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To obtain professional entity information including expert research fields in academic papers and provide theoretical references for academic paper or technology project review experts, an entity recognition model based on RoBERTa-wwm is proposed to identify professional entities in academic papers in the field of computer science. First, with the reference of the available experts' basic information table, the abstract data of these experts' academic papers are obtained through the advanced search of the China National Knowledge Infrastructure ( CNKI) and crawler technology. Next, the abstract data are manually annotated and the RoBERTa-wwm pre-training model is employed to obtain character vectors with semantic features as inputs for downstream models. Finally, the semantic character vectors are put into the BiLSTM-CRF model to identify professional entity recognition in the text. The experiments show the proposed model achieves better results in the self-labeled dataset. The F1 score of model reaches 89.94%, higher than all other comparison models in the experiment, demonstrating its excellent ability to identify professional entities. [ABSTRACT FROM AUTHOR]

In recent decades, causal inference has been a significant research topic in various fields, including statistics, computer science, education, public policy, and economics. Most causal inference methods focus on the analysis of sample observational data and text corpora. However, with the emergence of various knowledge graphs and large language models, causal inference tailored to knowledge graphs and large models has gradually become a research hotspot. In this paper, different causal inference methods are classified based on their orientation towards sample observational data, text data, knowledge graphs, and large language models. Within each classification, this paper provides a detailed analysis of classical research works, including their problem definitions, solution methods, contributions, and limitations. Additionally, this paper places particular emphasis on discussing recent advancements in the integration of causal inference methods with knowledge graphs and large language models. Various causal inference methods are analyzed and compared from the perspectives of efficiency and cost, and specific applications of knowledge graphs and large language models in causal inference tasks are summarized. Finally, future development directions of causal inference in combination with knowledge graphs and large models are prospected. [ABSTRACT FROM AUTHOR]

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Copyright of Guangdong Architecture Civil Engineering is the property of Guangdong Architecture Civil Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Image & Graphics is the property of Editorial Office of Journal of Image & Graphics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Based on the theory of conceptual metaphor, this paper discusses the formation and characteristics of conceptual metaphor in the computer field and its influence on human thinking. The functions of the human brain and the expressions and related concepts used to describe these functions are applied to the computer, thus conceptual metaphor concerning the computer come into being. Conceptual metaphor in the field of computer, which is not only of universality but also of systematization, reflects human’s cognition of the computer and also influences human’s thinking mode to cognize the world. The study of this kind of conceptual metaphor can deepen our understanding of computer science and widen the research field of metaphor cognitive function as well. [ABSTRACT FROM AUTHOR]

Aiming at the disadvantages in existing data gathering schemes, this paper proposed a clustering data gathering scheme based on the hybrid CS. Firstly, it divided the network into multi-clusters, and sent the original data of nodes directly to the cluster head via the shortest path route. Then the cluster head aggregated the received data using CS and forwarded them to the sink via a backbone routing tree. The minimizing the number of transmission as the optimal objective among them, this paper theoretically analyzed the relationship between the size of clusters and number of transmissions in the hybrid CS method, and it obtained the optimal size of clusters that led to minimum number of transmissions. Furthermore, it modeled the intra-cluster data transmission as the K-median problem, and modeled the inter-cluster data transmission as the Steiner tree problem, and proposed the centralized and distributed algorithms to solve them. The simulation results show that the proposed scheme is effective, and is better than the traditional methods in terms of reducing the number of data transmission. [ABSTRACT FROM AUTHOR]

For the purpose of assessing vulnerabilities more effectively, from the vulnerability availability, this paper analyzed the shortcomings of common vulnerability scoring system(CVSS) as the evaluation indicators based on the vulnerability correlation assessment method. Meanwhile, on the basis of the improved CVSS evaluation indicators, this paper put forward a more sensible vulnerability availability evaluation system and promoted the original vulnerability assessment method. This method also mines its own characteristics of vulnerability effectively, assesses vulnerability scientifically and verifies its rationality and validity by experiments. [ABSTRACT FROM AUTHOR]

In view of that the rational exchange protocol was a dynamic game model, under complete imperfect information dynamic game, this paper introduced the maximum entropy principle to solve the problem of strategy behavior inference of rational party. Based on information entropy, this paper extended a rational exchange protocols model in which a new fairness description was given combined with a desired payoff function and an expected equilibrium. In addition, it constructed a new rational exchange protocol based on the maximum entropy principle, which was proved secure and fair. Meanwhile, made analysis of the exchange process by game tree. Results show that the proposed protocol can achieve expected equilibrium. Without the participation of the trusted third party, the protocol can achieve rational fairness and be beautifully adapted to the real environment. [ABSTRACT FROM AUTHOR]

