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ISO 14649 standard, commonly recognized as STEP-NC is a data model interface for computer numerical controllers. STEP-NC goes much further that G codes and has a more comprehensive data model that overcomes the lack of process information in ISO 6983 files (G codes programming). The STEP compliant approach brings the possibility to integrate the machine controller to the overall enterprise information network, with the intention of having bi-directional data flow. This will provide the novel capability for upstream feedback of information from the numerical controller to the design and process areas in the process planning and manufacturing. This paper presents the key concepts of the proposed STEP Convertor of the STEP-CNC Mapping System. The objective of the main system is to take a generic STEP file as the input to drive a CNC machine tool. The main system is broken down into two main sub-systems, STEP Convertor and STEP-NC Translator. This paper will focus solely on the information structure and conceptualization of the STEP Convertor.

In this paper, several data mining techniques were discussed and analyzed in order to achieve the objective of human daily activities recognition based on a continuous sensing data set. The data mining techniques of decision tree, Naïve Bayes and Neural Network were successfully applied to the data set. The paper also proposed an idea of combining the Neural Network with the Decision Tree, the result shows that it works much better than the typical Neural Network and the typical Decision Tree model.

This paper describes the design and implementation of a mini multi-process micro-kernel embedded Unix-like operating system on ARM platform in technical details, including MMU and memory space mapping, init process, inter-process communication, process management, TTY and tiny shell, multi-level priority-queue schedule, and signaling. The mini OS is developed on Linux platform with GNU tool chain by the author of this paper. The architecture of the mini OS is analogous to that of Minix. Based on it, other operating system components such as file system, network management, and copy-on-write can be appended to form a full-featured embedded operating system. The mini OS can be used for both embedded system application development and related curriculum teaching.

Inspired by the research of human visual system in neuroanatomy and psychology, the paper proposes a two-way collaborative visual attention model for target detection.In this new method , bottom-up attention information cooperates with top-down attention information to detect a target rapidly and accuractly. Firstly,the statistical prior knowledge of target and background is applied to optimize bottom-up attention information in different feature space and scale space.Secondly, after the SNR of salience difference between target and interference is computed ,the bottom-up gain factor is obtained.Thirdly, the gain factor is applied to adjust bottom up attention information extraction and then to maximize the salience contrast of target and background.Finally, target is detected by adjusted saliency.Experimental results shows that the proposed model in this paper can improve the real-time capability and reliability of target detection.

This paper proposes a survey on smartphone security from the aspect of mobile malware, specifications related to smartphone security, and smartphone security solutions. The contribution of this paper helps people to quickly know about definition of malware, attack channels and black industry chain of smartphone security, international and domestic mobile security specification, and smartphone security solutions by security vendors.

This paper describes the design and implementation of Web based secure embedded system, including tiny secure Web server, embedded system-based CGI library, and utilities for security, such as CAPTCHA program and mail sending program. The entire system is designed in C by the author of this paper on Linux platform with GNU tool chain. A Web based secure embedded application demo system is also designed to show the architecture and running effect. On the premise of implementing essential functions, the scale of the system is designed as small as possible therefore it is suitable not only for embedded Linux development on Web based applications but also for embedded system course teaching in colleges and universities. By some further extensions, it can also be used on development of general Web based MIS.

This paper aims at one of key technologies in digital television development ---intelligent personalized recommendation technology of digital TV programs for study. This paper proposes to take advantage of ample TV-Anytime to describe metadata so as to perform specific plans of guide service for TV programs based on TV-Anytime metadata specification. It combines technology such as data mining and artificial intelligence etc with a view of building a personalized TV program recommendation system on the framework of the multi-agent. Besides, a hybrid algorithm with content filtering and collaborative filtering based on the systematical recommendation algorithm has been put forward. In order to overcome the deficiencies of traditional collaborative filtering algorithm which relies on users explicit evaluation, the paper represents an improved algorithm with the footing of content collaborative filtering.

