语义出版:数字时代科学交流系统新模型

语义出版是基于传统互联网技术和语义网技术,结合自然语言处理、本体和信息可视化技术而发展起来的一种新兴出版形态,代表着数字出版的前沿。本文梳理语义出版的多种表现形式,分析其功能特征,进而提出语义出版的DBIU层次模型。最后,本文就语义出版在科学研究范式变革、科学出版商角色转变、科研工作方式、用户"战略阅读"和"宏知识"获取方面的影响和意义进行了深入探讨。

Catenary dropper fault identification based on improved FCOS algorithm

The contact network dropper works in a harsh environment,and suffers from the impact effect of pantographs during running of trains,which may lead to faults such as slack and broken of the dropper wire and broken of the current-carrying ring.Due to the low intelligence and poor accuracy of the dropper fault detection network,an improved fully convolutional one-stage(FCOS)object detection network was proposed to improve the detection capability of the dropper condition.Firstly,by adjusting the parameterαin the network focus loss function,the problem of positive and negative sample imbalance in the network training process was eliminated.Secondly,the generalized intersection over union(GIoU)calculation was introduced to enhance the network’s ability to recognize the relative spatial positions of the prediction box and the bounding box during the regression calculation.Finally,the improved network was used to detect the status of dropper pictures.The detection speed was 150 sheets per millisecond,and the MAP of different status detection was 0.9512.Through the simulation comparison with other object detection networks,it was proved that the improved FCOS network had advantages in both detection time and accuracy,and could identify the state of dropper accurately.

Novel method for searching ontologies on semantic web

In order to solve the problem of information retrieval on the semantic web, a new semantic information retrieval （SIR） model for searching ontologies on the semantic web is proposed. First, SIR transformed domain ontologies into global ontologies. Then semantic index terms were extracted from these global ontologies. Based on semantic index terms, logical inferences can be performed and the logical views of the concept can be obtained. These logical views represent the expanded meaning of the concept. Using logical views, SIR can perform the information retrieval and inferences based on the semantic relationships in the documents, not only on the syntactic analysis of the documents. SIR can significantly enhance the recall and precision of the information retrieval by the semantic inference. Finally, the practicability of the SIR model is analyzed.

Semantic analysis approach for construction of OWL ontology

A semantic analysis approach is proposed, by which semantic relationships between concepts are identified and defined, and then mapped or transformed to OWL （web ontology language） ontology. The most common abstractions （namely, inclusion, aggregation and association） and their implication in ontology are discussed; then the OWL implementation for three abstractions are analyzed and illustrated. Taxonomies, constraints on properties for each class, and the relations between taxonomies in OWL ontology are established after all the semantic relationships are identified and described. This research is the basis for the development of the ontology conceptual model （OCM） and the mapping from OCM to OWL ontology.

Kullback-Leibler distance based concepts mapping between web ontologies

A Kullback-Leibler（KL）distance based algorithm is presented to find the matches between concepts from different ontologies. First, each concept is represented as a specific probability distribution which is estimated from its own instances. Then, the similarity of two concepts from different ontologies is measured by the KL distance between the corresponding distributions. Finally, the concept-mapping relationship between different ontologies is obtained. Compared with other traditional instance-based algorithms, the computing complexity of the proposed algorithm is largely reduced. Moreover, because it proposes different estimation and smoothing methods of the concept distribution for different data types, it is suitable for various concepts mapping with different data types. The experimental results on real-world ontology mapping illustrate the effectiveness of the proposed algorithm.

New method for query answering in semantic web

To promote the efficiency of knowledge base retrieval based on description logic, the concept of assertional graph （AG）, which is directed labeled graph, is defined and a new AG-based retrieval method is put forward. This method converts the knowledge base and query clause into knowledge AG and query AG by making use of the given rules and then makes use of graph traversal to carry out knowledge base retrieval. The experiment indicates that the efficiency of this method exceeds, respectively, the popular RACER and KAON2 system by 0.4% and 3.3%. This method can obviously promote the efficiency of knowledge base retrieval.

Context query and association discovery for collaborative environment

A context memory model and an approach for context query and association discovery are proposed. The context query is based on a resource description framework （RDF） dataset and SPARQL language. To discover collaborative associations, an approach of transforming RDF named graphs into ＂context graph＂ is proposed. First, the definitions of the importance of the nodes and the weight assignment for the ＂context graph＂ are given. Secondly, the implementation of a spread activation algorithm based on ＂context graph＂ is proposed. An infrastructure is also built up in the collaborative context space （CCS） system to support context memory and knowledge discovery in a collaborative environment.

Searching scheme in P2P system based on semantic overlay network

In consideration of the limitation of super-peer overlay network, the semantic information was introduced into the super-peers＇ organization. A novel P2P （peer-to-peer） searching model, SSP2P, was put forward. The peers in the model were organized in a natural area autonomy system （AAS） based on the smallworld theory. A super-peer was selected in each AAS based on power law; and all the super-peers formed different super-peer semantic networks. Thus, a hierarchical super-peer overlay network was formed. The results show that the model reduces the communication cost and enhances the search efficiency while ensuring the system expansibility. It proves that the introduction of semantic information in the construction of a super-peer overlay is favorable to P2P system capability.

