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This paper mainly introduces a management information system about college teacher workload based on ASP.NET and ADO.NET technology. The system adopts B/S structure, benefits the using of client. And the system realized the digital and dynamical management, reduces the time of examination and approval, improves the efficiency and veracity of work. The paper analyses the theory of system development, function of system, and design scheme of system.

MVC is a typical software architecture model The paper states the development principle and advantages of the MVC pattern, discusses the software development process based on the MVC pattern, and designs a Web application— library management system. On the basis of introducing books management system, this paper describes the system design and implementation method based on MVC pattern. The use of MVC model improves maintainability and reusability of the system. KeywordsMVC model; JSP; Servlets; Javabeans

3DR-tree is an index method using the traditional R-tree to index moving objects. Its defect is that a cube generates when an object remains still for a period of time. For those objects that remain still for a long period of time, many strip cubes will generate. MBR will be overlong or overlarge, thus increasing a great deal of overlap and reducing index performance greatly. This paper is to improve the 3DR-tree model to enhance index performance. On the basis of 3DR-tree, this paper will put forward improving historical data index performance of 3DR-tree through node splitting. 3DR-tree is provided with the online data index function by means of tree splitting.

The Passive Location of Emitter based on Fuzzy Method.[Purpos The use of passive observation station to achieve the precise location has been an important topic of monitoring the electromagnetic spectrum resources and the environment. In order to locate the emitter accurately, a new method called fuzzy method is presented in this papers. [MethoBased on the distribution of points of intersections that are figured out by the LOB(Lines of Bearing), the paper put forward a fuzzy method for the passive location of emitter based on membership function to achieve the location of emitter. We compared this method with Pages method using 100 sets experimental data through the Monte Carlo simulated experiment. [Result The results showed that this method can effectively achieve the location of emitter, and improve the location accuracy. [Conclusion The positioning precision of this algorithm is obviously superior to Pages algorithm.

Nowadays, demand for automated Gas metal arc welding (GMAW) is growing and consequently need for intelligent systems is increased to ensure the accuracy of the procedure. To date, welding pool geometry has been the most used factor in quality assessment of intelligent welding systems. But, it has recently been found that Mahalanobis Distance (MD) not only can be used for this purpose but also is more efficient. In the present paper, Artificial Neural Networks (ANN) has been used for prediction of MD parameter. However, advantages and disadvantages of other methods have been discussed. The Levenberg–Marquardt algorithm was found to be the most effective algorithm for GMAW process. It is known that the number of neurons plays an important role in optimal network design. In this work, using trial and error method, it has been found that 30 is the optimal number of neurons. The model has been investigated with different number of layers in Multilayer Perceptron (MLP) architecture and has been shown that for the aim of this work the optimal result is obtained when using MLP with one layer. Robustness of the system has been evaluated by adding noise into the input data and studying the effect of the noise in prediction capability of the network. The experiments for this study were conducted in an automated GMAW setup that was integrated with data acquisition system and prepared in a laboratory for welding of steel plate with 12 mm in thickness. The accuracy of the network was evaluated by Root Mean Squared (RMS) error between the measured and the estimated values. The low error value (about 0.008) reflects the good accuracy of the model. Also the comparison of the predicted results by ANN and the test data set showed very good agreement that reveals the predictive power of the model. Therefore, the ANN model offered in here for GMA welding process can be used effectively for prediction goals.

The selection of a desirable machine is an important concern for the manufacturing firm. The selection process contains some critical selection attributes and the task of this process is to choose the desirable machine from a number of candidate machines. Then the machine selection problem is actually a multi-attribute decision making problem. This paper will develop a preference selection index method to solve the problem of machine selection in a flexible manufacturing cell. A case study is used to demonstrate that the proposed method is effective and feasible.

Researches on technologies about testing aggregate bandwidth of file systems in cloud storage systems. Through the memory file system, network file system, parallel file system theory analysis, according to the cloud storage system polymerization bandwidth and concept, developed to cloud storage environment file system polymerization bandwidth test software called FSPoly. In this paper, use FSpoly to luster file system testing, find reasonable test methods, and then evaluations latest development in cloud storage system file system performance by using FSPoly.

