Abstract:Account has been widely used as the user identifier in WEB applications suck as Social Networks (SN), Instant Massager (IM) and E-Commerce. At present, most researchers focus on the social network attack detection which includes spam and fake accounts detection among SN envrionment. Obviously, current works are unable to cover all related fields and put forward unified description to the study objects. In order to solve these problems better, in this paper, firstly, we propose that the account is the only study object, and define malicious accounts controlled by attackers executing abnormal behaviors as manipulated account. Then, we classify the manipulated account according to the degree of control they suffered so as to categorize the detection methods by different kinds of manipulated account. Moreover, a statistical methods to classify the account have been promoted to verify the existence of manipulated account. Finally, we discussed some challenges and show some prospects about this area.

Abstract:In container-based virtualization, the mainstream way to build images is Dockerfile. However, using Dockerfile to build images has the obvious deficiency:Because of complexity of the Dockerfile syntax, the way of editing with text does not provide effective guidance of syntax, and effective detection for common errors, which lead to low efficiency in building images. In addition, using the 3rd party images with no complete explanation, users can not completely understand the usage of images and security is also a challenge for the 3rd party images, this bring the difficulty to reuse images. To solve the above problem, based on analysising syntax of Dockerfile, statisticsing and analysising common errors and deeply studying on storage mechanism of Docker image, we design a tool for building Docker image on Dockerfile, which using technology of visual editing, error detection and reverse engineering. In view of the problems existing in building images, the tool can provide effective syntax guide, and detect the common errors effectively. In addition, in order to verify the usage and safety of the third party images, by reversing images to Dockerfile, users can fully understand usage of the third party images via Dockerfile, and through the way of second build, the tool can solve problem of safety of the third party images partly.

Abstract:Controller synthesis is the automatic process of searching for a winning strategy in an open real-time system on the basis of a given winning goal. This strategy can be expressed as a series of mapping relations of the symbolic states and the symbolic actions. In this paper, we focus on the reachability target which is described by Linear Temporal Logic(LTL) to discover if there is a synthetic strategy. This paper introduces a synthesis algorithm using on-the-fly method to avoid too many states. The algorithm is an extension of Ref.[1], which is mainly used to solve the problem based on branching temporal logic (CTL) for controller synthesis. Through the use of zone, our algorithm is greatly reducing the number of states, and the efficiency is acceptable.

Abstract:High dimensional data and noise have always been the major factors affecting the accuracy of text classification. Feature selection and feature extraction is the main methods of dimensionality reduction and denoising. In this paper, the words probability distribution variance and document distribution variance is used to improve the TF-IDF feature selection method (VAR-TF-IDF). After selecting good features, it tuned the CBOW+HS frame work of word2vec. The superposition of word embedding of the selected words is used as eigenvector which could improve accuracy of text classification. Experiment shows the proposed method is effective.

Abstract:A zero-configuration fine-grained end-to-end tracing approach, namely EasyTrace, is proposed, which is applied to the diagnosis of distributed system with performance degradation problem. Compared with the traditional tracing tools, in which granular control and service component source code are tightly coupled or which have complex configuration and high cost of modification, EasyTrace achieves accurate performance problem locating in the premise of zero-configuration. Extensive experiments that use EasyTrace to trace an open source e-commerce system show that compared with traditional monitoring tools, the disturbance caused by EasyTrace is low.

Abstract:Anonymous authentication has attracted widespread attention of the public as an important means of privacy protection. It is significant to achieve anonymous mechanism based on password which is the most common method of user authentication and remains very widely used in cyberspace. In this scenario, ISO/IEC JTC1/SC27 launched the project of ISO/IEC20009-4 to prepare the standards for PAEA(password-based anonymous entity authentication) mechanisms. There are 3 kinds of protocols for PAEA specified in the ISO/IEC2009-4. This paper designs and specifies a kind of anonymous password entity-authentication component system based on the SKI mechanism, which is one of three kinds of protocols for PAEA in ISO/IEC20009-4. And the system can support the other two protocols at the same time. We analyze the security, anonymity and performance of the system and enhance the security of the processes of system initialization, construction of anonymous group and execution of the protocol. Our work has closed the gap between the theory and the application of the mechanisms. In this paper, we mainly solve the security and performance problems of SKI mechanism when SKI is applied in practice, including "Inconformity of Bulletin Information" which will lead to failure in authentication and the long latency of the "First Query" of a group's public bulletin information etc. And we solve all of them by introducing the solutions of "Dual Bulletin Information Scheme", "Cache System", "Query-Bound-Session Mechanism", etc. At last, we analyzethe performance of the system by do the testing experiences. For now, no domestic and foreign similar systems have been proposed.