According to the virtualization technology of cloud computing, it can solve the problems that the electronic cash systems exist leakage of privacy, non-standard transactions and high cost in the traditional network. In the existing work, considering merchants and customers used the same bank to restrict the widespread use of electronic cash in a certain degree, the paper presented an multi-bank electronic cash payment scheme for trusted cloud platform based on TPM. Considering the efficiency and security from the electronic cash payment of the scheme, the scheme used the group signature and elliptic curve algorithm ECC to improve the execution efficiency of the protocol, and used the privacy protection and remote attestation function of TPM to achieve security. Finally, the paper analyzed the safety and efficiency of the scheme. [ABSTRACT FROM AUTHOR]

Direction is a key factor of accessibility research. Therefore, this paper proposed a calculation method on space-time accessibility considering the direction of travel. First, it constructed an experiential hierarchy of road network using experiential taxi routes. Second, it used the Dijkstra algorithm based on hierarchical road network to compute the travel time between each OD, and then used a grid method and inverse distance weighting method to render the isochrones maps of Guangzhou CBD. Finally, the paper analyzed the accessibility of it in different direction of travel and different time periods. The experimental results prove that accessibility in different direction, especially in peak time, is quite different. [ABSTRACT FROM AUTHOR]

Aim at the problem for how to analyze the propensity to spread of shortage of supplies in emergency logistics decision support system, this paper proposed a new model to study the propensity to spread of shortage of supplies for emergency logistics network. This paper, by the mechanism of viral spreading and introducing the parameter of time "t", it constructed SI-SIRS ( susceptible infective and susceptible infective recover susceptible) model to analyze the scale-free network which included 61 nodes. Case analysis shows that SIRS effectively depicts the spread behavior of shortage of supplies in emergency logistics network. Propensities to spread of shortage of supplies are effected by node self-spread ability, network topology, individual nodes differences and responding mechanism of emergency logistics. [ABSTRACT FROM AUTHOR]

In order to realize intelligence management of guide sign system, this paper proposed an algorithm for deploying guide signs using guide sign data model from the perspective of road guiding levels. The algorithm took road intersection as research object, and guide sign information was classified into two categories, namely, connection signs and direction signs according to the relationship of guide signs information and road network topology. Moreover, the paper illustrated the selection principles of directional signs based on road guiding levels, and constructed deployment algorithm model for directional signs. Finally, a case study was conducted: the deployment model was tested in Guangzhou Higher Education Mega Center. The result revealed that the data model could support the automatic deployment, analysis and evaluation for guide signs. [ABSTRACT FROM AUTHOR]

Internet of Things or cyber-physical systems provide a new challenge for formal modeling methods related to the aspect of physical elements such as location and time. Recently, this paper introduced a specification language called STeC to stress the spatio-temporal consistency for real-time systems. The operational and denotational semantics of and tool set related to this language have been given. The aim of this paper was to establish a STeC to Stateflow automatic transformation system and to propose a simulation and verification approach based on this transformation system. It firstly gave a formal model for an object system in STeC language, and then set up a real-time monitoring simulation model using Simulink. After that, it presented a verification approach for the system safety property based on Checkmate. Finally, it gave a case about Jinghu Gaotie (high speed train) running timetable to show that the proposed approach is effect and usable. [ABSTRACT FROM AUTHOR]

Community structure is one of the most important and basic topologic properties of complex network. The rational division of community structure in complex network is the main purpose of the complex network's community division research. This paper mainly researched the division of community structure in complex network based on the theory of supernetwork and standardized degree centrality. Based on the lack of GN algorithm, this paper proposed a new comprehensive algorithm to divide community structure from the perspective of supernetwork. Finally, the new comprehensive algorithm is illustrated through examples. [ABSTRACT FROM AUTHOR]