Medical researchers seek to identify and predict profit (or effectiveness) potential in a new medicine B against a specified disease by comparing it to an existing medicine A, which has been used to treat the disease for many years, called medicine assessment. Applying traditional data mining techniques to the medicine assessment, one can discover patterns, such as A.X=a à B.Y=b, which are identified at the attribute-value level. These patterns are useful in predicting associated behaviors at the attribute-value level. However, to evaluate B against A, we have to obtain globally useful relations between B and A at an attribute level. Therefore, this paper proposes a group interaction approach for multiple data source discovery. Group interactions include, such as rules, differences, and links between datasets. These group interactions are discovered at the attribute level. For example, R(A.X, B.Y), where R is a relationship, or a predication. Some examples are presented for illustrating the use of the group interaction approach.

t is a tough work to select accurate web pages for search engine. This paper applied a semantic parsing model into search engine by comparing the conceptual structures between users input and text. The words, sentences and sentence groups can be mapped into conceptual symbols, semantic categories, and contextual elements based on the theory of Hierarchical Network of Concepts. The approach will improve the intelligence and flexibility of the search engine in future.

Recently, wireless sensor networks (WSNs) have attracted a lot of attention from the network research community, especially in the aspect of event-driven wireless sensor networks (EWSNs), such as adversary locating, fire detection and so on.As the nature of importance of event monitoring, security has to be assured in both of communication and processing. However, due to the inherent resource constraints, security inEWSNs is faceddifferent issues and challenges than traditional WSNs.In this paper, we attempt to give an outline on the security issuesin the EWSNs. And then we propose a new secure architecture for it, which covers potential security issues. In this architecture, we analyze the possible threats and give out the correspondingcountermeasures.

Semantic Web application is the application of semantic Web technology, of which the data containing semantic, thus is able to support the knowledge understanding and the knowledge processing. It can share information and refine information dynamically through the Internet access, which makes more full use of the existing Web resource on the Internet. In this paper, the definitions of semantic Web application as well as the structure and properties are formulated. A semantic Web development model is constructed with reference to the Web application development model.

With the development of component technology, component granularity plays a very import role on the complexity of component composition. How to assemble the component of big granularity? How to make the component in the same domain integrated? Application framework brings the new era of software-reused technology. But how to construct application framework to make it higher reuse? According to the current research of application framework, the paper gives a hierarchy model; The model divides application framework into several layers. Different application framework in different layer has different solutions and the higher the application framework stands in, the lower the probability of change is.

Android is one of the most popular smart phone and tablet platforms; Zigbee is the standard for home automation and will play an important role on future WPAN. Enabling the Zigbee communication on Android can exploit the rich network and nice display power of the Android phone in Zigbee applications. In this paper we present our work on integrating CC2530 into an Android smart phone. Based on JNI library, the software is developed to enable Android system can control the CC2530 module insides. The firmware in CC2530 is also discussed. The test is carried on with the configuration that an Android smart phone communicates with a standalone CC2530 node via Zigbee radio. The test verified the design feasibility. Keywords-Android devices, zigbee networks; JNI library; wireless networks

The form of fruit fly optimization algorithm (FOA) is easy to learn and has the characteristics of quick convergence and not readily dropping into local optimum. This paper presents the optimization of RBF neural network by means of FOA and establishment of network model, adopting it with the combination of the evaluation of the mean impact value(MIV) to select variables. The validity of this model is tested by two actual examples, furthermore, it is simpler to learn, more stable and practical. Keywords-FOA; RBF neural network; Parameter optimization; MIV; Variables screen

Server virtualization is to create and run several independent operation systems at the same time to maximize the utilization efficiency and flexibility of IT resource, the most serious security problem of which, however, is the unauthorized access of unsafe virtual machines. This paper presents a SELinux-based secure server virtualization method against the issue. With SELinux access control, virtual machine process is isolated from system processes by setting up different type labels and access control policies. Whats more, different virtual machine processes can be independent with each other by introducing Multi Category Security (MCS) protection mechanism, thus to achieve secure access of server virtualization. Finally the realization of the method is presented.