Projectile impact point prediction method based on GRNN

In order to forecast projectile impact points quickly and accurately,aprojectile impact point prediction method based on generalized regression neural network（GRNN）is presented.Firstly,the model of GRNN forecasting impact point is established;secondly,the particle swarm algorithm（PSD）is used to optimize the smooth factor in the prediction model and then the optimal GRNN impact point prediction model is obtained.Finally,the numerical simulation of this prediction model is carried out.Simulation results show that the maximum range error is no more than 40 m,and the lateral deviation error is less than0.2m.The average time of impact point prediction is 6.645 ms,which is 1 300.623 ms less than that of numerical integration method.Therefore,it is feasible and effective for the proposed method to forecast projectile impact points,and thus it can provide a theoretical reference for practical engineering applications.

Semantic web-based networked manufacturing knowledge retrieval system

To deal with a lack of semantic interoperability of traditional knowledge retrieval approaches, a semantic-based networked manufacturing （NM） knowledge retrieval architecture is proposed, which offers a series of tools for supporting the sharing of knowledge and promoting NM collaboration. A 5-tuple based semantic information retrieval model is proposed, which includes the interoperation on the semantic layer, and a test process is given for this model. The recall ratio and the precision ratio of manufacturing knowledge retrieval are proved to be greatly improved by evaluation. Thus, a practical and reliable approach based on the semantic web is provided for solving the correlated concrete problems in regional networked manufacturing.

Structures of semantic networks: how do we learn semantic knowledge

Global semantic structures of two large semantic networks, HowNet and WordNet, are analyzed. It is found that they are both complex networks with features of small-world and scale-free, but with special properties. Exponents of power law degree distribution of these two networks are between 1.0 and 2. 0, different from most scale-free networks which have exponents near 3.0. Coefficients of degree correlation are lower than 0, similar to biological networks. The BA （Barabasi-Albert） model and other similar models cannot explain their dynamics. Relations between clustering coefficient and node degree obey scaling law, which suggests that there exist self-similar hierarchical structures in networks. The results suggest that structures of semantic networks are influenced by the ways we learn semantic knowledge such as aggregation and metaphor.

Absolute Exponential Stability of Generalized Dynamical Neural Networks

This paper investigates the absolute exponential stability of generalized neural networks with a general class of partially Lipschitz continuous and monotone increasing activation functions. The main obtained result is that if the interconnection matrix T of the neural system satisfies that - T is an H matrix with nonnegative diagonal elements, then the neural system is absolutely exponentially stable(AEST). The Hopfield network, Cellular neural network and Bidirectional associative memory network are special cases of the network model considered in this paper. So this work gives some improvements to the previous ones.

Updating ontologies and general rules

Inconsistencies or conflicts appearing in the integration of ontologies and general rules are handled by applying prioritizing and updating. First, a prioritized knowledge base is obtained by weighting information weight. Then, based on the idea ＂abandoning the old for the new＂, the weight of each rule is greater than that of the information in ontologies. If ontologies conflict with general rules, then a new knowledge-base without any inconsistency or conflict is obtained by using rules with big weight updating information in ontologies with small weight. Thus, current logic programming solvers and description logic reasoners are employed to implement the reasoning services, such as querying etc. Updating based on prioritizing is more suitable for handling inconsistencies than other approaches to introducing non-standard semantics if knowledge bases are dynamically evolving. Moreover, a consistent knowledge base can be always maintained in the dynamical environment by updating outdated information with new information based on weighting. Finally, this approach to dealing with inconsistencies is feasibly exemplified.

Reliable and Load Balance-Aware Multi-Controller Deployment in SDN

Software Defined Networking(SDN) provides flexible network management by decoupling control plane and data plane. However, such separation introduces the issues regarding the reliability of the control plane and controller load imbalance in the distributed SDN network, which will cause the low network stability and the poor controller performance. This paper proposes Reliable and Load balance-aware Multi-controller Deployment(RLMD) strategy to address the above problems. Firstly, we establish a multiple-controller network model and define the relevant parameters for RLMD. Then, we design the corresponding algorithms to implement this strategy. By weighing node efficiency and path quality, Controller Placement Selection(CPS) algorithm is introduced to explore the reliable deployments of the controllers. On this basis, we design Multiple Domain Partition(MDP) algorithm to allocate switches for controllers according to node attractability and controller load balancing rate, which could realize the reasonable domain planning. Finally, the simulations show that, compared with the typical strategies, RLMD has the better performance in improving the reliability of the control plane and balancing the distribution of the controller loads.