Abstract:According to the consecutive berth allocation algorithm of container terminals in the traditional serial environment, the efficiency of the algorithm is significantly reduced and the resource consumption is greatly increased when the number of ships greater than seven. The paper designs the overall system architecture and software architecture of the continuous berth allocation system of container terminals for the first time based on the distributed environment; puts forward the development environment construction of the continuous berth allocation system of container terminals based on the Hadoop platform, its component design and deployment as well as the key techniques of improved continuous berth allocation algorithm in distributed environment based on MapReduce. In the end, the continuous berth allocation system of container terminals in distributed environment is realized. The experimental results show that the system can effectively improve the efficiency of the continuous berth allocation.

Abstract:With the development of Internet technology, traditional WebGIS servers delay or even deny service when dealing with high concurrent access from large groups of users. After analyzing the problem, this paper proposes a framework of WebGIS servers based on cloud platform, which aims at dealing with high concurrent access. The framework uses cloud platform to provide flexible computing and storage resources for WebGIS servers, and alleviates bottleneck of high concurrency in three ways:load balancing, cache design, and database cluster. Open source server software GeoServer is selected to deploy as WebGIS application experiment. Experimental results show that usage of data cache can evidently reduce response time of WebGIS service. Compared with a single physical server, the WebGIS server clusters based on cloud platform can effectively process high-concurrence requests, and with the extending of cluster scale, the WebGIS system based on cloud platform can achieve good speedup.

Abstract:Deductive reasoning is an important method in formal verification, which can address programs in infinite state systems. In this paper, a proof system is studied and implemented, where infinite proof trees transform into finite ones. Firstly, a saturation algorithm is implemented based on iterative convergence, and the completion of the saturated system is implemented using Full Permutation Algorithm; Secondly, an optimization of proof search is carried out by inductive method; At last, the proof tree is visualized in 3D space using visualization technology.

Abstract:The goal of network measurement system based on P2P is to reduce the single-point bottleneck and deployment costs. Generally, assumed to have the same capacity among the nodes, the structured P2P is unsuitable for large-scale deployment. The unstructured P2P communication is overload and its expandability is poor. Therefore, combing with the adavantages of various P2P modes, the thesis brings in layered thought, clustering of the nodes in accordance with ability, which is the heads of a cluster selected from the excellent ones form the upper high-speed transmitting net, and take control of the maintenance and management of the common nodes in the clusters. The thesis also describes the initialized establishment process of the system, function modules and self-adaption maintenance mechanism and so on. Ultimately, system prototype is taken shape. The experiment suggests that not only is the automatic deployment of the node realized, but also the expandability of the system is improved, which reduces the measurement costs.

Abstract:The high quality decision-making depends on high quality data, hence data preprocessing is an essential phase for data analytics applications. In the big data area, traditional data preprocessing systems cannot be directly applied. To handle the large-scale data, enterprises adopt Hadoop/Hive as a popular solution at the present stage. However, it brings many defects, such as poor performance, the lack of interaction and so on. To fill this gap, this paper proposes and implements an interactive data preprocessing system based on Spark. This system provides a series of common preprocessing logics as basic components and supports flexible user-defined extensions. To get an interactive interface, the system presents data to users in the form of spreadsheets, while it can automatically records users operations to provide undo and redo support. In this paper, we introduce the architecture of this system with four aspects:data model, data preprocessing operations, interactive execution engine and interactive GUI. In the end, we conduct experiments with real stroke data and the result shows that the system can meet interactive demands in most big data scenarios.

Abstract:With the development of network and multimedia technology, traditional radio station director device is still using telephone coupler or the method of combination with CTI boards and telephone Coupler, which cannot meet the needs of radio businesses. For this reason, digital multi-channel director system emerges. New generation of digital director device builded by IP communication technology based on packet-switching, can effectively solve the problems faced by traditional director device, meet the needs of radio stations and listeners. Digital multi-channel director server is the core of director systems device. This paper designs and implements a digital director server system based on Keygoe device. Digital director server system architecture is desiged with modular method. This paper presents the design and implement of modules in digital director server system, such as resource management module, policy enforcement module, message communication module, and user interface module.