Under the study of Kernel Methods, this paper put forward two improved algorithm which called R-SVM & I-SVDD in order to cope with the imbalanced data sets in closed systems. R-SVM used K-means algorithm clustering space samples while I-SVDD improved the performance of original SVDD by imbalanced sample training. Experiment of two sets of system call data set shows that these two algorithms are more effectively and R-SVM has a lower complexity.

More and more organizations and individuals outsource their storage and computing business into cloud computing, which is a representation of a movement towards the intensive, large scale specialization and economy. Cloud computing brings about convenience and efficiency, but challenges in the areas of data security and privacy protection. This paper identifies the most vulnerable security threats in cloud computing, which will enable both end users and vendors to know about the key security threats associated with cloud computing, and to know about critical analysis about the different security models and tools proposed. Key security strategies from the infrastructure, operation and security incident response relieve the common security issues of cloud computing.

This paper proposed a framework and an algorithm for identifying communities in dynamic social networks. In order to handle the drawbacks of traditional approaches for social network analysis, we utilize the community similarities and infrequent change of community members combined with community structure optimization to develop a Group-based social community identification model to analyze the change of social interaction network with multiple time steps. According to this model ,we introduced a greed-cut algorithm and depthsearch-first approach and combine them to develop a new algorithm for dynamic social interaction network recognition (called ADSIN). In addition, we conduct experiments on the dataset of Southern Women, the experiment results validate the accuracy and effectiveness of ADSIN. Key words-social network; community recognition; time step; φ

Cloud computing has changed people's work, life and learning while more and more collaborative learning based on cloud services are applied to the field of education and teaching. This paper analyzes the collaborative learning characteristics supported by cloud computing and designs collaborative learning programs of College Computer Basis based on cloud services.

This paper combined with computer graphics and related spatial information sciences technologies, made use of the software Vega Prime, On the basis of three-dimensional modeling of Nanchang HangKong University campus, built a campus three-dimensional visual simulation software, which can achieve the campus landscape, zoom, rotation, scaling, flight roaming and static and dynamic simulation capabilities, such as the fountain, lake, pedestrians, vehicles, etc. The use of this technology has great importance on school enrollment, employment, education, alumni relations, showing the school strength and other aspects.

Data island exists in most of the information system. And the system platform integration could eliminate the existence of the information island. This paper visited database information system through the EJB component technology, and using the metadata way to extracted data information from the heterogeneous database system, and it realized sharing information between the heterogeneous database system. In this system the B/S mode structure and EJB component technology, improve the system usability and expansibility.

Computer network generate a spatial and temporal separation in teaching activities, the new feature of the online teaching also make it possible to improve students' learning efficiency by using of the theory of interactive activities and appropriate teaching strategies. This paper mainly discuss the problems exist in distance teaching system based on the Internet, and design an prototype model for distance teaching which could achieve a unified and efficient management of curriculums, teachers, students and teaching resource according to the specific requirement of school.

in order to solve the access control system loopholes, can appear the problem of chaotic management, security failure and conflict of competence, this paper studies the access control model, on the basis of the design of a SSL VPN oriented access control system, the authentication module, access control module, role access module and security detection module design. The realization technology of system user identity. This has practical reference significance to the personnel security technology research network.

Nowadays, microblog has emerged as the most promising social networking service in the Web2.0 age with diverse features for information dissemination, interpersonal communication and many other aspects. Chinese microblog shows great potential owing to the rich marketing source and powerful media influence brought by the huge user population. As the microblog community is largely influenced by some authoritative users, identifying these users and understanding the information dissemination pattern are theoretically and practically significant for us to promote user services, develop further applications and seek commerce opportunities. In this paper, we proposed a modified method for user authority ranking. A user-message graph modified according to Chinese microblog was applied to our study, and an algorithm based on ObjectRank was used to calculate ueser authority scores. We analyzed Sina microblog, as it was the most widely adopted Chinese microblog and more resources for research was accessible.

