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In order to speed up the development of new iron-base alloy materials and reduce the consumption of time and resources caused by a large number of experiments, a prediction method for Gibbs free energy of iron-base alloy materials was proposed based on the theory of material genetic engineering. Firstly, the collected data were preprocessed by splicing, filling, normalization and one-hot coding to adapt to the training of the model. Then, based on the DeepFM model, a fusion model based on Factorization Machine (FM), bitwise self-attention mechanism and Bi-directional Long Short-term Memory Network (Bi-LSTM) was proposed to predict the Gibbs free energy of iron-base alloy materials. It can not only extract the low-order and high-order features of the data effectively, but also the weight coefficients of each data feature can be reasonably optimized and the correlation between the data can be fully considered. The comparative experimental results show that the Gibbs free energy prediction method based on deep learning has a good prediction effect. It provides a new method to predict the Gibbs free energy of iron-base alloys.

By identifying the privacy concern degree of different users, we can provide users with targeted tips on telling the risk of privacy disclosure existed in Micro-blogs. For this purpose, the indexes of 4 aspects for distinguishing between high and low privacy concerns are selected, according to user attributes, potential tendency towards privacy concerns, privacy exposure of following friends and privacy disclosure events, and were processed quantitatively. Then, three machine learning methods of Adaboost-C4.5 decision tree, support vector machine and logical regression are used to establish the determination model and the corresponding algorithm. The compared experimental result showed that, the accuracy rate and recall rate of Adaboost-C4.5 decision tree to determinate privacy concerns is the highest in the three methods.

When using chaotic variables to solve optimization problems and encryption problems, it needs to study different dimension of chaotic images. We studied nonlinear dynamics systems performance about several chaotic images in different dimensions, including the phase diagram, Lyapunov exponent, probability density, etc. In order to improve their chaotic performance, the improvement measures were given for one-dimension tent system and two-dimension henon system, and a new chaotic system were proposed, it was two-dimension logistic system. It contained nolinear factor, the new system possessed higher level of complexity. Therefore, we can overcome the chaotic crisis of tent image, improve the probability density of henon system and obtain new higher-quality chaotic system 2d-logistic from the existence chaotic systems. The Runge-Kutta method for hyperchaos system was given, and applied it to the three-dimensional Lorenz chaotic system, we acquired its diagram in different axis efficiently. The simulation experiments were conducted, and the comparison test results were analyzed in detail. The study provides important scientific support to the improvement and application of chaotic systems.

Along with the popularization of e-Commerce and the development of the business of the corporations, requirements of collaboration among supply systems of inter-corporations and inner-corporations become more and more popular. And traditional integration technologies of enterprise applications cannot adapt to the quick increment of the enterprise information system. The birth and development of Web provides a new integration technology for enterprise applications. At the same time, the IT infrastructure could provide a better service, let the enterprise, customer, partner, supplier and distributor attend commercial activity conveniently and get information what they want. This is the aim that every enterprise wants to reach. In order to attain this aim, they always use integration. Through this way all business entities would be related in together, share commercial data, and complete the commercial activity together. But tradition "point-to-point" integrated method unable to satisfy the enterprise's electronic commerce demand and cause high cost and low efficiency. An integration solution based on Web(face service construction) is put forward, which utilizes the open standard and protocol, from the global viewpoint, connect the enterprise's business process and IT infrastructure. Then a unified, standardized integration platform will be established.

The paper combines rough set theory and adaptive genetic algorithm to enhance color image. First, regard the image as a knowledge system, and adopt classification method of rough set theory to combine image color attribute and noise attribute to classify the image, and then come into image boundary region and apply different enhancement algorithms to enhance the image. During rough set classification, use adaptive genetic algorithm to optimize threshold to obtain a best classification result. As image enhancement can be effectively carried out through practical application and verification, therefore, such algorithm has some certain application value.

This paper introduces the structure which bases on the DeviceNet control network system. It describes a general-purpose microprocessor. It is a platform for DeviceNet I/O interface development process, communication protocol, object modeling, application layer software design idea. Giving a detailed hardware, software design process and implementing the network communication based on DeviceNet.

Fractal coding is a novel method to compress images, which was proposed by Barnsley, and implemented by Jacquin. It offers many advantages. This paper proposes a new method using best polynomial approximation to decide whether a domain block is similar enough to a given range block. Also the paper gives a kind of domain pool. It is found that the probability distribution of 8 isometries in the fractal code is not average. And consequently it is proposed to use only 2 or 4 isometries to speed up compression. At last some testing results on Lena and Peppers are given.

In this paper, issues of informatization of domestic and foreign enterprises are described. For the selection of the best and second best of resource allocation, measurement and appraisal in the enterprise informatization dynamic equilibrium models, the enterprise informatization capacity maturity and dynamic equilibrium models are proposed from the corporate informatization level, quality, capability and moderation. The theory of second best is used to analyze the enterprise informatization resource allocations and solve the issues of methods, appraisal and application moderation.

Image fusion is the process by which multiple images of the same scene are combined to generate a more accurate description of the scene than any of the individual source images. Multi-source image fusion is an important topic in the image understanding and computer vision field. Focusing on the evaluation problems in the multi-source image fusion, this document makes systematic analysis and research on the methods of subjective qualitative evaluating as well as objective quantitative evaluating the image fusion performance. Based on the features and interrelations of these methods, this document gives an evaluation system and corresponding evaluation criterion for the multi-source image fusion, which have important directive to the application of the image fusion methods in actual projects.