Abstract:To investigate the energy consumption in different areas of the campus, the energy monitoring platform has been designed. In the process of the implementation of energy-saving regulation on campus, by using B/S, Ajax, MYSQL and PHP language, the power data is displayed to the user in the WEB page by a variety of figures.at the same time, users can master real-time data of the entire campus building energy consumption through a WEB page management, which turns distributed monitoring and centralized management for the campus energy system into reality.The emphasis is put on analyzing the key techniques during the development of the system.The development and operation practice show that the adoption of these techniques significantly enhances the monitoring efficiency of the campus power system.

Abstract:Cloud computing is a technology that enables elastic, on-demand resource provisioning. In multi-tenant shared data storage model, how to achieve dynamically scalable data storage is the key of cloud data management. For the issue of how SaaS applications adaptively scale with the change of the quantity of tenants and request, on the basis of analyzing scalability requirements of the data storage layer, based on Walraven et al. proposed multi-tenant architecture, we extend the typical cloud application architecture, and design a multi-tenant data management framework, achieving scalability of storage resources. Based on the framework, a SaaS prototype system for network management is developed, verified its validity and availability.

Abstract:Completing the design of the external disk array storage system in deep space measurement and control is the part of deep space strategy. On the basis of analyzing the performance of disk array, this paper gaves the suggestion for disk array of deep space TT&C external storage system of computer. Through the theoretical analysis and actual measurement of capacity, speed and reliability of different disk array, the results shows that Raid0 meets the demand of storage system.

Abstract:To solve the problem that the trajectory based on traditional pedestrian tracking method is very different from the real trajectory, this paper proposed an improved particle filter pedestrian tracking method based on 3D model. It used camera calibration information and image sequence information to construct 3D pedestrian model, in order to deal with scale variation and extract real trajectory. And double exponential smoothing is used to improve particle filter, so it can deal with occlusion issue and reduce computation complexity. The experiment results of this paper indicates that the proposed method can cope with the situations of targets occlusion and scale variation. It has good performance in pedestrian tracking compared to standard particle filter as well as KPF.

Abstract:3D human pose estimation using depth sensor is an important research topic in computer vision, and it is useful for applications in human-computer interaction, virtual reality, and design of animation etc. The most successful methods toward this problem are bottom-up methods which predict 3d poses using classification, regression or retrieval techniques. These methods are widely applied in human-computer interactions. However, these methods rely on a huge human pose database and the predictions are rather inaccurate. In this paper, we propose to estimate 3D human pose using personalized 3D human models and monocular depth images. We firstly reconstruct a 3D virtual human model for each subject, and in the pose estimation phase, we reconstruct incomplete mesh from depth data, and estimate the correspondences between points of the 3d human model and the incomplete mesh. We estimate the optimal 3D poses through iterative optimization of objective function. In comparison with bottom-up methods, our method is free of any pre-captured dataset. Our experiments verifies that our results are more accurate than those of other methods.

Abstract:Recommendation algorithm has a good application prospect in e-commerce systems, has been paid more and more attention and recognition, and has become a research hotspot in the field of electronic commerce. Based on the introduction of the current mainstream recommendation algorithm, in combination with the practical application requirements of e-commerce, multi-objective composite evaluation and optimization of recommendation algorithm is proposed. Based on the tuniu.com data, comparing with other recommendation algorithm, this paper verifies the effectiveness of the algorithm, and provides a new way and method of research of composite recommendation system.

Abstract:The R-tree is a highly balanced tree, and is the most widely used spatial index structure. Based on the similarity of the historical data, this paper constructs R-tree, and proposes a collaborative filtering recommendation algorithm based on R-tree (R_CF). In addition, this paper sets about from the user's implicit feedback, builds the user interest behavior data model, and standardizes data. Simulation experiments show that compared with the traditional collaborative filtering recommendation algorithm (CF), the proposed R_CF algorithm can greatly improve recommended top-n query speed.

Abstract:With the development and maturity of text classification technology, more and more enterprises have applied it to the customer complaint classification system, and obtained the certain effect. Given that the CHI-square Statistic methods tend to choose negative words, so an improved CHI statistical method is applied to the text feature selection, which means reducing the weight of negative words in the feature selection algorithm and minimizing the impact on the model. Finally, an experiment is performed on the complaint text of a communications company business. The result shows that the model and method are effective, and can be more accurate for the classification of business complaints, so as to provide data support for the follow-up problem analysis.