At present, Cross Site Scripting (XSS) vulnerability exists in most web sites. The main reason is the lack of effective validation and filtering mechanisms for user input data from web request. This paper explores vulnerability detection method which based on taint dependence analysis and implements a prototype system for Java Web program. We treat all user input as tainted data, and track the flow of Web applications, then we judge whether it will trigger an attack or not. The taint dependent analysis algorithm mentioned in this paper is used to construct the taint dependency graph. Next the value representation method of the string tainted object based on finite state automata is discussed. Finally, we propose the vulnerability detection method for the program. The experiment result shows that the prototype system can detect reflection cross-site scripting vulnerability well in those programs which dont have effective treatment for the user input data.

By investigating insufficiency of typical artificial intelligence algorithms aiming at the high rate of False-Positives and False-Negatives in the Intrusion Detection Systems (IDS), this paper presents an approach that Support Vector Machine (SVM) is embedded in Network Intrusion Detection System (NIDS). At the same time, by using online data and K-fold cross-validation method, this paper proposes a method to optimize the attributes and model of SVM respectively. Experimental results show that by using this method as the detection core of the intrusion detection system, the rate of False-Negatives in IDS can be reduced significantly.

This paper describes the technical details of design and implementation of embedded system-based CAPTCHA (verification code) in C, including a brief analysis of techniques for implementing CAPTCHA, and a simple and practical CAPTCHA system designed by the author of this paper, which can be used not only in embedded systems but also ordinary Web based MIS or control systems, without the support of any dedicated graphics library. An example is provided to show the practical usage and effect of this CAPTCHA system on an embedded application demo system.

The medical health insurance claims application case the inspection usually relies on experts’ experience for verification and experienced personnel in charge for checking. This paper takes advantage of data-mining technology to design models and find out cases requiring for manual inspection so as to save time and manpower. By the analysis of the 20/80 principle and the coverage and accuracy ratio, a great number of periodic data (over 2 million records) are fed back to the data-mining models after repetitive verification. Also, it is discovered that to integrate the data-mining technology and feed back to different business stages so as to establish early warning system will be an important topic for the health insurance system in hospital’s EMR in the future. Meanwhile, as the information acquired by data-mining needs to be stored and the traditional database technology has limitations. Next time, this paper explores the ontology framework to be set up by semantic network technology in the future in order to assist the storage of knowledge gained by data-mining.

Higher power consumption in data centers results in more heat dissipation, cooling costs and degrades the system reliability. Conventional power reduction techniques such as dynamic voltage/frequency scaling (DVS/DFS) have disadvantages when they are ported to current data centers with virtualization deployments. In this paper, we give a short survey and discussion on some issues and aspects of DVS/DFS in data centers. This paper also presents a simple comparison of four power management schemes in virtualization environments.

End users and consumers of halal industry are facing difficulties in finding verified halal information. This occurred due to information that is stored in silos at every point of activity for every process chain, employing different structures and models, creating an issue of information verification. Integration of multiple information systems generally aims at combining selected systems so that information can be easily retrieved and manage by users. A proposed five components metadata representation development methodology is presented in this paper so that they form a unified new whole and give users the illusion of interacting with one single information system, therefore, data can be represented using the same abstraction principles (unified global data model and unified semantics) without any physical restructuring.

This paper shows how a databased approach towards production optimization was realized with the help of cloud-technologies. Several uncertainties, either in the manufacturing of the producing machines or in the production on these machines can be systematically reduced. In this way a significant improvement in production amount, but also in produced quality can be reached.

Ontologies represent inter-related semantic information. The automated integration of new knowledge helps to detect and reduce data-induced conflicts and model-based uncertainty in ontologies. However, automatic extension of an existing ontology from heterogeneous distributed sources can often lead to incomplete and contradictory entities. In order to resolve these conflicts and to complete entities, inductive inference mechanisms should be applied in addition to the deductive mechanisms already in use. This paper first describes various inductive inference mechanisms and compares these with each other according to pre-defined requirements and other criteria. Finally, the mechanisms’ suitability for an information model for the exchange and visualization of uncertainty in load-carrying systems and possible combinations of the individual mechanisms are discussed, also with respect to the necessity of further modifications of these mechanisms.

