The frequent items problem is to process a stream as a stream of items and find all items occurring more than a given fraction of the time. It is one of the most heavily studied problems in data stream mining, dating ...
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The frequent items problem is to process a stream as a stream of items and find all items occurring more than a given fraction of the time. It is one of the most heavily studied problems in data stream mining, dating back to the 1980s. Aiming at higher false positive rate of the Space-Saving algorithm, an LRU-based (Least Recently Used, LRU) improved algorithm with low frequency item pre-eliminated is proposed. Accuracy, stability and adaptability of the improved algorithm have been apparently enhanced. Experimental results indicate that the algorithm can not only be used to find the frequent items, and can be used to estimate the frequency of them precisely. The improved algorithm can be used for online processing both high-speed network packet stream and backbone NetFlow stream.
Rapid HDL is an object oriented software library for scripting the generation of synthesizable Verilog. A fully functional customized microprocessor is defined and automatically synthesized for an FPGA from an XML spe...
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Rapid HDL is an object oriented software library for scripting the generation of synthesizable Verilog. A fully functional customized microprocessor is defined and automatically synthesized for an FPGA from an XML specification file. Using a library of blocks, a microprocessor fabric is defined in XML. Control states specify the connections between the fabric blocks during microprocessor operation. Opcodes sequence the control states and provide a vocabulary for assembly programs, which are compiled and executed on the microprocessor.
Wireless ad hoc networks, especially in the hostile environment, are vulnerable to traffic analysis which allows the adversary to trace the routing messages and the sensitive data packets. Anonymity mechanism in ad ho...
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We will explore a new network transport ”optical flow switching-OFS”, that will enable significant data rate growth and cost-effective scalability of next-generation networks. The talk will concentrate on the tough ...
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We will explore a new network transport ”optical flow switching-OFS”, that will enable significant data rate growth and cost-effective scalability of next-generation networks. The talk will concentrate on the tough network management/control issues of OFS.
Recently, much work have been done on text emotion classification. However, they mainly focused on the emotions expressed by authors instead of the readers. In addition, researches on simplified Chinese text emotion c...
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Recently, much work have been done on text emotion classification. However, they mainly focused on the emotions expressed by authors instead of the readers. In addition, researches on simplified Chinese text emotion classification are extremely less. In this paper, we proposed a simplified Chinese text emotion classification based on readers' emotions. Mass of documents with readers' emotion tag are used as raw text sets, and Vector Space Model is used to represent each document. An emotion dictionary is created semi-automatically by using WordNet to build text vectors. We then train a Support Vector Machine classifier on preprocessed data with four emotion classes, and compared the predicate results with that from Naive Bayes classifier. Experiment results indicate that our approach performs much better on classify accuracy and efficiency.
Replying to F.-J. Müller & A. Schuppert Nature 478, 10.1038/nature10543 (2011) Müller and Schuppert1 describe an exception to our finding2 that roughly 80% of the nodes must be controlled to gain full co...
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Replying to F.-J. Müller & A. Schuppert Nature 478, 10.1038/nature10543 (2011) Müller and Schuppert1 describe an exception to our finding2 that roughly 80% of the nodes must be controlled to gain full control over gene regulatory networks. Yet our result hides subtleties that reveal as much about controllability as about the limits of our current understanding of biological networks.
In this paper, we provide a generalized file replication scheme with a storage load balancing function in unstructured P2P file-sharing networks. The generalized file replication scheme is expressed as a weighted mixt...
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In this paper, we provide a generalized file replication scheme with a storage load balancing function in unstructured P2P file-sharing networks. The generalized file replication scheme is expressed as a weighted mixture of the concepts introduced in existing schemes. A mathematical analysis shows that the system behavior realized by the generalized file replication scheme can be described by a thermal diffusion equation composed of heat, reaction and diffusion terms, the weights of which are controlled by a parameter of the mixing rate. Here, the heat term represents a function to enhance file search performance by making replicas on specific peers. The reaction term represents a function to avoid concentrations of storage loads on specific peers. The diffusion term represents a function to uniform the storage loads among peers. The simulation results show that the generalized file replication scheme enables us to control the trade-off between search and storage load balancing performances extensively and intuitively by controlling the parameter of the mixing rate. In addition, the simulation results show that the generalized file replication scheme can adapt to dynamic P2P file-sharing environments.
Present-day networks are being challenged by dramatic increases in bandwidth demand of emerging applications. We will explore a new transport, "optical flow switching," that will enable significant growth, p...
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Present-day networks are being challenged by dramatic increases in bandwidth demand of emerging applications. We will explore a new transport, "optical flow switching," that will enable significant growth, power-efficiency and cost-effective scalability of next-generation networks.
With the spread use of the computers, a new crime space and method are presented for criminals. Thus computer evidence plays a key part in criminal cases. Traditional computer evidence searches require that the comput...
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With the spread use of the computers, a new crime space and method are presented for criminals. Thus computer evidence plays a key part in criminal cases. Traditional computer evidence searches require that the computer specialists know what is stored in the given computer. Binary-based information flow tracking which concerns the changes of control flow is an effective way to analyze the behavior of a program. The existing systems ignore the modifications of the data flow, which may be also a malicious behavior. Thus the function recognition is introduced to improve the information flow tracking. Function recognition is a helpful technique recognizing the function body from the software binary to analyze the binary code. And that no false positive and no false negative in our experiments strongly proves that our approach is effective.
Rigidity and reflectivity are important properties of objects, identifying these properties is a fundamental problem for many computer vision applications like motion and tracking. In this paper, we extend our previou...
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Rigidity and reflectivity are important properties of objects, identifying these properties is a fundamental problem for many computer vision applications like motion and tracking. In this paper, we extend our previous work to propose a motion analysis based approach for detecting the object's rigidity and reflectivity. This approach consists of two steps. The first step aims to identify object rigidity based on motion estimation and optic flow matching. The second step is to classify specular rigid and diffuse rigid objects using structure from motion and Procrustes analysis. We show how rigid bodies can be detected without knowing any prior motion information by using a mutual information based matching method. In addition, we use a statistic way to set thresholds for rigidity classification. Presented results demonstrate that our approach can efficiently classify the rigidity and reflectivity of an object.
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