Abstract:Since the existing scheduling solution can not deal with the uncertainties in household appliance operation time and renewable generation, we propose a solution based on real-time electricity pricing. The solution adopts linear programming model and tries to minimize the total monetary expense. Beside, the solution takes into account the photovoltaic systems, home battery and the sale of excess energy. To handle the uncertainties in household appliance operation time and ensure the users' satisfaction, a stochastic scheduling technique and Monte-Carlo simulation are used. Finally, the simulation results demonstrate the practical significance of our solution.

Abstract:Adaptive affinity propagation clustering(adaptive Affinity propagation clustering, adAP), as a new clustering algorithm, does not need to specify the initial "exemplars" and the class number, which is effective to solve the problem of class number uncertainty in clustering. Then, as a result of the adAP is extremely time consuming, the larger the number of samples is, the slower the speed is. In order to improve the speed of the adAP, this paper realizes a parallel method, which is based on NVIDIA's Compute Unified Device Architecture (CUDA) and Matlab parallel computing toolbox. The experiment results show that the GPU-based parallel adAP method has a certain speedup effect, and it is more than 2 times faster than the serial execution. With the increase of the number of samples, the acceleration performance is getting better and better.

Abstract:The number of malicious software targeted on Android system is rapidly increasing. Therefore it is important to implement privacy protection software on smart phones. This paper introduces a new design and development of privacy protection software which encrypts the text message using lightweight block cipher encryption algorithm. This Android App provides software login protection, mobile contacts importing, conversation key setting, text message importing and message encryption and decryption features. This APP prevents the privacy leakage from the text message in Android devices.

Abstract:Collaborative filtering provides a solution for the personalized recommendation to solve the problem of information overload. But the problems of data sparsity and scalability are the serious factors affecting the recommendation quality. To solve these problems, we propose a collaborative filtering algorithm based on singular value decomposition and fuzzy clustering. We retain the number of the total characteristic value through the theory of energy conservation in the special relativity in physics, so as to determine the dimension of dimension reduction. In addition, by using the fuzzy clustering, we also reduce the search range of the neighbors. Compared with traditional collaborative filtering recommendation algorithm in the different data sets of MovieLens and 2013 Baidu movie recommendation system, the proposed algorithm performs better in the recommendation quality.

Abstract:With the development of medical and health services informatization, patient similarity becomes an important task in reuse of Electronic Health Records (EHR). By using the physician feedback on EHR data, patient similarity problem can be transformed to supervised distance metric learning problem, the supervised information usually comes from the tags we make on one patient's EHR data. In the existing work of Patient similarity Computing, the utilization of supervised is pretty circumscribed, the similarity of two different patients is often depended on their EHR data tags' completely equality. But in fact, the patient's tags contains many dimensions, that methods ignores tags' own similarity. In this work, we use the patient's diagnose data as the supervised information and divide the target patient's neighbor area into many margins based on their similarity using metric learning. The supervised information is also more fully used in this algorithm. Finally, in the multi-label KNN classification evaluation experiment, the similarity metric learned from this algorithm performs better than other algorithms in Hamming Loss and a-Accuracy.

Abstract:One scan algorithms of labeling connceted components aren't so efficient because of the need of a large number of stack operations and repeated search pixel neighborhood. The algorithm of labeling connceted components based on contour tracing, could decrease times of searching neighbours and accessing stack, improves it's efficiency, through labeling all contour pixels of one object in image before scanning and labelling it's pixels in image. In order to improve the efficiency, the proposed algorithm of labeling connected components based on contour tracing discards accessing stack, and adopts efficient algorithm of contour tracing. The algorithm has the advantages of higher efficiency, better stability than others.

Abstract:We present a method for automatic modeling in SMV of a parameterized system based on its corresponding Murphi Model. Modeling in Murphi for parameterized systems is easy because its parameterization feature, and a Murphi model code is relatively small and is not very complex to read, understand and modify. On the other hand, an SMV model could give more powerful operations, such as quick invariant checking and bounded model checking, but it is very hard to model in SMV for a parameterized system and to maintain an SMV model. We present a semantic model which is well able to describe a parameterized system, then analyze a Murphi model to create its semantic model, finally we get its corresponding SMV model which is effective for research work automatically by a series of conversion strategies.