For decades, multiple lighting simulation software packages and plugins for commercial software have been developed in an effort to ease the usage and integration of simulation into the lighting design process. In this effort, one of the main challenges is to provide lighting designers with an easy and comprehensive access to simulation results. Visualization is used as a means to achieve this goal. In this paper, we explore two of the most used free lighting simulation packages towards the identification of visualization techniques that facilitate the access to the simulation results as well as the identification of opportunities for the enhancement of simulation-assisted lighting design processes. A test case of a metal workshop illustrates the output produced by both software packages. Based on this exploration, we identified an open gap regarding three main aspects: interactive exploration of simulation results, visualization of compliance with lighting standards, and visual comparison of lighting solutions. We provide a discussion on how approaches from other domains can be applied to close this gap.

Ultrasonic signal reconstruction for Structural Health Monitoring is a topic that has been discussed extensively. In this paper, we will apply the techniques of compressed sensing to reconstruct ultrasonic signals that are seriously damaged. To reconstruct the data, the application of conventional interpolation techniques is restricted under the criteria of Nyquist sampling theorem. The newly developed technique - compressed sensing breaks the limitations of Nyquist rate and provides effective results based upon sparse signal reconstruction. Sparse representation is constructed using Fourier transform basis. An l1-norm optimization is then applied for reconstruction. Signals with temperature characteristics were synthetically created. We seriously corrupted these signals and tested the efficacy of our approach under two different scenarios. Firstly, the signal is randomly sampled at very low rates. Secondly, selected intervals were completely blank out. Simulation results show that the signals are effectively reconstructed. It outperforms conventional Spline interpolation in signal-to-noise ratio (SNR) with low variation, especially under very low data rates. This research demonstrates very promising results of using compressed sensing for ultrasonic signal reconstruction.

Big Data is widely used in many organizations nowadays. Hive is an open source data warehouse system for managing large data set. It provides a SQL-like interface to Hadoop over Map-Reduce framework. Currently, Big Data solution starts to adopt HiveQL tool to improve execution time of relational information. In this paper, we investigate on an execution time of query processing issues comparing two algorithm of ORC file: ZLIB and SNAPPY. The results show that ZLIB can compress data up to 87% compared to NONE compressing data. It was better than SNAPPY which has space saving 79%. However, the key for reducing execution time is Map-Reduce that were shown by a less query execution time when mapper and data node were equal. For example, all query suites in 6-node(ZLIB/SNAPPY) with 250-million table rows has quite similar execution time comparison to 9-node(ZLIB/SNAPPY) with 350-million table rows.

This paper introduces a methodology for the type synthesis of two degree-of-freedom hybrid translational manipulators with identical legs. The type synthesis method is based upon the screw theory. Three types of two degree-of-freedom hybrid translational manipulators with identical legs are identified based upon their wrench decomposition. Each leg of the manipulators is composed of a proximal module and a distal module mounted in series. The assembly conditions and the validity of the actuation scheme are also defined. Eventually, some novel two degree-of-freedom hybrid translational manipulators are synthesized with the proposed procedure.

In past few decades, most of the modern electrophysiological concepts and methods were developed by the computational technique extensively to compute the cardiac action potential in nerve cells. Thus, tissue models consisting of a large number of single cell models cause a problem in the amount of computation required to obtain meaningful results from simulations. One of the solutions to this problem is by implementing the simulation through hardware modeling using a Field Programmable Gate Array (FPGA). Here, a research on developing a real-time simulation tool responsible for reentrant excitations in a ring of cardiac tissue based on the FitzHugh-Nagumo (FHN) model has been carried out by using a Xilinx Virtex-6 XC6VLX240T ML605 development board FPGA. In order to invest some of the time savings for creating the FPGA prototype, rapid prototyping method introduced by MathWorks which are MATLAB Simulink and its HDL Coder toolbox have been used to automate the algorithm design process by converting Simulink blocks into Hardware Description Language (HDL) code for the FPGA using a fixed-point data type in discrete-time framework. In this paper, the method and the optimization of the HDL design through the MATLAB Simulink have been discussed and the model is successfully converted into an optimal fixed-point VHDL design and the operating frequency is increased from 26.29 MHz to 53.61 MHz by using HDL Coder.