In order to promote the feasibility of the construction of cubic splines, this paper presented a novel pseudoinverse-based construction method (PCM) to construct the cubic spline function effectively. Without using endpoint-constraint conditions, this method obtained the solution of the second-order derivatives of the cubic spline that was closest to the origin, namely the minimum norm solution. Theoretical analysis and numerical experiments highlight the efficacy of the PCM. For better understanding, it further studied and investigated the characteristics of various construction methods. In this way, it provided guidelines for choosing suitable methods to construct cubic splines in practical applications of engineering calculation. [ABSTRACT FROM AUTHOR]

The paper introduce the debug module of ColdFire family MCUs, put emphasis on the BDM debug principle, then give the design method and schematic of BDM. This paper outlines the function of BDM debug system, and the in-depth analysis about the basic debug order is given. [ABSTRACT FROM AUTHOR]

Practice teaching is an essential link of university education, and provides a powerful support of academic teaching. Building outside-school practice bases and further improving university-enterprise cooperation patterns of cooperative education are effective approaches for training the practice ability, and strongly guarantee the employment and entrepreneurship for students. In this paper, we summarize the founding process of outside-school practice bases of School of Computer Science and Engineering of Dalian Minzu University, analyze the problems existing in outside-school practice teaching, and propose a method for further deepening practice teaching, which has certain reference significance on strengthening the cooperative education and improving the practice training ability of students in universities. [ABSTRACT FROM AUTHOR]

Generalized computation theories include algorithms, computational complexity theory, computability theory, automata theory, and formal language theory. This paper discusses several typical problems in computation theory(computability theory and complexity theory)and reveals the importance of computational thinking in practical teaching. We elaborate the relation between computation theory and computer science from different perspectives. And then we describe Turing machine model and reveals the essential relation between Turing machine model and computational thinking. In addition, we discuss time complexity and space complexity in computer science, explain approximation algorithm, using packing problem examples. Finally, we emphasize the importance of computation theory in computer science education. [ABSTRACT FROM AUTHOR]

Aiming at the partial comparatively optimum scheduling result caused by the singleness of priority selection in the existing task scheduling algorithms, starting from the global comparatively optimum, this paper proposed a static task scheduling algorithm named HGCOTS, which based on the stratification first and then branching determining priority. HGCOTS algorithm took large communication among tasks and redundancy tasks for scheduling efficiency of heterogeneous CMP into account, the combination of inserting and task duplication technique reduced the communication overhead among tasks greatly, besides, deleting redundancy tasks improved the task scheduling efficiency significantly. The simulation experiment based on randomly generated graphs shows that the new algorithm has a shorter scheduling length compared with other algorithms. [ABSTRACT FROM AUTHOR]

In order to solve the natural images problems of widely types, complex instruction and low classification accuracy, this paper proposed a new classification method for natural images based on feature-weighted K-nearest neighbors. By analyzing the impact of different features on natural images classification, using genetic algorithm to get a set of optimal classification weight vector, weighted textural features and color features based on that data. Finally, it used the adaptive feature-weighted K-nearest neighbors to classify the natural images. The experimental results show that in the constraint of demand classification accuracy and low time complexity that the user given, this algorithm can classify the natural images with high speed and high-precision. The adaptive feature-weighted K-nearest neighbors classification method is generally apply for the variety of natural images, and can improve the classification performance effectively for natural images. [ABSTRACT FROM AUTHOR]

In order to improve the accuracy of control chart patterns recognition (CCPR),this paper proposed a new CCPR method, which extracted shape features from control chart pattern to make them fused with the raw features, i. e. the raw data of control chart pattern, and then based on that to execute pattern classification with support vector machine (SVM). The fusion of features effectively enhanced the discrimination between different patterns by means of strengthening the local geometrical properties of confusable patterns with shape features as well as keeping the global property information contained in raw features of each control chart pattern. Moreover, the used of SVM as classifier ensures this method a well recognition performance even under a condition of high dimension feature and small training sample number. The results of simulation experiments demonstrate that the proposed method can get an improved recognition accuracy compared with several other CCPR methods based on shape features. [ABSTRACT FROM AUTHOR]

This paper proposed a hierarchical evaluation method to quantitative evaluate vulnerability attributes to improve vulnerability risk evaluation process. It developed a evaluation system based on the analytic hierarchy process to obtain the factor weights. And it quantified the vulnerability severity based on the fuzzy comprehensive evaluation to give the severity rank, evaluated vulnerability by the combining of exploitability attributes and safety influence attributes. Experimental results show that this method can evaluate the vulnerability severity more accurately. [ABSTRACT FROM AUTHOR]

