西方早期音乐史论的概念范畴、知识体系和现实意义

"早期音乐复兴"被认为是上个世纪西方音乐学术界最重大的一个热门话题之一,但是国内学界目前还尚未涉足。文章将对其概念范畴、早期音乐研究的重要知识体系和早期音乐研究的现实意义三个方面论述这一特殊的学术领域,并结合早期小提琴的典型研究案例进行介绍和分析。

A Study on Short Text Matching Method Based on KS-BERT Algorithm

To improve the accuracy of short text matching,a short text matching method with knowledge and structure enhancement for BERT(KS-BERT)was proposed in this study.This method first introduced external knowledge to the input text,and then sent the expanded text to both the context encoder BERT and the structure encoder GAT to capture the contextual relationship features and structural features of the input text.Finally,the match was determined based on the fusion result of the two features.Experiment results based on the public datasets BQ_corpus and LCQMC showed that KS-BERT outperforms advanced models such as ERNIE 2.0.This Study showed that knowledge enhancement and structure enhancement are two effective ways to improve BERT in short text matching.In BQ_corpus,ACC was improved by 0.2%and 0.3%,respectively,while in LCQMC,ACC was improved by 0.4%and 0.9%,respectively.

Embedding-based approximate query for knowledge graph

To solve the low efficiency of approximate queries caused by the large sizes of the knowledge graphs in the real world,an embedding-based approximate query method is proposed.First,the nodes in the query graph are classified according to the degrees of approximation required for different types of nodes.This classification transforms the query problem into three constraints,from which approximate information is extracted.Second,candidates are generated by calculating the similarity between embeddings.Finally,a deep neural network model is designed,incorporating a loss function based on the high-dimensional ellipsoidal diffusion distance.This model identifies the distance between nodes using their embeddings and constructs a score function.k nodes are returned as the query results.The results show that the proposed method can return both exact results and approximate matching results.On datasets DBLP(DataBase systems and Logic Programming)and FUA-S(Flight USA Airports-Sparse),this method exhibits superior performance in terms of precision and recall,returning results in 0.10 and 0.03 s,respectively.This indicates greater efficiency compared to PathSim and other comparative methods.

Generation of scale-free knowledge network with local world mechanism

In order to simulate the real growing process, a new type of knowledge network growth mechanism based on local world connectivity is constructed. By the mean-field method, theoretical prediction of the degree distribution of the knowledge network is given, which is verified by Matlab simulations. When the new added node＇s local world size is very small, the degree distribution of the knowledge network approximately has the property of scale-free. When the new added node＇s local world size is not very small, the degree distribution transforms from pure power-law to the power-law with an exponential tailing. And the scale-free index increases as the number of new added edges decreases and the tunable parameters increase. Finally, comparisons of some knowledge indices in knowledge networks generated by the local world mechanism and the global mechanism are given. In the long run, compared with the global mechanism, the local world mechanism leads the average knowledge levels to slower growth and brings homogenous phenomena.

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.

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.

Expert recommendation system based on analyzing expertise and networks of human resources in National Science & Technology Information Service

This work aims to implement expert and collaborative group recommendation services through an analysis of expertise and network relations NTIS. First of all, expertise database has been constructed by extracting keywords after indexing national R＆D information in Korea （human resources, project and outcome） and applying expertise calculation algorithm. In consideration of the characteristics of national R＆D information, weight values have been selected. Then, expertise points were calculated by applying weighted values. In addition, joint research and collaborative relations were implemented in a knowledge map format through network analysis using national R＆D information.

Modeling and Robustness of Knowledge Network in Supply Chain

The growth and evolution of the knowledge network in supply chain can be characterized by dynamic growth clustering and non-homogeneous degree distribution.The networks with the above characteristics are also known as scale-free networks.In this paper,the knowledge network model in supply chain is established,in which the preferential attachment mechanism based on the node strength is adopted to simulate the growth and evolution of the network.The nodes in the network have a certain preference in the choice of a knowledge partner.On the basis of the network model,the robustness of the three network models based on different preferential attachment strategies is investigated.The robustness is also referred to as tolerances when the nodes are subjected to random destruction and malicious damage.The simulation results of this study show that the improved network has higher connectivity and stability.