In this paper the Takagi-Sugeno type fuzzy logic was utilized for the purpose of control of electromagnetically levitated steel ball system. The system is the basis for important systems such as, the modern train which floats along the rails, aerospace shuttles, magnetic bearings and high precision systems. Such systems apart from being nonlinear they are also not stable. Results were obtained using the SIMULINK/MATLAB software and the control system developed for the electromagnetically levitated steel ball system was able to stabilize it with good response.

Vibration analysis has proven to be the most effective method for machine condition monitoring to date. Various effective signal analysis methods to analyze and extract fault signature that embedded in the raw vibration signals have been introduced in the past few decades such as fast Fourier transform (FFT), short time Fourier transform (STFT), wavelets analysis, empirical mode decomposition (EMD), Hilbert-Huang transform (HHT), etc. however, these is still a need for human to interpret vibration signature of faults and it is regarded as one of the major challenge in vibration condition monitoring. Thus, most recent researches in vibration condition monitoring revolved around using Artificial Intelligence (AI) techniques to automate machinery faults detection and diagnosis. The most recent literatures in this area show that researches are mainly focus on using machine learning techniques for data fusion, features fusion, and also decisions fusion in order to achieve a higher accuracy of decision making in vibration condition monitoring. This paper provides a review on the most recent development in vibration signal analysis methods as well as the AI techniques used for automated decision making in vibration condition monitoring in the past two years.

Application of axiomatic design (AD) for the purpose of enhancing end-of-life recovery potential of a product has been the main focus of this paper. To demonstrate the usage of AD in this particular area, a case study that involves keypad assemblies of mobile phones is presented. The functional requirements (FR) of the two assemblies were defined differently (only Handset 2 involves refurbishment-related FRs). Using evaluation approach presented by Kwak and Kim (2010), it can be observed that when recovery-related requirements are omitted, application of AD produces a keypad assembly that fulfills the FRs derived from customer needs with more complicated product architecture. In contrast, when recovery-related FRs are included during problem definition using axiomatic approach, the disassemblability of the resulted keypad is improved and thus increasing recovery potential in the event of replacing defective keypad, while satisfying product-related FRs.

The paper summarizes an experience of information system implementation in mechanical engineering industry of Russia Federation. Methodological spaces of information supply in mechanical engineering enterprise have been approved. Effectiveness of creation and usage of non-unified information systems for information gathering about local socio-economic issues has been estimated. Conjointly with the friendly user interface individually tuned for each stakeholder, and realized on the base widely used webserver Apache 2.2, using programming language PHP, as well as using database engine mysql 5.5 with report import into unified format like SPSS or Excel, the system confirms its own usefulness.

We take the overall architecture of internetware on-line evolution model as basic, and study on trust metric model of the software in internetware system. In view of the not accurate results from the rough and existing trust metric model granularity, this paper proposed a multi service and hierarchical dynamic trust metric model based on time frame. Model also offer a method to established time frame weighted factor based on inducing ordered weighted operator, which makes the trust measurement results more accurate. The trust measurement results obtained from the model will be used as decision-making basis for Bias game model.

A method for deriving the parameters of a six-degree-of-freedom (6-DoF) aircraft dynamics model by adopting reverse engineering techniques is presented. The novelty of the paper is the adaption of the 6-DoF Aircraft Dynamics Model (ADM) as a virtual sensor integrated in a low-cost navigation and guidance system designed for small Unmanned Aircraft (UA). The mass and aerodynamic properties of the JAVELIN UA are determined with the aid of an accurate 3D scanning and CAD processing. For qualitatively assessing the calculated ADM, a trajectory with high dynamics is simulated for the JAVELIN UA and compared with that of a published 6-DoF model of the AEROSONDE UA. Additionally, to confirm the validity of the approach, reverse engineering procedures are applied to a published CAD model of the AEROSONDE UA aiding to the calculation of the associated 6-DoF model parameters. A spiral descent trajectory is generated using both the published and calculated parameters of the AEROSONDE UA and a comparative analysis is performed that validates the methodology. The accurate knowledge of the ADM is then utilized in the development of a virtual sensor to augment the UA navigation and guidance system in case of primary navigation sensor outages.