This paper describes the cold rolling database system based on Web platform and the relevant technology of this system. Adopt tree-tier B/S architecture,ASP.NET technology, C# programming language. By communicating in different data storage of application , a dynamic, execute, interactive, highly efficient network application software has been built. KeywordsCold Rolling Materials; Web Database; ASP.NET; Internet

In this paper we intend to apply a new method to predict tertiary structure. Several feature extraction methods adopted are physicochemical composition, recurrence quantification analysis (RQA) , pseudo amino acid composition (PseAA) and Distance frequency. We construct the binary tree Classification model, and adopt flexible neural tree models as the classifiers. We will train a number of based classifiers through different features extraction methods for every node of binary tree, then employ the selective ensemble method to ensemble them. 640 dataset is selected to our experiment. The predict accuracy with our method on this data set is 63.58%, higher than some other methods on the 640 datasets. So, our method is feasible and effective in some extent.

Anomaly detection has been a field of intensive research over the last years. Along with that several works to evaluate anomaly detectors have been proposed. In this paper we argue four properties regarding ideal evaluation methodologies that cannot be answered by single current evaluation technique employed today. We therefore present an framework of an evaluation methodology that leverages traces from operational networks, simulation and emulation to satisfy the four properties.

The cloud computing can greatly reduce the cost of computing, but is unable to ensure either the integrality or the confidentiality of data and calculation. Therefore, this paper considers of the safety of cloud computing, combining the thought of abstract algebra group theory in modern algebra, puts forward TCCPoGT (trusted cloud computing platform based on group theory) that designs in many different respects,such as general structure, public key cryptosystems and node management,etc. The analysis results show that the platform TCCPoGT can insure service security.

This paper studies the development trend of intelligent mobile phone, confirmed the necessity of research on intelligent mobile phone malicious code. Study on the detection technology, proposed intelligent mobile phone regular networks and random networks based on malicious code propagation model, propagation mechanism is studied. Set up a perfect malicious code discovery and defense system model, at different levels is put forward that different, prove the necessity of scanning algorithm and Semantic Detection Algorithm for eigenvalue. To improve the security of the whole communication network.

As the information age is coming, there is a vast amount of information available in the Internet. Most of data on Web are unstructured. But the significant data should be organized and stored in a suitable way for future purposes. One of the unsolved problems is the management of unstructured data. The unstructured data such as presentation, spreadsheet, text document, memo, images and web pages are difficult to manage while the data become a large scale and the users have different requirements and interests. In this paper, we proposed an architecture for unstructured data management by integrating source query, data collection and data management to solve these problems. The data collection layer extracts the data we care about, we use the existing tools to extract automatic and we can also add the data to the repository manually. The data management layer manage all the collection data by classifying the data, selecting nodes to store and managing centralized as index. The source query layer allows users to query and get the data diversity according the adaptive query service and recommendation service. Finally, we implemented a prototype system OCourse based on this system architecture to show its feasible and efficient.

The Rapid development of cloud computing impels the new situation of information technology services in foreign language teaching in universities, and brings more quality requirements to subject librarians in universities. The teaching database of English reading in universities combines image, audio, video, text, animation and interactive contents for teaching to create a fresh, vivid, interesting English learning environment. The paper proposes the implementation strategies of university English reading teaching datebase construction and the cloud service model according to the concept of cloud computing; It thinks that the subject librarians should supply personalized services for the readers, at the same time, they should also strive to be cloud librarians.

