Earticle

With the widespread development of the Semantic Web, large-scale ontologies are being developed in more real-world applications to represent and integrate knowledge and data. There is an increasing need for measuring the cohesion of these ontologies for better understanding, maintenance, reuse and integration. The ontology cohesion metrics proposed in this paper can be used as a very useful complementarity of existing ontology cohesion metrics. Specifically, we first propose a set of evaluation metrics to measure the cohesion of ontologies based on directed acyclic graph. Following the framework for software measurement validation, we then evaluate the effectiveness of the proposed metrics theoretically. Finally, we conduct experiments using a set of classical ontologies; the results show that the proposed metrics are reasonable and effective.

One-class support vector machine (OCSVM) is an important and efficient classifier used when only one class of data is available while others are too expensive or difficult to collect. It uses vector as input data, and trains a linear or nonlinear decision function in vector space. However, the traditional vector-based classifiers may fail when input is matrix. Therefore, it makes sense to study matrixzed classifiers which can make use of the structural information presented in the data. In this paper we propose a matrix-based one-class classification algorithm named Kernel-based Matrixzed One-class Support Vector Machine (KMatOCSVM). It aims to convert the OCSVM to suit for matrix representation data and to deal with nonlinear one-class classification problems. The efficiency and validity of the proposed method is illustrated by four real-world matrix-based human face datasets.

With the rapid development of urbanization, the importance of civil air defense projects is becoming more and more obvious, how to use the new technology to carry on the effective management becomes an important issue. In this paper, the author research on constructional organization design of single built civil air defense based on geographic information system. By using the technology of GIS and MIS to manage the attribute data and spatial geographic data of civil air defense project, enterprise could manage the civil air defense engineering efficiently. In addition, as the GIS function is added to the system, civil air defense project location can be directly displayed on the map, all the operations of the system can be directly carried out on the map interface, making the system more easy to use than the traditional MIS system.

Deep learning is a technique of machine learning in artificial intelligence area. Deep learning is a refined "machine learning" algorithm that surpasses a considerable lot of its forerunners in its capacity to perceive syllables and pictures. As of now Deep learning is a greatly dynamic examination territory in machine learning and example acknowledgment society. It has increased colossal triumphs in an expansive zone of utilizations, for example, speech recognition, computer vision and natural language processing and numerous industry items. Neural networks are used to implement the machine learning or to design intelligent machines. In this paper thorough survey to all machine learning paradigms and application areas of deep machine learning and different types of neural networks with applications are discussed.

Triaxial compression tests had been performed to determine the properties of the rock mass around unlining underground crude oil a storage cavern which was the first one in China. The execution situation of the tunnel project and the seepage law of groundwater were taken into account. The stress and the seepage field around the tunnel in different working states were simulated by applying Comsol around a underground crude oil storage caverns. According to the test results, it was found that the excavation process may arise the local damage. The extension of the loose zone induced by excavation ranged from 0 to 15.6 m, depending on the buried depth of the caverns. According to numerical simulation results, the crown settlement and stress concentration was depended on the buried depth and the water pressure distribution after excavation of the main cavity. This research results can provide the reference for analysis on the stability of the underground cavities under low stress level and on the water sealed underground petroleum storage rock caverns.

Firstly, through the analysis of traditional processing mode of jewelry industry, the reason that influences or restricts the production and development of enterprises is obtained. Combined with the practical experience in scientific research, a production model taking computer technology as the core is proposed, and then the proposed model is compared with the traditional model on the advantages and tested in practical production, and achieved certain results. This study combines the computer aided design and rapid prototyping technology in the fields of computer technology with actual production requirement, and realizes the "concurrent engineering" from the "product development" to "product promotion", further to "product production" in jewelry industry chain, improving the production efficiency and achieving diversity development of business.

In the present study, the linear attenuation coefficient and mass attenuation coefficient have been calculated at energy range of 0.8MeV, 1MeV, 3Mev, 5MeV and 7MeV. The mass attenuation Coefficient μm has been calculated analytically for Iron material Fe (ρ= 7.87 g/cm3) and developed material lead Pb (ρ= 11.3 g/cm3) at photon energies [0.8 MeV to 7 MeV] using X-Com computer code. The obtained results were compared with the calculated values. The linear attenuation Coefficient μ has been calculated, its variations with photon energy were plotting. The Comparison between two materials Iron and Lead were also studied. The obtained result shows that μ and μm depends on the photon energy, density of the materials and atomic number. From this study we notice that the values of μm and μ of Lead material is greater than Iron material and also the values are decreasing with increasing the photon energy. The half value layer (HVL) and tenth value layer (TVL) of two studied materials were calculated at photon energy range of 0.8 MeV, 1MeV, 5MeV and 7MeV. The relation between this equation Ln (Io/I) and the thickness of material were calculated, so the curves show that the relation of Ln (Io/I) of Iron and Lead materials is increasing with the increasing of material thickness and the relation gives the straight line, also the comparison of this relation for Lead material is higher than Iron material. This study can also be utilized to improve the effectiveness of radiation shielding by using the developed shielding material.

Interrupt response is an important index to measure the embedded operating system, and the high efficiency interrupt handling mechanism can greatly improve the system's interrupt response. In this paper, we analyze interrupt processing flow of MQX Lite, and propose a fast interrupt mechanism ,in which Emergency handling is embedded in the kernel ISR. The interrupt response time of three interrupt handling points including kernel interrupt, user terminal and user task in the fast interrupt mechanism is detected, and the experimental data show that the mechanism can significantly improve the system's interrupt response, and can meet the high risk of high voltage, explosion-proof, and other high risk applications.

n consideration of effectively balancing government financial subsidies and customer satisfaction rate of rural logistics services in China, a bi-level programming model is newly developed to improve the cooperation between government and logistics enterprises. A heuristic algorithm is used to obtain the optimal solution to the new It is found that the proposed model has a good performance to obtain applicable and model. effective schemes for the prosperous development and progress of Chinese rural logistics.