Various types of network security devices generated a large number of redundant alarm information with the high rate of false alarms. Alarm information is very trivial which is more difficult to analysis and understand the alarm. In order to research this problem, this paper proposed an alert aggregation method for multi-source heterogeneous alarm. By analyzing alarm type, source IP, destination IP, destination port and time interval, it summed up four rules, dynamically updated the time interval threshold and improved degree of accuracy. The experimental results show that this method can efficiently reduce the number of heterogeneous alarm information, get simplified super alarm data, and realize the real-time processing ability of the alarm information. [ABSTRACT FROM AUTHOR]

This paper proposed a labeling to data stream binding method independent of the contents of the packet, which based on packet delay modulation, and introducing the packet inter-arrival delay as the new labeling vector. The method used Himming code to achieve the label error control, designing the data packet randomized blocks, and modulated the packet delay time according to the label binding rules, then realized the implicit binding of security label to data stream. Based on this method, it solved the targeted attack problems caused by explicit binding method and its inflexibility. Theoretical analysis and experimental results demonstrate that the proposed method is robust against the network random timing perturbation and safety the binding security label when is transmitted in the network. [ABSTRACT FROM AUTHOR]

The ranges of state variable value of transition system are large, and the state space of system transition, but the transitions of the system are often unpredictable. This paper defined the concepts: initial safety states, safety transition condition, safety state, safety action, safety run and safety transition system, and proved the all states in safety transition system were safe. Then it used it to remold the network transition system, and changed it a safety transition system. [ABSTRACT FROM AUTHOR]

Courier tracking number stolen and express list information are not protected carefully that may cause privacy leakage. So this paper proposed a new K-anonymity model to protect express information. Unlike most anonymity methods, this method anonymized data by randomly breaking links among attribute values in records. By data randomization, this method maintained statistical relations among data to preserve knowledge, whereas in most anonymization methods, knowledge was lost. Further more, it proposed the algorithm for extra privacy protection to tackle the situation where the user's prior knowledge of original data may cause privacy leakage. Simulation results show that the new K-anonymity method can enhance privacy protection and improve the accuracy of the knowledge protection. [ABSTRACT FROM AUTHOR]

To detect malware such as bot and trojan, this paper proposed a method based on inherent activities of compromised hosts. This method identified suspicious network traffic through persistent arithmetic that measured if hosts had temporal regularity when communicating with other hosts, and analyzed suspicious network traffic through rules of user driven activities and occurring moments to detect compromised hosts. The results show that the system can accurately detect compromised hosts with low error rates. [ABSTRACT FROM AUTHOR]

The known certificateless signcryption schemes have many problems, for example, lack of security, low computational cost and so on. This paper proposed a new secure certificateless signcryption scheme without pairings, which was based on Sharmila's. And it was provably secure in the random oracle model ( ROM). The proposed scheme did no use of pairing and exponentation. And compared with the most efficient scheme, the proposed one just needs 2 more point multiplications under the secure circumstance. [ABSTRACT FROM AUTHOR]

This paper proposed a multi-authority attributed based signature scheme based on distributed ABE, which was suitable for distributed system. It compared with traditional schemes, our scheme allowed an arbitrary number of authorities to independently maintain attributes and distribute secret attribute keys. The master authority was responsible for the distribution of secret user keys, without need to supervise each attribute authority. Attribute authorities were responsible to verify whether a user is eligible of a specific attribute, and every attribute is associated with a single attribute authority. Our construction was very efficient, as it required only a small amount of pairing operations during sign and verification. Our scheme has a good flexibility, and has a great of practical value in practical applications. [ABSTRACT FROM AUTHOR]

Analyzing the user behavior is of great importance to the management and control of network users. User behavior, which is actually s set of data exchanges, is ultimately displayed as traffic flow, showing regularity along time. This paper explored this regularity through studying the timing relationship between traffic flows, and proposed a novel user behavior analysis method. The proposed method utilized three steps, which were based on fractal model, improved maximum distance clustering method, and Apriori algorithm for segmentation, clustering, and timing analysis, respectively, to obtain the user behavior regularity from user data exchange. Theoretic analysis and simulation results illustrate that this method can satisfactorily classify the packet sequence and discover the regularity of user transmit behavior without decrypting user information. [ABSTRACT FROM AUTHOR]