Abstract:The inverse kinematics of a general 6R serial robots has much difficulty to be solved.The method using traditional D-H need amount of computations and exists singular solution. Inverse kinematics of puma robot decomposes into position solution and pose solution. Firstly we use D-H method to solve θ₁, θ₂, θ₃, then use the unit quaternion to solve θ₄, θ₅, θ₆. At last we verify the new method in the robot of puma and new method can solve the inverse kinematics correctly. Compared with D-H method and double quaternion method, the new method has much increase about 15% in speed than D-H method.

Abstract:The current methods for selecting time series of cloud services are failed to take into account the user preference, while the traditional user preference algorithms are only applied to the case that QoS indicators values are single numerical. QoS indicators values for time series vector case cannot be effectively quantified. This paper proposed a time series of cloud services selection algorithm which employs subjective and objective weight. The new algorithm could adapt to the different level of user preference with a subjective weight calculation method, and could evaluate correlation with an objective weight calculation method. Experiments show that the algorithm not only avoids the vagueness of user preference, but also accurately reflects the performance of the services. So the results have high accuracy and scientificalness.

Abstract:In the angle of networks security effects, malicious node behaviors lead to route failure and data destroy. So node behavior security evaluation is the most important evaluation factor in behavior detection and trust evaluation, which can debase trust value of the malicious nodes. This paper has an analysis on 9 sorts of common node behaviors profile, which presents behavior detection parameters and detection model. The results show that in the static and dynamic network environment it reaches a high detection accuracy and evaluation accuracy which can exclude malicious node from network activity effectively.

Abstract:Disaster relief demands urgent need for rapid transport of supplies. Vehicle transportation scheduling is based on large-scaled and real-time traffic network with time limit constraints and various supplies for multiple destinations lay the difficult points. To attain the target, multi objective optimization model for vehicle emergency transportation is built, and an optimized genetic algorithm is put forward to solve the vehicle scheduling problem in emergency rescue with multiple constranins including road variation, arrival deadlines and multiple materials. Based on the theory of biological evolution and principles of population genetics, the optimized algorithm takes the multi spots and in-fact road conditions into consideration, makes focus on the multiple material demands and the precedence on the arrival time without delay, designed a new coding pattern which made new encoding mode design, adaptive function, new selection, crossover and variation operators, and new generation mechanism to produce more and better patterns in less time, so as to overcome the premature convergence of the classic genetic algorithm. Tests proved the better performance of the proposed algorithm in finding the global optimized solution than the traditional genetic algorithm in delivery time constrains and the total length of arrival time, with less vehicles involved and less solving time. The proposed method can improve the transportation efficiency of disaster relief and cut down the vehicle cost, and meet the demands of complex vehicle scheduling tasks.

Abstract:A improved just noticeable distortion (JND) model based on saliency map detection algorithm is proposed for video coding in order to apply feature of visual perception to the video compression system. The optimal JND model is calculated by setting modle of pixel-based JND with the hybrid. The saliency map concluded by context aware saliency detection modle is used for the weight distribution of JND model. The proposed model and residual filter can be integrated into the framework of HEVC, which is useful for quantifying video data. The experimental results shows that in the case of visual subjective perceptual quality, the average bitrate reduction is 10.71%, compared with HM 16 (all Intra profile).

Abstract:Aimed at problem that analyzing and extracting knowledge form massive data is high computation cost, a Hadoop based knowledge extraction framework is proposed. We designe a knowledge exraction framework which combines with the parallel processing and distributed storage feature, and the framework is compatible different prototype reduction methods. Based on the MapReduce programming method the prototype reduction method is parallelly processed, and a prototype reduction combination rule with high classification accuracy and computational speed is designed. Finally, experiments results based on real UCI big data sets show that the proposed framework improves two orders of magnitude of the classification time of the nearest neighbor classifier.

Abstract:With the development of the technology of serial robots, multiple human-computer interaction control methods through computer programming is becoming a new research hotspots. This article conducts research on physical mechanism, communication and programming interface of haptic input/output device and 6-degrees of freedom serial robots, using Geomagic Touch haptic input/output device producing by Geomagic cooperation. By using OpenHaptics programming interface and UR10 robots to control script language, we construct a real-time control system of 6-degrees of freedom serial robots.

