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With the increasingly importance of early traffic recognition, early stage identification has drawn many researchers interests in recent years. In this paper, we propose packet inter arrival time (IAT), which is an effective feature for early stage application identification. In order to validate the effectiveness, the five classical classifiers and crossover-validation are applied to our experiment...
Change data capture (CDC) is an approach to data integration that is used to determine and track the data that has changed so that action can be taken using the change data. However, the state of art of change data capture (CDC) in the context of document-oriented NoSQL databases is not mature. Therefore, it is urgent to require a NoSQL CDC solution. Although some manufacturers of NoSQL databases...
Background Many therapies are commonly used to help treat irritable bowel syndrome (IBS), including pharmacological and non-pharmacological approaches. However, there is a lack of direct evidence to help the clinicians make a decision. Objectives The aim of this review is to determine whether one of the approaches is more benefit than any of the others for the treatment of IBS through adjusted indirect...
Service management is becoming more and more important within the area of IT management. How to efficiently manage and organize service in complicated IT service environments with frequent changes is a challenging issue. IT service and the related information from different sources are characterized as diverse, incomplete, heterogeneous, and geographically distributed. It is hard to consume these...
Fault localization is a challenging task in domain specific data mining. Most existing works focus on call graph that can find bugs which are associated with control flow. However, there are a lot of bugs related to data flow. In this paper, we presented a data dependency graph in fault localization. The approach at first analyzes the execution of the test suites dynamically, then derives the data...
It is a problem in application-oriented personnel education that students are hard to apply their knowledge learning from classes. Problem-based learning (PBL) is now a widespread method which can help students learn to apply knowledge. But the teaching condition with limited resources is a big obstruction when using PBL in the undergraduate curriculum. Taking into account this problem, a problem-based...
As an important technique in modern sociology, social network analysis has gained a lot of attention from many disciplines, and been used as important complements to traditional statistics and data analysis. In order to make it affordable for analysts with massive and fast growing networks, we present X-RIME, a cloud-based library for large scale social network analysis. We propose an implementation-oriented...
Lossless coding is commonly found in binary image encoding with lower compression ratio. In this paper, image segmentation is used to classify the document image into line image regions, text image regions and halftone image regions. According to different features of each region, different encoding methods are applied to improve the image compression ratio. Adaptive arithmetic coding is used for...
Mining frequent closed itemsets provides complete and condensed information for frequent pattern mining. Online mining of frequent closed itemsets over streaming data is one of the most important issues in mining data streams. In this paper, we first present a general methodology to identify closed itemsets over data streams, using concept lattice theory. Using this methodology, we then proposed a...
Certificateless public key cryptography (CLPKC) is an attractive paradigm which combines the advantages of both certificate-based and identity-based cryptosystems as it avoids the use of certificates and does not suffer from key escrow. This paper studies certificateless strong designated verifier signatures (CLSDVS) based on bilinear pairings by combining CLPKC with the strong designated verifier...
This paper studies fair resource allocation schemes for orthogonal frequency-division multiple-access (OFDMA) with the decode-and-forward relaying strategy. To satisfy the heterogenous rate requirement of each user while considering the fairness and efficiency as performance indices, the bargaining theory is applied to allocate resource at a relay node to multiple source nodes. Motivated by the fact...
In this paper, a new biometric authentication scheme based on fingerprint is proposed. To the best knowledge of us, this is the first biometric authentication scheme which is combined with fuzzy extractor and smart card. Futhermore, this scheme has improved the security flaws of previous schemes and can be suitable to the use of ATM, e-bank, and e-commerce etc. due to its convenience and simplicity...
Discernibility matrix method is an important method to design algorithm for computing the core based on information entropy. In this method, the core is found by discovering all discernibility elements of discernibility matrix. So this method is very time consuming. To improve the efficient of computing the core based on information entropy, the core of the simplified decision which is the same as...
Identity-based designated verifier signatures allow a signer to designate a specific verifier by using a simplified public identity such as name or IP address. In such a way, only the designated verifier can check the validity of signatures. In this paper, we present an ID-based strong designated verifier signature (IBSDVS) scheme from bilinear pairings, and provide the security proofs and efficiency...
SIFT (scale invariant feature transform) is an important local invariant feature descriptor. Since its expensive computation, SURF (speeded-up robust features) is proposed. Both of them are designed mainly for gray images. However, color provides valuable information in object description and matching tasks. To overcome the drawback and to increase the descriptor's distinctiveness, this paper presents...
Designing efficient algorithm for computing the core of decision table is a very meaningful work because the core is the foundation of constructing attribute reduction of the decision table and multi-variable decision tree. To improve the efficiency of the algorithm for computing the core based on Skowron's discernibility matrix, simplified decision table and the definition of the core based the Skowron's...
Choosing appropriate values for kernel parameters is one of the key problems in many kernel-based methods. Beside common used cross validation method which is time-consuming, another kind of rapid methods using kernel matrix evaluation criteria such as kernel target alignment(KTA) and Feature space-based kernel matrix evaluation measurement(FSM) criteria were proposed by researchers. However, we find...
Recently, non-contact measurement technology has improved significantly. With the increasing of the accuracy and the speed of data acquisition of 3D laser scanners, the amount of point data has increased dramatically . 3D laser scanners generate up to thousands of points per second, which have become a burden of both computation and store of the data. It is quite important, therefore, to reduce the...
Resource discovery is a key component of P2P network. The resource discovery algorithm complexities of classic models, such as Chord and Pastry, are always equal or even bigger than O(logN), which means while the network scale increasing, the time delay will also increase rapidly without a ceiling. In this paper, we present a new P2P network model for resource discovery. Firstly, we take location-aware...
Support Vector Machines (SVM) has drawn extensive interests due to its attractive properties, based on which some dimensionality reduction methods have been proposed. However, SVM here only serves as a feature extractor rather than a classifier, the extracted features are in turn used as inputs to other different classifiers. In this paper, a novel and simpler SVM-induced Dimensionality Reduction...
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