Clinicopathological significance of B-cell-specific Moloney murine leukemia virus insertion site 1 expression in gastric carcinoma and its precancerous lesion

AIM： To explore the relation between B-cell-specific Moloney murine leukemia virus insertion site 1 （Bmi-1） expression and the clinicopathological features of gastric carcinoma （GC）.METHODS： Immunohistochemistry was used to detect the expression of Bmi-1 and ki-67. Doublelabeling staining was used to display the distribution of Bcl-2^＋/ki-67 cells in 162 cases of GC and its matched normal mucosa and precancerous lesion.RESULTS： The positive rate of Bmi-1 expression in GC（52.5%） was significantly higher than that in normal gastric mucosa （21.6%, X^2 = 33.088, P 〈 0.05）. The Bmi-1 expression in GC was closely related with the Lauren＇s and Borrmann＇s classification and clinicalstage （X^2 = 4.400, 6.122 and 11.190, respectively, P〈 0.05）. The expression of ki-67 was related to the Borrmann＇s classification （X^2 = 13.380, P 〈 0.05）.Bcl-2 expression was correlated with the Lauren＇s classification （Z2 = 4.725, P 〈 0.05）, and the Bmi-1 expression both in GC （rk = 0.157, P 〈 0.05） and inintestinal metaplasia （rk = 0.270, P 〈 0.05）.CONCLUSION： Abnormal Bmi-1 expression in GCmay be involved in cell proliferation, apoptosis andcancerization. This marker can objectively indicate theclinicopathological characteristics of GC.

A Game-Theoretic Approach to Elastic Control in Software-Defined Networking

Elastic control could balance the distributed control plane in Software-Defined Networking(SDN). Dynamic switch migration has been proposed to achieve it. However, existing schemes mainly focus on how to execute migration operation, but not why. This paper designs a decision-making mechanism based on zero-sum game theory to reelect a new controller as the master for migrated switches. It first chooses a switch for migration in the heavy controller which invites its neighbors as the game players to compete for the master role of this switch in the game-playing field(GPF) which is an occasional and loose domain for game-playing. Second, based on the concept of GPF, we design a decentralized strategy to play the game and determine which player as the final master. We implement it by extending the Open Flow protocol. Finally, numerical results demonstrate that our distributed strategy can approach elastic control plane with better performance.

SDICN: A Software Defined Deployable Framework of Information Centric Networking

the Information-Centric Networking(ICN) paradigm is proved to have the advantages of decreasing data delivery latency, enhancing user mobility, etc. However, current implementations of ICN require changing the infrastructure of Internet, which hinders its deployment and development. Meanwhile, Software Defined Networking(SDN) emerges as a viable solution to facilitate the deployment of new network paradigm without disrupting production traffic by decoupling the control plane from data forwarding plane. In this paper, the essential properties which reflect ICN working principles are summarized, and a framework called SDICN is designed in accordance to the SDN philosophy. The algorithmic frameworks of SDICN which can satisfy the essential properties are designed based on the programmability and virtualization functions of SDN. Based on Open Flow and data center technology, a prototype of SDICN is implemented. By comparing the performance with the CCNx, the SDICN is proved to be feasibility and availability.

Linking a Game Engine Environment to Architectural Information on the Semantic Web

Because of the importance of graphics and information within the domain of architecture, engineering and construction （AEC）, an appropriate combination of visualization technology and information management technology is of utter importance in the development of appropriately supporting design and construction applications. Virtual environments, however, tend not to make this information available. The sparse number of applications that present additional information furthermore tend to limit their scope to pure construction information and do not incorporate information from loosely related knowledge domains, such as cultural heritage or architectural history information. We therefore started an investigation of two of the newest developments in these domains, namely game engine technology and semantic web technology. This paper documents part of this research, containing a review and comparison of the most prominent game engines and documenting our architectural semantic web. A short test-case illustrates how both can be combined to enhance information visualization for architectural design and construction.

Knowledge presentation model for QnA web forums

For an extract description of threads information in question and answer （QnA） web forums, it is proposed to construct a QnA knowledge presentation model in the English language, and then an entire solution for the QnA knowledge system is presented, including data gathering, platform building and applications design. With pre-defined dictionary and grammatical analysis, the model draws semantic information, grammatical information and knowledge confidence into IR methods, in the form of statement sets and term sets with semantic links. Theoretical analysis shows that the statement model can provide an exact presentation for QnA knowledge, breaking through any limits from original QnA patterns and being adaptable to various query demands; the semantic links between terms can assist the statement model, in terms of deducing new from existing knowledge. The model makes use of both information retrieval （IR） and natural language processing （NLP） features, strengthening the knowledge presentation ability. Many knowledge-based applications built upon this model can be improved, providing better performance.

A New Method of Semantic Network Knowledge Representation Based on Extended Petri Net

Abstract： It was discussed that the way to reflect the internal relations between judgment and identification, the two most fundamental ways of thinking or cognition operations, during the course of the semantic network knowledge representation processing. A new extended Petri net is defined based on qualitative mapping, which strengths the expressive ability of the feature of thinking and the mode of action of brain. A model of semantic network knowledge representation based on new Petri net is given. Semantic network knowledge has a more efficient representation and reasoning mechanism. This model not only can reflect the characteristics of associative memory in semantic network knowledge representation, but also can use Petri net to express the criterion changes and its change law of recognition judgment, especially the cognitive operation of thinking based on extraction and integration of sensory characteristics to well express the thinking transition course from quantitative change to qualitative change of human cognition.