An Intelligent-Data Management System (IDMS) for store separation analysis has been developed for Stores Separation Simulation program. The characteristics of the IDMS generically focuses on gathering, collecting, analysing, reporting, summarising and visualising validated data prior separation activity in simulated environment. The components of IDMS are Aircraft Configuration, Interface Configuration, Stores Geometry, Pylon Configuration and Cube (a multi-dimensional visibility of Form, Fit and Function stores-platform Data Verifier). Overall, this project combined information from separation patterns analysis by integrating multi-dimensional databases, systematic-data orchestration; rules based data mining for stores separation verifier into one data management system. This paper presents the program review of overall store separation simulation program.

In digital tourism, the current hot topic on tourism is applying data mining [1] technology to conduct deep analysis and disposal on mass data of tourism information in order to provide service for individual needs of user. This paper mainly introduced a kind of tourism service intelligent recommendation system based on Apriori-MD algorithm. Through data comparison analysis, we found that Apriori-MD algorithm was a kind of intelligent recommendation method with superior performance whose enforcement efficiency was doubled compared to Apriori algorithm. Satisfactory recommendation result can be obtained according to the demand of users and has wide application prospect in tourism market.

The Outlier detection is one of the major issues that has been worked out deeply within the Data Mining domain. It has been used to detect dissimilar observations within the data taken into the account. Detection of outliers helps to recognize the system faults and thereby helping the administrators to take preventive measures before it rises. In this paper, we recommends a comprehensive survey of an outlier detection. We anticipate this survey will support a better understanding of various directions in which experimental approach can be done on this topic.

Manpower allocation determines the competence of the companies. Scientific manpower allocation calls for accurate evaluation on the abilities that the employees have for the posts. In this paper, we first present a general fuzzy clustering model for manpower evaluation for companies. To verify the approach, a new distance-based evaluation model is also presented. Simulation results demonstrated the accuracy of our research.

People have learnt from biological system behaviours and structures to design and develop a number of different kinds of optimisation algorithms that have been widely used in both theoretical study and practical applications in engineering and business management. An efficient supply chain is very important for companies to survive in global competitive market. An effective SCM (supply chain management) is the key for implement an efficient supply chain. Though there have been considerable amount of study of SCM, there have been very limited publications of applying the findings from the biological system study into SCM. In this paper, through systematic literature review, various SCM issues and requirements are discussed and some typical biological system behaviours and natural-inspired algorithms are evaluated for the purpose of SCM. Then the principle and possibility are presented on how to learn the biological systems' behaviours and natural-inspired algorithms for SCM and a framework is proposed as a guide line for users to apply the knowledge learnt from the biological systems for SCM. In the framework, a number of the procedures have been presented for using XML to represent both SCM requirement and bio-inspiration data. To demonstrate the proposed framework, a case study has been presented for users to find the bio-inspirations for some particular SCM problems in automotive industry.

Part of speech contains important grammatical information, so it has great significance for the natural language understanding while the words in the sentence are marked on the parts of speech. POS tagging rules based on statistical methods and rule-based method can mining effectively, but its marked accuracy need to be improved. This paper presents a statistical method and rules of the combination of speech tagging rule mining algorithm in order to improve the correct rate of marked.

