to deal with the problem of asynchronous callback during the application process.

Abstract:In recent years, the Chinese proofreading technology has achieved good results at the word-level and the grammar-level, while it's relatively weak at the semantic level. This paper provides a new method of Chinese proofreading powered by the ontology technology. The semantic contents are firstly extracted from the Chinese texts and transformed into some kind of structured ontology, which is combined with the correct background ontology. The logical consistency of the extracted semantic content is determined by description logic reasoning machine, with the detected logical consistency error mapped into some Chinese semantic errors. This method is tested in the domain of political sensitive information. Compared with other methods, it has obvious advantages of the transparency of the semantic proofreading, the integrity of the semantic model and the intelligence of the semantic reasoning.

Abstract:In this era of information explosion, how to handle these vast amounts of data and how to classify the data effectively has attracted much attention, especially in the stage of rapid development of Internet technology free, the field of web classification has become a hot spot. Compared with the traditional classification methods, support vector machine has the characters of high-dimensional, small sample size, strong adaptability, and can be very effective to solve the problem of web page classification. But in the field of classification of imbalanced data, there is a problem of inaccurate classification. Therefore, this paper proposes a new strategy to solve the imbalance data samples, that is, combining the under-sampling strategy with the traditional support vector machines to increase the number of samples set in the minority class and to reduce the concentrated noise data in the majority class, so that imbalanced sample set tends to be balanced. Finally SMO algorithm is used to improve the accuracy of classification.

Abstract:Focus on the problem of the traditional step-size model used in pedestrian dead reckoning algorithm cannot fully reflect individual differences in the research of indoor positioning. We propose a method to establish database of individual feature of step-size based on satellite ranging and then replace the step-size model. Satellite ranging is applied to calculate the step-size in the outdoor, the corresponding relationship between different speed features and step-size is set up. Then we carry out real-time step-size matching indoors for the step, using improved K-nearest-neighbor(KNN) algorithm and calculate people's current position combined with direction information. The actual test results show that the maximum error distance can be controlled within 4%, and the mean absolute error distance can be controlled within 2%. The positional accuracy has a larger enhancement compared to the traditional step-size model.

Abstract:With the rapid development of mobile terminal technology, wireless communication network technology and the universal application of geo-spatial information in all walks of life, the application mode that combines LBS with mobile GIS has become a hot research topic, and it opens up a market with unlimited potential. This paper discusses the basic concept of mobile GIS based on location services and the system architecture of Android development platform and the architecture of mobile GIS based on LBS. On the basis of this, a mobile GIS system based on Android platform is designed. The system has been improved on the basis of traditional mobile GIS, which overcomes the shortcomings of lack of social interaction in traditional mobile GIS, it not only can realize accurate real-time positioning and query trajectory, but also can share real-time location with friends and track the trajectory of many people at the same time. It can be used for real-time monitoring of the old elderly, children and other vulnerable groups, but also for employees, vehicle management scheduling.

Abstract:The displaying of bidirectional text in SVG is implemented by Unicode bidirectional algorithm, but bidirectional algorithm cannot automatically generate correct results to be displayed in line with semantics in many cases, so additional settings are required. By analyzing the basic principle of bidirectional algorithm, this paper discusses several aspects of bidirectional text display prone to occur, which includes text direction determining, display positions of special characters, text reordering across tspan elements in text elements, and position changes after display direction setting. According to specific circumstances of each issue and individual differences in different browsers, figure out ways to set correctly by using specific attributes in SVG.

Abstract:More and more developers are being attracted by blockchain technologies and sustainable development of various open source blockchain projects. Nevertheless, the various popular programming languages and distinctive blockchain projects could perplex the developers inevitably when they commence to develop systems or applications based on blockchain. So, this paper utilizes a tool named Cloc to count the lines of source code in 12 well-known open source blockchain projects. By further reading codes and documents associated, we try to analyze and compare the programming language constitutions of the projects. Moreover, the paper demonstrates their project sizes and the attention degree to them in the form of charts. Finally, some reference information and suggestions about selections are given to the blockchain developers.

