Abstract:Recently, ontology learning is emerging as a new hotspot of research in computer science. In this paper the issue of ontology learning is divided into nine sub-issues according to the structured degree (structured, semi-structured, non-structured) of source data and learning objects (concept, relation, axiom) of ontology. The characteristics, major approaches and the latest research progress of the nine sub-issues are summarized. Based on the analysis framework proposed in the paper, existing ontology learning tools are introduced and compared. The problems of current research are discussed, and finally the future directions are pointed out.

Abstract:In recent years, there have been extensive studies and rapid progresses in automatic text categorization, which is one of the hotspots and key techniques in the information retrieval and data mining field. Highlighting the state-of-art challenging issues and research trends for content information processing of Internet and other complex applications, this paper presents a survey on the up-to-date development in text categorization based on machine learning, including model, algorithm and evaluation. It is pointed out that problems such as nonlinearity, skewed data distribution, labeling bottleneck, hierarchical categorization, scalability of algorithms and categorization of Web pages are the key problems to the study of text categorization. Possible solutions to these problems are also discussed respectively. Finally, some future directions of research are given.

Abstract:An efficient digital ink data coding algorithm IWPHSP (integer wavelet packet based hierarchical set partitioned) is proposed in this paper. The algorithm compresses digital ink multi-dimension data losslessly using three approaches: integer wavelet packet transform, hierarchical set partitioned, significant bits combination code and fast adaptive arithmetic code. The experiments show that the IWPHSP algorithm is efficient.

Abstract:Multi-Modality fusion is one of the hottest discussed issues in the current research of medical image processing and it has a deep impact on the cognitive science and clinical treatment. In this paper, an fMRI-constraint equivalent dipole model (FC-ECD) based on ICA is proposed to solve the fusion of fMRI and EEG. The ICA is adopted as a preprocessing step to exclude the noise and select the available ERP components. At the same time, it can provide a prior estimate of the number of dipoles. Then considering the spatial information provided by fMRI, the selected ERP components are localized by FC-ECD model based on an ideal four-sphere head model. Thus it can reduce the computation time dramatically. Finally, the simulation study proves the correctness and validity of the method proposed in the paper and the human study coincides with the physiology fact.

Abstract:Use of structural information and lexicalization are two of the main challenges facing syntactic analysis, and they are investigated in this paper. First, the probabilities of lexical dependencies are obtained by training a large-scale dependency treebank and used to build the lexical model. Second, the governing degree of words is introduced to utilize the structure information. The lexical method overcomes the weakness of POS dependencies in the past work; meanwhile the governing degree of words is helpful to distinguish the syntactic structures so some ill-formed structures are avoided. Finally, the paper shows a good experimental result of around 74% accuracy on the test set that consists of 4000 sentences.

Abstract:Enlightened by the behaviors of gregarious ant colonies, an artificial ant movement (AM) model and an adaptive ant clustering (AAC) algorithm for this model are presented. In the algorithm, each ant is treated as an agent to represent a data object. In the AM model, each ant has two states: sleeping state and active state. In the algorithm AAC, the ant’s state is controlled by both a function of the ant’s fitness to the environment it locates and a probability function for the ants becoming active. By moving dynamically, the ants form different subgroups adaptively, and consequently the whole ant group dynamically self-organizes into distinctive and independent subgroups within which highly similar ants are closely connected. The result of data objects clustering is therefore achieved. This paper also present a method to adaptively update the parameters and the ants’ local movement strategies which greatly improve the speed and the quality of clustering. Experimental results show that the AAC algorithm on the AM model is much superior to other ant clustering methods such as BM and LF in terms of computational cost, speed and quality. It is adaptive, robust and efficient, and achieves high autonomy, simplicity and efficiency. It is suitable for solving high dimensional and complicated clustering problems.

Abstract:The navigation problem of multi-robot movement in a complex and unknown environment is studied in the paper. A new algorithm, ants navigation algorithm, is presented. At the start the method maps the global targets onto the area near the border of the robot’s eyeshot, and takes them as the local targets. Then two groups of ants will be cooperating to complete the search for the local optimal path in the robot’s eyeshot. Based on these configurations, the algorithm can predict possible collision with other robots and execute subsequent avoidance plans. The local search will be executed by the algorithm repetitively whenever the robot progresses a step. So, the path of the robot will be altered dynamically, which makes the robot move on the global optimal path to the ending node. The simulation results indicate that the optimal path, which the robot moves on, can lead the robot to reach the end safely even in complicated geographical environment. The effect is very satisfactory.