Although the rapid development of the modern distance education, there is still some shortcomings. In order to overcome these shortcomings and use a large number of data in these remote teaching sites effectively, it is necessary for the introduction of data mining technology to the modern remote education system. The paper introduced distance education system based on Web mining, and how data mining of these distance education website.Modern distance education is the common trend of the development of education in the world. With the development and application of satellite and cable TV, as well as a variety of electronic communications technology, especially with the advancement of the global computer network and multimedia technology, many universities have established distance education platforms. Because of a large number of students, we are relative lack of educational resources nowadays. For this reason, our country is actively developing modern distance education and integrating the various types of educational resources by advanced information technology and educational technology.

Tree growth management decision-making model can simulate growth management of tree and perform quantitative analysis of tree growth conditions. This paper explores the feasibility of modern information technology in management assessment of tree growth, information technology include neural network, ontology and expert system technology, then ontology technology is used to establish ontology database and knowledge base of tree growth management resource, the growth simulation and tree growth management ontology technology are used to build simulation models of tree growth, then expert systems and neural network technology are combined to simulate tree growth development process of decision-making model. The practice has proved that the research can not only predict the growth conditions of tree and dynamic grasp the growth process of the tree, but also can provide theoretical basis for the analysis and evaluation of tree growth management, greatly improving the level of tree growth management.

This paper reports on the design of software based on Android operating system, which enables smart phone, tablet PC and other devices to communicate with WEB server through the network. The WEB server then sends the data got from connection with school shared database to Android client device in JSON way. Data synchronization is made on a regular basis between campus education administration systems, students and faculty systems, scientific research systems, library system and the shared database. Thus campus information inquiry and interaction can be achieved by mobile devices such as Android smart phone or tablet computer.

The process monitoring and fault diagnosis is one of the important problems in the process industry. Archived monitoring data is valuable for long-term analysis and decision making. In this paper, we propose a general architecture to manage and storage archived monitoring data. It has been implemented within an archiving terabytes of monitoring data in metallurgy industry. It is an effective way to solve the problems of the efficiency and expandability via practical applications.

In this paper, we use GA to improve the D-S evidence theory, and apply the improved D-S evidence theory to VIP intelligent recognition and recommendation system. In the VIP intelligent recognition and recommendation system of clothes, there are three main evidences: body size, personal preferences, and purchase records. So collision often happens inevitable. This requirement asks us to find out a suitable method to identify the VIPs needs. D-S evidence theory can improve the rate of identification, but has no idea about the collision. The improved D-S evidence theory based on genetic algorithm can deal with the collision evidence and improve the rate of the identification and the stability. As such we can provide VIP more suitable recommendation. The experiment results of clothes recommendation demonstrate the flexibility of the improved method.

Database technology is of great variety, structure diversity, solving data integration and exchanges sharing of the heterogeneous database system have became the important problem in all fields. Because of XML is the very important data exchange technology to realize data exchange and transmission ability, this paper mainly explores the data exchange problem how to use XML in heterogeneous database system, , and .Net platform have good support to XML and heterogeneous database system, so the combination of XML and.net, can realize data exchange of heterogeneous database system.

In this paper,we design a uniform circular array beamforming device of 16 yuan based on the least squares SLC-LSCMA algorithm (based on the linear subspace constrained least squares cma) high stability and rapid convergence for the foundation. The design of the complete beam-forming the SLC-LSCMA algorithm by plural, time-multiplier and accumulators, which uses less resources and faster than the traditional algorithm. The beamforming device uses hardware description language of Verilog HDL , and wires on the QUARTUS II 8.0. Finally the beamforming device is downloaded to the Alteras EP2C35F672C6, and its timing simulation can be run properly in the 50MHz clock frequency. This design can be widely used in mobile communication and satellite communications.

In C language, it is difficult to use the pointer to access the two-dimensional array element. The reason is the addresses of two-dimensional array are many, pointers that can access the two-dimensional array element are many and complex. This paper analyzes the two-dimensional array address and pointer, introduces various forms of using pointer to express two-dimensional array element, explains the relationship between pointer and two-dimensional array address. The program examples show how to use pointers to access the two-dimensional array element.