Image fusion aims to obtain a new image meeting a certain requirement. It achieves this goal by synthetically processing the multiple images obtained from different sensors or the same sensor based on a certain algorithm. By processing the remote sensing images of the different platforms and sensors with the same target or scene, the image fusion technology can generate a new remote sensing image, which has the features and information of both source images. As the new fusion image can provide more comprehensive information and thus provide powerful technical support for the synthetic analysis and extraction of remote sensing information, the image fusion technology has become a key technology in terms of remote sensing image processing. While improving the spatial texture features of the final remote sensing images and enhancing the ability of the multispectral images in expressing spatial details, the HIS transform fusion method also causes great spectral distortion. Wavelet analysis is a time-frequency analysis method featuring multi-resolution analysis. It grows from the Short Time Fourier Transform (STFT). Owing to its characteristic of time-frequency localization, wavelet analysis is widely used in the image processing field. This document designs and realizes a new remote sensing image algorithm which is based on HIS and wavelet transforms.

The hardware components of embedded system for fiscal cash register is introduced. The functions and characteristics of BSP (Board Support Package) in the development of embedded system is discussed. The key techniques of BootLoader and its driver’s design within Nucleus Plus operating system is analyzed in detail. Design examples are given. The BSP presented in this paper is manufactured and works for fiscal cash register. The functions and performance meet national standards.

In essence, Service Oriented Architecture (SOA) is distributed and shall not have any centralized control point. Any application can access an SOA network for interaction as long as it complies with the corresponding standards. A centralized SOA architecture can also be regarded as a part of SOA. This paper gives a general overview of the fundamental principles, features, and core technologies of distributed SOA, analyzes the integration of distributed object technologies and Web technology, and describes the difference between distributed SOA and centralized SOA. With the previous as a basis, this paper discusses the function and implementation of SOA in the distributed architecture, proposes an SOA-based distributed multi-layer architecture and an application integration frame realized via J2EE. This application integration frame can connect any distributed application without restriction and support data and function sharing among applications,thus simplifying the implementation of the functions at various layers and providing better maintainability and scalability.

Data mining is not an autonomous data-driven trial-and-error process, but a human-machine-cooperated interactive knowledge discovery process. As a result, the domain-driven data mining is proposed. Additionally, there are lots of models existing in oil and gas exploration and production, such as geological models, logging constrained seismic inversion models and well logging interpretation models, which contain the multifarious domain knowledge. This paper proposes model-driven data mining in the oil and gas exploration and production, with the purpose of mining actionable knowledge benefiting the exploration and production of oil and gas. Main ideas of the model-driven data mining methodology are introduced. Guided by this methodology, we demonstrate some of our work in mining four types of data, including petrophysical data, logging data, seismic data and geological data. Real work of model-driven data mining has shown that our methodology is practical and potential for deeply analyzing data in the exploration and production of oil and gas.

The software systems grow rapidly with the development of software technologies. Traditional Enterprise Application Integration technology can not adapt to the rapid increase in the Enterprise Information Systems. In SOA, different development tools can interact with each other to realize integration. With standard protocol, Web can integrate all kinds of heterogeneous system into current system conveniently and quickly, especially provide a high-quality and low-cost solution to enterprise application integration. Using SOA technology to realize EAI will resolve all sorts of shortage in EAI technology among distributed different- structure systems, moreover it makes the integration of application programs faster, easier and more effective than before. This paper introduces the integration of enterprise application, then analyzing the architectures and key technologies of SOA, propose a SOA-based solution to the integration of enterprise application realized via J2EE.

With the rapid growth in business size, todaypsilas businesses orient towards electronic technologies. Unfortunately the enormous size and hugely unstructured data on the Web. Extracting valuable information from such an ever-increasing data is an extremely tedious task towards the success of businesses. Web content mining can play a major role in solving these issues and application of Web content mining can be very encouraging in some areas. In this paper we present a review of some very interesting, efficient yet implementable techniques from the field of Web content mining and study their impact in the area specific to business user needs focusing both on the customer as well as the producer. These techniques have been analyzed and compared on the basis of their execution time and relevance of the result they produced against a particular search.

In this paper, the implementation of a Model Predictive Control (MPC) strategy for livestock ventilation systems and the associated indoor climate through variable valve opening and exhaust fan, is presented. The design is based on Thermal Comfort (TC) and Indoor Air Quality (IAQ) parameters for poultry in barns. The dynamic models describing the nonlinear behavior of ventilation and associated indoor climate, by applying a so-called conceptual multi-zone method are used for prediction of indoor horizontal variation of temperature and carbon dioxide concentration. The simulation results illustrate the significant potential of MPC in dealing with nonlinearities, handling constraints and performing offset free tracking for multiple control objectives. The entire control systems are able to determine the demand ventilation rate and airflow pattern, optimize the Thermal Comfort, Indoor Air Quality and energy use.

In this paper, the implementation of a new autocovariance least-square (ALS) technique for livestock hybrid ventilation systems and associated indoor climate with a model predictive control (MPC) strategy is presented. The design is based on thermal comfort parameters for poultry in barns and a combined dynamic model describing the entire system knowledge. Reference offset-free tracking is achieved using target calculation and quadratic programming and adding a disturbance model that accommodates unmeasured disturbances entering through the process input. The unknown noise covariances are diagnosed and corrected by applying the ALS estimator with the closed loop process data. The comparative simulations show the performance improvement with the ALS estimator in the presence of disturbances and moderate amount of error in the model parameters. The results demonstrate the high potential of ALS methods in improving the best practice of process control and estimation.