Abstract:This paper presents a new framework for spatiotemporal alignment of two video sequences. It proposes Intra-video and inter-video matching strategy for spatial alignment; modifies Dynamic Time Warping for temporal alignment. Intra-video matching tracks feature points and binds them together. Contextual inter-video matching uses track correspondences to provide initial feature correspondences for inter-video frame matching and updates track correspondences using frame-matching results. The proposed matching strategy makes best use of coherency of source videos and improves coherency of aligned video, stability and efficiency of alignment. The Modified Dynamic Time Warping establishes frame correspondences by minimizing global differences between them, keeps temporal order of frames, and handles nonlinear misalignment of videos. The proposed method can successfully align videos viewing different events recorded by independently moving cameras. Experimental results and comparison show that great improvements on stability and efficiency of video matching together with coherency of aligned video are reached.

Abstract:Texture segmentation is a typical difficult problem in image processing. This paper presents a new textural oscillatory feature based on image decomposition. The oscillatory feature together with other textural features based on the structure tensor and nonlinear diffusion constructs a 5 dimensional textural feature space. The last result can be obtained by segmenting the feature space using level set and non-parametric active contours technology. The validity of the method in this paper is proved by different texture segmentation tests.

Abstract:Gradient vector flow (GVF) snake shows high performance at capture-range enlarging and boundary concavity convergence, however, the initial contours encounter a so-called critical point problem (CPP). The initial contour must contain the critical points inside the object and exclude those outside the object, otherwise, the final result would be far from the expected. This paper investigates the CPP of the GVF snake and points out that, serving as an external force field for snake models, gradient vector flow could be effective only under some restrictions. Also, it is proved that the theoretical foundation, the Navier-Stokes equation for viscous fluid flow, for the solution to this CPP in literatures is incorrect. Finally, an empirical solution to the CPP is presented and its performance is validated by experiments.

Abstract:The inter-domain routing system is a complex macrosystem just like the Internet, and the self-organization theory is the efficient utility for studying complex system. This paper analyzes the intrinsic rules and behavioral exhibitions of inter-domain routing system from the view of self-organization, and evaluates the mending methods to BGP protocol for improving the scalability, convergence, stability and security of inter-domain routing system, in order to extract good experience and find out the deficiency. Based on the development forecast of BGP, the rules and techniques of using the self-organization character to solve the inter-domain system problems are presented.

Abstract:Exchange of attribute credentials is an important means to establish mutual trust between strangers who wish to share resources or conduct business transactions. Automated trust negotiation (ATN) is an approach to regulate the exchange of sensitive credentials by using access control policies, so as to protect sensitive credentials, policies and private privacy, and to improve negotiation efficiency and successful negotiation establishment rate. A detailed review of the research on ATN is presented based on the survey and classification of the current negotiation techniques. According to the precise investigation on ATN, the pitfalls of ATN are pointed out and the reasonable rules that ATN should observe are put forward, meanwhile, the development trend for ATN is proposed.

Abstract:Nowadays, many high speed Internet applications require high speed multidimensional packet classification algorithms. Based on the uniqueness of Network Processor, this paper presents a multidimensional classification algorithm—AM-Trie (asymmetrical multi-bit trie). AM-Trie is a high speed, parallel and scalable algorithm and very fit for the “multi-thread and multi-core” feature of the Network Processor. A heuristic field division algorithm is also presented, and it is proved theoretically that it can find out the minimum storage cost solution when the height of the AM-Tire is given. Finally, a prototype is implemented based on Intel IXP 2400 Network Processor. The performance testing result shows that AM-Trie is a high-speed and scalable algorithm; the throughput of the whole system is influenced little by the size of rules and it can reach 2.5 Gbps wire speed.

Abstract:The existing TCP/AQM model does not consider the impact of unresponsive flows to AQM algorithms, which contributes to about 70%～80% of the Internet flows. It is important to analysze the performance of AQM algorithms taking into account of the unresponsive flows. An extended GI/M/1/N queueing system is established by means of embedding the AQM mechanism into the standard GI/M/1/N queueing system. Based on the extended GI/M/1/N queuing system and self-similar traffic of the Internet, three classical AQM algorithms (TD, RED and GRED) are evaluated for the unresponsive flows. The analytic results are consistent with those obtained from NS2 simulations, which means the extended queueing system can be used to assess the performance of AQM algorithms with the unresponsive flows.