The grade examination management program is various, workload is big, and efficiency is low. This paper on the basis of the existing educational system and the provisions of the state on the basis of grade examination system, developed a test management data transfer system based on ADO.NET technology, the heterogeneous data interconnection test process, the full realization of cyber source sharing, improving the efficiency of examination management. Through the introduction of test data of the design has been completed and mature and stable operation of the system, detailed description of the design and implementation, it has good application value.

This paper analyzes the deficiency of P2DR security model, and proposes a kind of new active dynamic security model AD-RPPDRRM, in which risk analysis, management and recovery are imported. On the basis of this model, basic technologies used to implement the defense in depth system are discussed. At last, a defense in-depth system of a typical network is given.

Power grid is a complicated and huge system, many links are involved during its life-cycle, and serious information exchange and sharing problems can be found between these links, they restrict the level of power grids informatization construction. With the presentation of building information modeling (BIM) and the application of IFC standard, the research for building different life cycle stages of information exchange and sharing is strongly pushed forward as well as gained good results. The successful application of BIM in construction business provides great chance for grid whole life data information integration and sharing. After intensively studying every links business and data characteristics of power grid, cooperated with the BIM theory, this paper comes up with a method that applies BIM theory into power system data integration and sharing, with an electric power data integration platform construction scheme based on BIM, by which grid full life cycle of data integration and sharing problem can be successfully solved.

A model of emotional interaction agents in intelligent tutoring systems is presented in this paper, and the functionalities of the key components of the agents are described. To improve the emotional interaction between learners and the system, a kind of emotional interaction agents which can deduce users emotional statues, provide helps needed, and mark emotional difficulty of the learned pedagogical units, is introduced and discussed in detail in order to improve pedagogical effects.

Based on Howard Gardner s Multiple Intelligence theory, this paper puts forward that college English teaching assisted by multimedia technology and network could promote multiple intelligence to the greatest extent. By taking advantage of students-center, teachers-mediator, task-base drive, constructivism approach, network support, extra-curriculum assist, which all contribute to multiple intelligence development, both college English teaching and multiple intelligence are bond to obtain its best effect.

Accurate detection of the direction of hydraulic fracturing cracks in the oil field is one of the crucial factors in rational exploitation of the remaining oil and enhanced oil recovery. In this paper, using the potential and the potential gradient test methods and virtual instrument technology, we design and develop an intelligent borehole-surface electrical method multi-parameters detection system (BEMDS), which can achieve multi-channel, multi-parameter and high-precision borehole-surface electrical method data acquisition. Joint programming technology of Labview and Matlab gains the simultaneously measurement of the parameters of resistivity and induced polarization. As a result, the drawbacks of the original instrument that measuring single parameters and cannot mutually authenticate has been overcome.

Based on the idea of "functionality-centric", this paper proposes a complete set of oriented semantic query methods for Deep Web, builds up the relevant software architecture, provides a new method for full use of Deep Web data resources in semantic web environment through describing the establishment of the semantic environment, re-writing the SPARQL-to-SQL query, semantic packaging of semantic query result, and the architecture of semantic query services.

With the rapid development of network technology and the promotion of application, web has become the main platform of the issuing and accessing information. It is current research focus, how to obtain the information required by the user from the vast information source. This paper presents an extraction method of website information based on DOM to improve the searching efficiency, which only to preserve the theme information and to filter out the noise information that the users are not interested in.

Aiming at the incompleteness and uncertainty of information existing in power system fault diagnosis, a new fault diagnosis approach based on Bayesian network is proposed in this paper. Through the Bayesian network of structure learning and parameter learning, a power system fault diagnosis model based on Bayesian network has been proposed. Conditional probability table describes the connection degree between various factors in quantity. Diagnostic results of instance proved the effectiveness and superiority of the proposed method.

With the dramatic increase in amount of information in campus network, the security and high reliability of access data have become urgent requirements on redundancy reliability design of campus network. This paper adopts the technology of VRRP and takes advantages of double backup sets and router to process the design and configuration. As is shown in the experiment, when one device fails, the other ones can still complete relevant operations under the conditions of double backup sets. Therefore, the redundancy reliability design of campus network can be realized through the technology of VRRP double backup sets.