In order to research on the connectivity of aeronautical Ad hoc, this paper proposed a method based on the connectivity of single-dimensional airline for the problems of airline routes singleness and the lack of flights. Considering the features of flight delamination and two-way directions, it built an appropriate airplane distribution model, and deduced the mathematical expression which could measure the actual connectivity of single-dimensional airline with the whole idea. Meanwhile, it proved the correctness of theoretical calculation results via experiments. At last, it calculated the connection probability of aeronautical Ad hoc network in parts of Chinese aerospace based on the real flight data. The results show that the connectivity of one-dimensional bidirection flight can meet the requirements of aeronautical Ad hoc network in advantages of the reverse airplanes transitions. [ABSTRACT FROM AUTHOR]

To solve the problems of low efficiency and more redundant messages in unstructured P2P network resources search, this paper proposed an ant colony optimization based on interest factor(IACO). It gave full consideration to the effects of node value of resources search. It introduced node interest factor into traditional ant colony algorithm to adjust the weight relationship of node value and pheromones dynamically in the forward probability calculation, and effectively guided the generation of resources query path. The simulation results show that the proposed algorithm can improve the success significantly rate and to a certain extent can reduce the amount of redundant messages in the network at the same time. [ABSTRACT FROM AUTHOR]

In P2P network, performances of many nodes in Chord algorithm are inconsonant. The problem that nodes leave and join frequently will restrict the performance of system seriously. Therefore, this paper presented grouping improved algorithm based on related degree of information. It introduced the concept of the node information relevant degree in the algorithm, in which the original Chord was adjusted by group on the related degree of information. Then the super group was connected through the super nodes. It selected two super nodes from each group and constitute a super group. In the meantime, every node was increased a counter-clockwise route. Then they could choose the shortest path to find two super nodes in both clockwise and counterclockwise direction. The experiments show that performance and adaptability of system are strengthened by the improved algorithm. The search efficiency of Chord in P2P network is improved. [ABSTRACT FROM AUTHOR]

In order to estimate the original phase of a sinusoidal signal under noisy circumstances precisely, this paper proposed a novel phase estimation method which based on restricted phase unwrapping and Tretter's phase estimation algorithm. Firstly it acquired the coarse estimation of initial phase by using modified segmented DFT estimator. Then an appropriate linear combination of observed phase, by which the ambiguity number of whole cycle restricted in a smaller integer set, was simply unwrapped on the basis of the principle of minimum phase error. Formulas for evaluating the error probability of restricted phase unwrapping and the RMS error of the initial phase estimation with different SNRs and lengths of signal are also presented. Simulation results show that the SNR threshold of restricted phase unwrapping method is much lower than that of common unwrapping methods, and the estimator derived attains the Cramer-Rao lower bound ( CRLB) at high SNR, which has better performance than the segmented DFT estimator developed and the all-phase FFT estimator . For SNR = 5 dB and N = 1023, the RMS error of the initial phase estimation is about 0.9 degrees, and the error probability of restricted phase unwrapping is only about 10-3 orders of magnitude when SNR =0 dB. [ABSTRACT FROM AUTHOR]

In order to solve the defects of retransmission for random network coding, this paper presented a retransmission approach FMWBR based on local random coding parameter which was combined with Fourier matrix and random network coding. A row vector of the Fouier matrix shared with a source node and a receiver node acted as a coding vector and a decoding vector, which ensured the retransmission packets' solvability. The head of retransmission packets only included the number of the row vector in the Fourier matrix. The theoretic analysis shows that TMWBR enhances the security of wireless transmission, improves the robustness of networks and reduces the cost of packets' head. The simulation results indicate that comparing with traditional scheme, the scheme effectively reduces the average number of transmission and the overhead of networks, improves networks' throughput. [ABSTRACT FROM AUTHOR]

Taking advantage of the social network centrality index and considering the social network "small world" characteristic, This paper proposed a CRCR ( centrality-based replica control routing ) algorithm. In the CRCR algorithm, routing was partitioned by intra-community and inter-community routing, thus messages were limited in the community during message transmission in the community; while the inter-community message transmission took the centrality utility to measure the node activity, increased the speed of messages to the destination node. The simulation results illustrate that the CRCR algorithm, compared with classic opportunistic routing algorithm, has a higher message delivery rate, the smaller network overhead and the lower average delivery delay. [ABSTRACT FROM AUTHOR]