Abstract:Burst detection over data streams has been attracting more and more attention from academic and industry communities due to its broad potential applications in venture analysis, network monitoring, trend analysis and so on. This paper aims at detecting bursts of both monotonic and non-monotonic aggregates over multiple windows in data streams. A burst detection algorithm through building monotonic search space based on fractal technique is proposed. First, the piecewise fractal model on data stream is introduced, and then based on this model the algorithm for detecting bursts is presented. The proposed algorithm can decrease the time complexity from O(m) to O(logm), where m is the number of sliding windows being detected. Two novel piecewise fractal models can model the self-similarity and compress data streams with high accuracy. Theoretical analysis and experimental results show that this algorithm can achieve a higher precision with less space and time complexity as compared with the existing methods, and it could be concluded that the proposed algorithm is suitable for burst detection over data streams.

Abstract:Access authentication is important to the deployment and application of mobile IPv6 network, and Authentication in handover procedure will reduce handover performance in mobile IPv6 network. However, many studies for the access authentication in mobile IPv6 network ignore the effect of authentication in handover procedure. Furthermore, many certificate-based authentication schemes are not fit for the wireless mobile environment. To solve these drawbacks, a fast mutual authentication mechanism using Identity-based signature in mobile IPv6 network is proposed. The identity-based signature scheme uses NAI (network access identifier) as public key and simplifies the key management in wireless mobile environment, so it can resolve the deficiency in PKI-based authentication mechanism. An effective combination of the fast handover and authentication can minimize the additional load resulting from authentication in mobile procedure. Performance analysis results show that the proposed mechanism is more efficient than other schemes.

Abstract:Active queue management (AQM) is a very active research area in networking. As a complementary mechanism to the congestion control of end-to-end systems, AQM, used on the intermediate nodes, can provide high throughputs for routers and control the queue length effectively at the same time. Based on a model of TCP and AQM, a new PID controller is designed analytically using H∞ optimal control theory in this paper. The specialty of this controller is that a single parameter tuning method is proposed, through which the nominal performance and robust performance can be adjusted monotonically to achieve the trade-off. The performance of the controller is verified and compared with other methods using NS simulations. The result shows the advantages of the proposed PID controller.

Abstract:A call admission control (CAC) scheme used in hierarchical mobile IPv6 (HMIPv6) network is proposed, which solves the ideal call number of each cell adaptively to maximize system’s profits, under the restriction of system’s overload probability and capacity and in terms of hosts’ mobility characteristics and call characteristics. The CAC threshold of each cell used in making decisions of accepting or rejecting a new call by network is solved by establishing a Markov model in HMIPv6 network, which can make system’s call number up to the ideal value. Simulation analyzes the factors affecting the optimal regional size, providing a reference for designing a dynamic regional mobility management scheme. The simulation analyses reveal that with the increase of calls’ handoff probability and average duration time, the optimal regional size increases while the regional ideal call number decreases; and with the restriction of overload probability relaxes, the new call blocking probability (CBP) comes down while the handoff dropping probability (HDP) goes up. Finally, a performance comparison result between the proposed scheme and the mobile IP reservation (MIR) scheme demonstrates that the average values of CBP and HDP in the proposed scheme are lower than those in MIR during 2000 simulation intervals, which means the optimization is realized.

Abstract:J.A.Solinas suggested an optimal signed binary representation for pairs of integers, which is called a Joint Sparse Form (JSF). JSF is at most one bit longer than the binary expansion of the larger of the two integers, and the average joint Hamming density among Joint Sparse Form representations is 1/2. This paper extends the Joint Sparse Form by using a window method, namely a new representations, for pairs of integers, which is called Width-3 Joint Sparse Form (JSF₃). The representation is at most one bit longer than the binary expansion of the larger of the two integers, and the average joint Hamming density is 19/52. So, computing the form of uP+vQ by using JSF₃ is almost 9% faster than that by using JSF.

Abstract:As a novel information acquiring and processing technology, compared to other traditional sensor networks, multimedia sensor networks pay more attention to the information-intensive data (e.g. audio, video, image). Potential applications of multimedia sensor networks span a wide spectrum from military to industrial, from commercial to environmental monitoring. This paper introduces the concept and characteristics of multimedia sensor networks, and discusses the technical challenges in this field. In particular, this paper summarizes the current research progresses. Finally, the open research problems are also pointed out. Multimedia sensor networks discussed in this paper is a novel conceptual system; and many issues need to be solved. The research on this topic is with great theoretical and practical value.