Abstract:In order to improve the prediction accuracy of photovoltaic power generation, a prediction model of photovoltaic power generation based on improved BP neural network is proposed. First, such factors as outdoor temperature, light radiation, wind speed and other factors are taken as input layer nodes while AC power is taken as output nodes, RMSE is introduced as indicators to measure the optimal model to determine number of hidden layer nodes, and then BP neural network is used to learn which cuckoo search algorithm is used to optimize BP neural network. Finally, the simulation experiment is used to test its effectiveness. The results show that improved neural network can improve prediction accuracy of photovoltaic power generation, and it has a widespread value.

Abstract:The operations of large integers have been widely used among the fields of public-key encryption algorithms, the operations of floating-point data types of large-scale scientific computation and the construction of large eigenvalues and so on. However, most of the large integer arithmetic algorithms are space and time consuming especially for the large integer multiplication, one of the core large integer operations. When data reaches a certain scale, the overlong serial computing time has been the bottleneck of the applications of the large integer algorithms. Simultaneously, with the popularity of multi-core processors in the computer field in recent years, taking advantages of the parallelism of algorithms, it'll be a trend to parallelize applications to optimize their performance efficiently by using multithread programming to take full use of the powerful computing capability of parallel computers. Meanwhile, the paper did an in-depth study on the multi-core parallelization of fast algorithms of large integer multiplication Comba algorithm and Karatsuba algorithm using the OpenMP multithread programming technology and automatic vectorization technology about the SIMD model of the Intel C++ Compiler. Besides, the testing shows that the speedup of Comba algorithm with 8 threads reaches to 5.85, and Karatsuba algorithm with 8 threads reaches 6.14 at most.

Abstract:Based on the research of IEEE802.11,referring to information related to the channel access control of Ad hoc network and analyzing the strongpoint and shortcoming of IEEE802.11, we provide some kinds of new improved methods for IEEE8 02.11 DCF to improve the performance of the system. The main work of this paper includes the following several aspects:1. Based on analyzing the shortcoming of the BEB backoff mechanism used in IEEE802.11 and referring to related improved methods, such as MILD,EIED and so on, we put forward a new backoff mechanism which is based on the status of the channel. This method is based on the busy or idle degree of the channel to certain the parameter of the contention window then can relieve the unfairness during the period of the channel access and enhance the throughput of the system.2. After analyzing the problem of the hidden terminal,exposed terminal and blocking in IEEE802.11's channel ac cess control, we modify the mechanism of DCF.During the period of deferring, we detect the channel to avoiding the false blocking. At the same time, based on the status of receiving and sending RTS/CTS we decide to transfer data parallelly to improve throughput.3. Modifying the threshold of the retransmission for RTS/CTS and DATA packet in IEEE802.11, an adaptive mechanism is used to set the threshold of the retransmission, so that the probability of packet loss is minimized and TCP's congestion control mechanism is triggered fewer.4. The NS2 network simulator is used to simulate the modified scheme. The results of the simulation show that with the modified scheme, the throughput of network is better than IEEE802.11. In this paper, we take into account the shortcoming of the IEEE802.11 and put forward some improvement. The results of this paper providesa valuable reference for the research of Ad hoc network.

Abstract:In the fields of machine translation, automatic classificationand search engine technology, Yi word segmentation plays a very important role, which is also a vital part in Yi language information processing. This paper is based on the current segmentation of Yi word.Through the construction of Yi thesaurus and webpages of Yi, we can grab the page texts of Yi. Combining with the advantages of Yi language, with a detailed analysis such as the thesaurus, word segmentation algorithm, flowchart and structure, system interface and modulesand the experimental results, we build the segmentation platform of Yi page text. Finally, the results show that the segmentation platform has a property of higher accuracy, practicality and versatility.

Abstract:The algebraic properties of curves and surfaces are directly determined by its form of parameter, such as regularity. However, in computer aided geometric design, the phenomenon of self-intersection belongs to a kind of irregularity problem which cannot be applied directly. The tubular surface, as a kind of important geometric model, mainly studiing pipe surfaces and orthogonal torus. On the basis of researching the regular tubular surface, we must attach important to researching self intersection of two kinds of special irregular tubular surfaces. The paper mainly applies algebraic methods to analyze their geometric features respectively, so as to specify some areas of self-intersection in theory. Furthermore, it can provide support to remove self-intersection exactly in the future.