Articulating China's Science and Technology:Knowledge Collaboration Networks Within and Beyond the Yangtze River Delta Megalopolis in China

In this paper, we reconsider the defining but often overlooked ‘hinge' function of megalopolises by analyzing how megalopolises have articulated national and international urban systems in the context of a globalizing knowledge economy. Taking the case of China's Yangtze River Delta(YRD) region, we particularly focus on knowledge circulation within and beyond the YRD region by analyzing the pattern and process of knowledge collaboration at different geographical scales during the 2004–2014 period. Results show that the structure of scientific knowledge collaboration as reflected by co-publications has been strongest at the national scale whereas that of technological knowledge collaboration as measured by co-patents has been strongest at the global scale. Despite this difference, the structure of both scientific and technological knowledge collaboration has been functionally polycentric at the megalopolitan scale but become less so at the national and global scales. The ‘globally connected but locally disconnected' pattern of Shanghai's external knowledge collaboration suggests that the gateway role of the YRD megalopolis in promoting knowledge collaboration at different geographical scales will take time before it is fully realized.

Method for Incorporation of Controllability in Heat Exchanger Network Synthesis by Integrating Mathematical Programming and Knowledge Engineering

A method for incorporation of controlling the heat exchanger networks with or without splits is proposed by integrating mathemati-cal programming and knowledge engineering. The simultaneous optimal mathematical model is established. This method can be practically used in the integration of large-scale heat exchanger networks, not only to synthesize automatically but also to satisfy the requirement of struc-tural controllability with more objective human intervention.

The development of a knowledge base in an expert system based on the four-layer perceptron neural network

Owing to continuous production lines with large amount of consecutive controls, various control signals and huge logistic relations, this paper introduced the methods and principles of the development of knowledge base in a fault diagnosis expert system that was based on machine learning by the four-layer perceptron neural network. An example was presented. By combining differential function with not differential function and back propagation of error with back propagation of expectation, the four-layer perceptron neural network was established. And it was good for solving such a bottleneck problem in knowledge acquisition in expert system and enhancing real-time on-line diagnosis. A method of synthetic back propagation was designed, which broke the limit to non-differentiable function in BP neural network.

Structure of Chinese City Network as Driven by Technological Knowledge Flows

Based on patent cooperation data,this study used a range of city network analysis approaches in order to explore the structure of the Chinese city network which is driven by technological knowledge flows.The results revealed the spatial structure,composition structure,hierarchical structure,group structure,and control structure of Chinese city network,as well as its dynamic factors.The major findings are:1) the spatial pattern presents a diamond structure,in which Wuhan is the central city;2) although the invention patent knowledge network is the main part of the broader inter-city innovative cooperation network,it is weaker than the utility model patent;3) as the senior level cities,Beijing,Shanghai and the cities in the Zhujiang(Pearl) River Delta Region show a strong capability of both spreading and controlling technological knowledge;4) whilst a national technology alliance has preliminarily formed,regional alliances have not been adequately established;5) even though the cooperation level amongst weak connection cities is not high,such cities still play an important role in the network as a result of their location within ′structural holes′ in the network;and 6) the major driving forces facilitating inter-city technological cooperation are geographical proximity,hierarchical proximity and technological proximity.

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.

A Location Privacy Preserving Solution to Resist Passive and Active Attacks in VANET

Existing location privacy- preserving methods, without a trusted third party, cannot resist conspiracy attacks and active attacks. This paper proposes a novel solution for location based service （LBS） in vehicular ad hoc network （VANET）. Firstly, the relationship among anonymity degree, expected company area and vehicle density is discussed. Then, a companion set F is set up by k neighbor vehicles. Based on secure multi-party computation, each vehicle in V can compute the centroid, not revealing its location to each other. The centroid as a cloaking location is sent to LBS provider （P） and P returns a point of interest （POI）. Due to a distributed secret sharing structure, P cannot obtain the positions of non-complicity vehicles by colluding with multiple internal vehicles. To detect fake data from dishonest vehicles, zero knowledge proof is adopted. Comparing with other related methods, our solution can resist passive and active attacks from internal and external nodes. It provides strong privacy protection for LBS in VANET.