Web Service architecture gradually matures in the related applications of campus network, but campus network anomaly mining technology still needs further development in its confidentiality, integrity, and non-repudiation problems. In SOA, campus network anomaly mining technology still needs to strengthen safety and reliability. Based on suffix tree technology, this paper proposed the application of campus network information security technology based on network anomaly mining technology, analyzed the campus network security features in detail, and designed an anomaly mining algorithm on suffix tree campus network security. Computer simulation results show that the proposed method can rapidly mine the abnormalities of the network and ensure the security of campus network. KeywordsWeb log; Campus network; information security; data mining algorithm

Big data phenomenon refers to the practice of collection and processing of very large data sets and associated systems and algorithms used to analyze these massive data sets. Big data service is very attractive in the field of wireless communication environment, especially when we face the spatial applications, which are typical applications of big data. Because of the complexity to ingest, store and analyze geographical information data, this paper reflects on a few of the technical problems presented by the exploration of big data, and puts forward an effective storage method in wireless communication environment, which is based on the measurement of moving regularity through proposing three key techniques: partition technique, index technique and prefetch technique. Experimental results show that the performance of big data storage method using these new techniques is better than the other storage methods on managing a great capacity of big data in wireless communication environment.

This paper adopts statistical learning theory and optimization theory to the analysis of the algorithm theory, probe into its theoretical foundation. The existing theoretical analysis on the basis of the establishment of clustering model algorithm design, code realization and finally a lot of different data set of test, choose soil data as a test database, will be in the database on a large number of data mining experiment to verify the performance of the proposed algorithm. The test result feedback back will further deepen the theoretical research or correct theory already mistakes, new theory and will continue to guide experiments, both mutual promoting common development.

Federated Media Publishing means to distribute the single source content through multimedia after integrating various media manners, which is the trend of digital publishing. DITA is designed to produce multiple deliverable formats from a single set of DITA content, but it cant be directly used in Federated Media Publishing for not coping well with multimedia except for text and image. This paper takes music as an example to discuss the method of integrating multimedia into DITA. The specialization facility is used to integrate MusicXML DTDs into DITA and a solution is putted forward to provide appropriate rendition distinctions according to audio and five-line staff. Experiments show the solution is efficient to extend DITA for dealing with multimedia, which can be used in federated media publishing.

Data mining is the techniques of finding the potential law from the data by machine learning and statistical learning .This paper focuses on a number of problems existed in the currents ports training, discusses the application principle of the data mining technology in sports training, and applies the critical neural networks for forecasting the performances of the athletes .Experimental data show that prediction of athletic performance by the use of neural network has very good approximation ability. It shows a broad application space of the use of data mining technology.

The most serious threats for Android users is come from application, However, the market lack a mechanism to validate whether these applications are malware or not. So, malware maybe leak users private information, malicious deductions for send premium SMS, get root privilege of the Android system and so on. In the traditional method of malware detection, signature is the only basis. It is far enough. In this paper, we propose a runtime-based behavior dynamic analysis for Android malware detection. The new scheme can be implemented as a system. We analyze 350 applications come from third-party Android market, the result show that our system can effectively detect unknown malware and the malicious behavior of malware.

In this paper, we construct a web-based document life-cycle management model. The model manages documents which consist of the institute library from their creation to the archive state. For an online office system, we aim at solving three issues: network delay, version storage problems and deletion strategy. To solve network delay, we propose both local and online document synchronized editing model. In addition, we combine the longest recursive chain with recursive chain time to optimize the system response time. In order to optimize documents to be deleted, we propose a two-step optimized method. In the performance test, the effectiveness of the method is confirmed to solve the issues of documents management.

The method of modeling is the key technology for digital mockup (DMU). Based upon the developing for mechanical product DMU, the theory, method and approach for virtual environment (VE) and virtual object (VO) were studied. This paper has expounded the design goal and architecture of DMU system, analyzed the method of DMU application, and researched the general process of physics modeling and behavior modeling.

The application and development of computer network system bring a great convenience for library management and readers. At the same time, the security of computer network system in library is faced with all kinds of threats. How to guarantee the security of library computer network system has become the most important question for each library. This paper analyzes the factors which affect the library network security, such as network hardware, network operating system and application system, data security and so on, and puts forward corresponding security strategies and solutions.