This paper proposed an uplink CSI based adaptive pre-repeat GBN-HARQ scheme to solve the problem that the throughput and delay of traditional pre-repeat GBN-ARQ scheme declined greatly at low BER. First, transmitter encoded the data with FEC and obtained different redundant versions. And then, the method adaptively chose the number of redundant versions for retransmission packets according to the uplink CSI, transmitted multiple redundant versions to ensure the reliability of pre-repeat transmission in the poor condition of wireless channel and reduce delay caused by the error in retransmission and it used few redundancies to ensure high throughput in the good condition of wireless channel. Finally, it compared and analysed the throughput for the traditional GBN-ARQ scheme, pre-repeat GBN-ARQ scheme and adaptive pre-repeat GBN-HARQ scheme. The simulation results show the throughput of adaptive pre-repeat GBN-HARQ scheme improves about 0. 1 than traditional GBN-ARQ scheme and about 0. 05 than pre-repeat GBN-ARQ scheme as the BER exceeds 10, that is to say, the uplink CSI based adaptive pre-repeat GBN-HARQ scheme can further guarantee the reliability at high BER. [ABSTRACT FROM AUTHOR]

This paper proposed a novel cognitive radio spectrum sharing scheme, which based on the tradition auction model and group buying auction. Collusion competition model was developed and realized by introducing collusion relationship to competition of secondary users and adopting the group buying auction theory. The mechanism dealt with the relationship between the primary user and the secondary users or the secondary users themselves in cognitive radio networks. It achieved the fast solution of spectrum's optimal price by artificial bee colony optimization algorithm. Simulation results show that the mechanism is able to improve the spectrum auction revenue of primary user while the secondary users can get the opportunities to access the idle spectrum. As a result, the mechanism enhances the efficiency of spectrum utilization in system as well as the fairness of secondary users access the spectrum, and it has a favorable application prospect. [ABSTRACT FROM AUTHOR]

To solve the problems of logistics park logistics resources elements dispersed and logistics services co-allocation, this paper put forward a new logistics park model of logistics services--cloud logistics services. It abstracted all kinds of customer resources and logistics resources of the park into virtual cloud services to establish the cloud service platform, and analysed and designed the system architecture. According to the task environment of the industrial park supply chain operation node to introduce the context-aware analysis model, and set up the dynamic combination and allocation mechanism which faced the park task context adaptive logistics service resources. Related research explored a new path based on the "push strategy" logistics service, which provided personalized and secure and efficient many-to-many logistics service. [ABSTRACT FROM AUTHOR]

Traditional continuous data protection ( CDP) had difficult in selecting the right one from many restore points, could not guarantee consistence of data recovery and could not support transaction-level recovery for the application. This paper suggested an event-based continuous data protection recovery system, and gave the detail design of the three core components including the application-aware model, the application-collaborative model and the event-based recovery view. It implemented the key functions of EBRS in Oracle database environment. Experiment results show that event-based continuous data protection recovery system has the features of supporting fine-grained data recovery, efficient recovery and good data consistence, and has broad application prospects [ABSTRACT FROM AUTHOR]

In order to improve the computational efficiency of PageRank algorithm, this paper proposed a method based on block structure partition, converting the link relation of Web nodes into the relation of net blocks, which would decrease the times of calls about the map and reduce operations, reduced the consumption caused by I/O transmission and improved the computation efficiency. The experiment shows that the proposed method has certain advantages. [ABSTRACT FROM AUTHOR]

People have different understanding about domain knowledge and system goals, and expressed demand for software is not standardized, so that the domain requiremented are often inconsistent and have to be changed frequently. This paper presented a method of domain requirements description based on limited language, by designing the restricted language requirement template to descript domain application needs. Then it checked the legality of vocabulary and matching the sentence patterns to verify the correctness of domain requirement description. And it saved the domain requirement in XML files. Finally it built instances to verify the effectiveness. [ABSTRACT FROM AUTHOR]

Aiming at the problem of ranking keyword search results in relational database based on data graph, this paper presented two factors based results ranking method which combined result's structure weight and content matching. It often used content matching in field of information retrieve. Firstly, it used result's path weight to measure the compact degree among keywords, results could get a rough ranking according that. Then for results with the same structure weight, keyword frequency in information tuple and amount of information that contain keywords were used to further ranking. Experiment and analysis shows that this ranking method can improve result precision by making highly relevant results in front of result set. [ABSTRACT FROM AUTHOR]