Abstract:In this paper, we discuss the shortcomings of the existing embedded airborne communication system, such as poor architecture, low reuse, long development cycle and so on. We combine the traditional software engineering component technology with the domain engineering features, and propose a component reuse solution based on VxWorks. Fast constructions of several types of embedded airborne satellite communication system show that the solution realizes the reuse of resources, effectively reduces the development cost and shortens the product time to market, improving the quality of products.

Abstract:In the applications of micro area network which is composed of bus interconnection, there are some problems caused by the limitation of bus bandwidth such as low network speed and network congestion. In this paper, we propose a multi-bus fusion Ad Hoc network, which can improve the network speed and reduce network congestion. In addition, the system can detect the direction of the surrounding routing nodes, that is, the routing nodes possess the vector property.

Abstract:This paper solves the regulation optimal control problem for nonlinear systems based on the adaptive dynamic programinf(ADP) and neural networks(NNs). Firstly, we propose the regulation nonlinear system; afterwards, the cost function and its Hamilton-Jacobi-Bellman(HJB) function were given; furthermore, an actor-critic frame structure was put forward to get the optimal control, and the neural network algorithms were utilized to approximate the performance index and the optimal control ofactor-critic structures respectively. The NN weights are estimated by gradient algorithms, so that the optimal control is obtained. Simultaneously, the stability of the whole system and the convergences of actor-critic NN weights are proved based on the Lyapunov theory. Finally, the simulation results are provided to verify the effectiveness of the proposed methods.

Abstract:It is an important way to improve the application efficiency of the control simulation machine by applying speech recognition technology to training of ATC students. On the basis of analyzing the characteristics of Chinese and English control instruction, fundamentals of speech recognition technology has been studied in this paper. And a set of speech recognition technology which is suitable for the phonetic characteristics of Chinese and English contorl commands has been designed. The corresponding procedures and flight simulation interface have been designed with MATLAB. Unique control instruction speech recognition template library is completed, and under the control of voice commands, the aircraft can fly very well in the flight simulation interface. The results provide reference for further realization of the automatic simulation of captain's seat.

Abstract:Digital image processing is widely used in all fields of life, along with the higher requirement of the image transmatting information, it has been further developed and pretreatment of the noise processing is the key section. Classical methods for image denoising include the average method and median filtering, Wiener filtering, but these algorithms in noise processing has brought a series of missing details. And there are so many methods that lead to spending a lot of time selection algorithm to the specific noise, but not necessarily to get the desired effect. In this paper, the effect of the three methods of mean value method, median method and morphological method is analyzed. And combined with simulation results to adjust the parameters can obtain better quality image. The final result, morphological processing noise has more universality and superiority.

Abstract:The grain output fluctuation is a result of several factors. And there is a very complex nonlinear relation between these factors. Lacking the ability to reflect the nonlinear regulation, most of traditional prediction method leads to low accuracy of prediction. BP neural network model has good nonlinear approximation capacity and it does well in prediction of Chinese grain output. Principal component analysis can be associated with the fuzzy variable data for dimension reduction. The combination of PCA and BPNN can optimize the network structure and improve the prediction precision. The results show that the accuracy of combined model is improved by 3% and the efficiency of network training performance also has been improved in different degree.

Abstract:To solve the problem of the wheat yield estimation information lagging in current Henan province area, with the tech of integrating the sensor, GPS and wireless communication, docking the agricultural machinery equipment, the wheat yield measuring and information service system is built that is based on the multi-sensor technology to realize the simultaneous wheat yield measuring with the wheat harvest. The system application experiment has been carried out in the 800-mu experimental field in Changge county, Xuchang City in June 2015. The experimental results show that the measurement error of this system is less than 5% and could satisfy the actual demand of the real-time wheat yield measuring. The popularization and application of the system would provide the data reference for the wheat yield measuring in Henan province. Moreover, it also could provide data support for the obtaining of the spatio-temportal difference of the farmland information and offer the decision basis for the implementation of "precision agriculture".

Abstract:Due to the excellent performance of thin clients and cross-platform, VNC has been widely applied and drawn widespread attentions in the field of the Remote Desktop synchronization. In the paper, we analyze and study the overall architecture of VNC, especially the updating retrieval mechanism of the desktop of VNC server and image compression processing algorithms in RFB protocol utilized by VNC. Moreover, the direction for further optimization on VNC protocol is proposed.