Protocol Based Approach for Tacit to Explicit Knowledge Conversion

In the knowledge management domain, the conversion of tacit knowledge to explicit knowledge is critical because it is a prerequisite to the knowledge amplification process wherein knowledge becomes part of an organization＇s knowledge network. Although codified knowledge and its capture is commonplace, tacit knowledge has up until recent years proved elusive in its inclusion within the organization＇s knowledge base. In this paper, the conversion process has been dealt with the help of protocols. It is learned that while structure may significantly improve the tacit to explicit conversion process, it also may matter how the structure is employed. It is anticipated that eventual successful modeling of such knowledge will ultimately be undertaken in several organizations with a view to improving information capture and transference.

A POWER SYSTEM INTELLIGENT TRAINING SIMULATOR BASED ON TRANSPUTER

The simulator is a combination of computational functions describing physical system, distributed rule and knowledge bases, and a reasoning machine, all executing in parallel. The hardware,comprising two levels of multiprocessor network-- a T800 transputer and STD--BUS computer systems--and analogue and I/O boards, has been used successfully to train and simulate a 100 MW power system at a low cost. The system has wide applications in industry.

＂A Raft in the Stormy Sea＂： New Roles, New ＂Dresses＂ Operating in ＆ for Business Networks

This paper aims to discuss the development and functioning conditions of business networks. After recalling the main characteristics of post-fordistic environment and comparing it to a ＂stormy sea＂ （section one） of the paper focuses on the idea of networks described as ＂rafts＂ useful to firms to build their own competitive advantages. In fact, while theoretical knowledge is not so valuable because everybody can have it, practical and contextual knowledge is specific and therefore it can be defended. The development of a contextual knowledge is feasible if the firm chooses among all the possible alternatives. Subsequently in section two, it shows how fordistic principles eliminate space, reduce time, and increase the speed of communication among individuals and as entering a network has become a necessity as it allows a firm to obtain competitive advantages. The greatest benefit is the chance to share the task of creating new knowledge among different members. In section three it is discussed if navigation in the post-fordistic stormy sea could take advantage from the existence of a more certain regulation. It is necessary to underline that positive law is not a post-fordistic tool. There is no satisfactory detailed law regarding ideas, knowledge, and know-how, by now. Therefore, it is not possible to rely on a specific regulation framework to protect knowledge found on the network. In conclusion in section four, the work discusses how single organizations need to reach the ＂raft＂--which is the network--through the idea of sharing learning and distinguishing elements necessary to survive in the stormy sea post-Fordism environment. Lastly, section five would be analyzed a public institution--Milan Chamber of Commerce--which has ＂changed its dress＂ to more effectively perform its support role to firms.

Study on the Innovative Design of Graphic Design

With the advent of the informatian age, people are working to build a new knowledge network, knowledge of the past gradually pieced together again. The new knowledge network includes not only advanced science and technology, but also includes the historical and cultural value, emotion and sense of innovation. Graphic design is a spiritual and material reality and artistic, aesthetic and practical disciplines integrated with each other. Always take the old approach to their creative confined in a narrow space, and this will inevitably lead to failure. Graphic design must rely on the sense of innovation, combined with the image of abstract thinking; ideas can really create unique designs. Therefore, to enhance training in graphic design innovative design capabilities, innovation and the development of graphic design is an important issue. In this paper, graphic design requirements and the role of innovation capacity will be explared, and the method of application of proposed innovative thinking in graphic design process will be provided.

A RBF Network Learning Scheme Using Immune Algorithm Based on Information Entropy

A hybrid learning method combining immune algorithm and least square method is proposed to design the radial basis function(RBF) networks. The immune algorithm based on information entropy is used to determine the structure and parameters of RBF nonlinear hidden layer, and weights of RBF linear output layer are computed with least square method. By introducing the diversity control and immune memory mechanism, the algorithm improves the efficiency and overcomes the immature problem in genetic algorithm. Computer simulations demonstrate that the RBF networks designed in this method have fast convergence speed with good performances.