Abstract:Meteorological conditions have a significant impact on the safe production of electric power, which is of great significance to carry out the research of the electricity meteorological service. Oriented by the user's demand, combined with features of meteorological data, thiessen polygon corresponding weather station is used in live and nowcasting, and district and county administrative divisions is used in short-term forecasts and early warnings, to divide transmission lines and substations respectively, and then establish nearest neighbor relations. At the same time, meteorological comprehensive influence grade standard is designed to improve the fineness of service. A system of electricity meteorological service is built by GIS and database technology, which includes information about live monitoring, nowcasting, short-term predicting, signal of warning, historical queries, service material and so on. The results of the business application show that the system is stable, and is able to enhance the level of meteorological services, ensure the safety of power system.

Abstract:For a kind of system of aircraft wing-fuselage adjustment-docking which is composed of 3-axis positioners, this paper introduces the process of adjustment-docking, achieves adjustment-docking algorithm by planning trajectory of the wing-fuselage and solving the equation of inverse kinematic. The simulation software of wing-fuselage adjustment-docking is developed by using of object oriented technology and OpenGL library in environment of Visual Studio 2010. The dynamic simulation of the whole models in the software interface is accomplished by combining the kinematic equation of the positioner and the trajectory planning of the wing-fuselage. Results of simulation can be used to display the position and dynamic process of the wing and fuselage. It proves the correctness of adjustment-docking algorithm.

Abstract:Traditional information revelation methods of electric power standard literature are mainly divided into external description and internal feature. But both ways are difficult to conduct a comprehensive description of electric power standard literature's details and adapt to the demands of content index comparison based on knowledge unit. In order to solve the above-mentioned problems, semantic web theory, traditional information management technology and standardization theory are integrated creatively in this paper. An electric power standard literature content revelation method is proposed and a system of electric power standard literature content revelation is designed, which is in application and dissemination in the power industry, and got better effect than traditional retrieval.

Abstract:With the continuous development and updateof mobile intelligent device, mobile application is also facing unprecedented development. At the same time, the mobile application extended to the corporate office. In the information construction of StateGrid corporation, mobile Internet is also an important aspect. The mobile application development processbasing on mobile platform, aiming to the background services for mobile application development, operation and deployment problems, basing on the middleware container plugin development is came up, realized the rapid development and deployment of mobile application service, improved the efficiency of mobile application development and deployment of operation.

Abstract:In recent years, mobile video monitoring is an important research field because of the development of mobile communication network and the popularity of Android smart phone. This paper deeply studies the streaming media transmission technology, video coding-decoding technology and SIP protocol, on this basis, it designes a mobile video monitoring system owning voice function which mainly carries on the research and design of mobile video surveillance client on the basis of the Android platform.

Abstract:Data quality evaluation is very important for military data construction. To improve the science and rationality of the military data quality evaluation, a data quality evaluation index system is constructed according to the feature of military data in the paper, and then an evaluation comprehensive model is constructed with multilevel grey evaluation method to estimate the data of several departments. The evaluation test shows that the results of the proposed method is reasonable and effective, and have great significance to enhance the scientific level of the management of military data quality.

Abstract:In order to solve the disadvantage that it needs to set an experiential value of existing stop criterion of Intrinsic Mode Functionin EMD (Empirical Mode Decomposition) sifting process, the paper proposes a new criterion of Intrinsic Mode Function based on Shannon entropy. There is no need to set an experiential value of a parameter, which avoids the defects of differences in decomposition results caused by different experience value in sifting process. By comparing with other criterion, it demonstrates that the decomposition result are more accurate and have smaller index of orthogonality according to the proposed stop criterion, the IMFs can reflect the characteristic of non-stationary and nonlinear in signal. This stop criterion is applied to the fault diagnosis of rolling bearing in wind turbine. The result showes that this criterion can better retain the fault feature information such as the shock pulse, amplitude and frequency modulation, and diagnose the fault site accurately.