This paper proposed an adaptive fault detection method to protect the reliability of cloud system. Firstly, it exacted the cloud metric using the incremental metric search algorithm and the metric space separation technology, which could obtain the best metric for characterizing the cloud behavior and the health status such as the maximal relevance criterion and the minimal redundancy criterion. And then mapped the data point of cloud metric into the kernel space to reduce the dimensionality by using the minimum enclosing sphere formulation. Finally, input the low-dimensional data into the fault detector, which generated a smallest enclose spherical with accommodating data in the kernel space to identify the potential failure. If the fault history could not be obtained, the fault detector would find the other states different from the cloud health status to identify the failure. The cloud operators verified and confirmed the detection results as either true failures or normal states (false alarms). It have implemented a prototype of the fault detection system and conducted experiments in an on-campus cloud computing environment. The experimental results show that the method can achieve more efficient and accurate failure detection than other existing schemes. [ABSTRACT FROM AUTHOR]

Finite-domain representations (FDR) is one of the best methods to compress the size of state space, but it requires building a logic program for each initial state in grounding stage. Unfortunately the number of the possible initial state in conformant planning is always huge. So there will be heavy time and space overhead and even leads to memory overflow. In order to improve the efficiency of the algorithm, this paper designed a new method named IFDR using a single logic program to translate the PPDDL task into grounded one. A logic program consists of a set of facts and a set of rules. The set of facts of the logic program was formed by the atoms in all the possible initial state, and the set of rules was derived from the axiom and operator definitions. The outcomes of comparative experiments validate the accuracy and effectiveness of the new algorithm. [ABSTRACT FROM AUTHOR]

For the heterogeneity problem among ontologies, this paper presented an algorithm based on sub-graph approximate isomorphic here. It was an extension of existing methods in ontology matching. Under the comprehensive application of features such as edit distance and hierarchical relations, it calculated the similarity of graph structures between two ontologies. Lastly, it determined the ontology matching on the condition of sub-graph approximate isomorphism based on the alternately mapping of nodes and arcs in the describing graphs of ontologies. It used an example to demonstrate this ontology matching process and analyzed the time complexity to explain its effectiveness. [ABSTRACT FROM AUTHOR]

This paper proposed the job scheduling algorithm ( ISS) and optimization of dynamic data replication algorithm ( ODHRA) for effectively conducting job scheduling and data replication, and built a program to effectively combine the two algorithms, in order to reduce the execution time of job. First, this program used ISS algorithm to give a comprehensive consideration to the number of jobs waiting in queue, the location of required data for the job and the computing capacity of sites, and used a hierarchical scheduling of network structure with appropriate weighting coefficient to calculate the comprehensive job cost and search for an optimum computing node area; next, it used ODHRA algorithm to analyze data transfer time, storage access latency as well as replica requests that waiting in the storage queue and the distance between nodes, selected the best replica location from many replicas, and then combined replica placement and replica management to reduce the file access time. The simulation results demonstrate that the proposed replication and scheduling strategies give better performance than the other algorithms in the mean execution time of job. [ABSTRACT FROM AUTHOR]

This paper presented a novel ubiquitous knowledge cloud model based on Cloud-P2P network platform, which organized the various types of documents, knowledge orderly together, and took full account of the available resources of network edge. In the premise of protecting user's experience, the model made the tasks about knowledge requirement submitted from users migrate from the network servers to the nodes of network edge. To further improve the users' satisfaction, it proposed a new dynamic complex adaptive quality of service protection mechanism, which provided an effective solution of the problem of server performance bottleneck in peak time existing in the traditional knowledge systems through differentiating the different types of users and setting the threshold of server load. [ABSTRACT FROM AUTHOR]

After analyzing the sparsity of traditional collaborative filtering algorithm and the merit and demerit of current solutions, this paper proposed a collaborative filtering recommendation algorithm based on user characteristics and item attributes which was mainly based on the item-based collaborative algorithm. It predicted the unrated items by analyzing different users' interests to various attributes of items and integrating the attributes of rated items to reduce the sparsity of data sets, and then to improve the accuracy of items' similarity calculation. The experimental results based on MovieLens data set show that the sparsity of extreme data sets can be reduced effectively, to a certain extent the proposed algorithm alleviates the cold starting problem in collaborative filtering algorithm and achieves better prediction accuracy. [ABSTRACT FROM AUTHOR]