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In the last few years, an ecosystem of devices and heterogeneous services has emerged with a huge variety of capacities and characteristics. These new devices, along with applications and services, must be used to enhance the quality of life, making the users daily activities easier, as well as increasing their personal autonomy. In this sense, there is a clear need for creating interfaces that adapt...
Computation of maximal exact matches (MEMs) is an important problem in comparing genomic sequences. Optimal sequential algorithms for computing MEMs have been already introduced and integrated in a number of software tools. To cope with large data and exploit new computing paradigms like cloud computing, it is important to develop efficient and ready-to-use solutions running on distributed parallel...
LEACH algorithm as a classic clustering algorithm is widely used in wireless sensor networks, but not considers the number of cluster head, monitoring areas and other factors, and the network greatly huge consumption reduces the life cycle of the network. To this defects, on the basis of the optimal coverage theorem in Wang, a kind of CDE-LEACH algorithm is proposed, which pre-built data table to...
In the Cloud manufacturing environment, there are a huge number of cloud services, which are dynamic and changeful. The management of cloud services is very difficult. The paper presents a hypergraph clustering-based method to manage cloud manufacturing services. The clustering-based Cloud Manufacturing Service Management Model is presented, which contains three layers: manufacturing resources, cloud...
Image segmentation is a fundamental process in computer vision applications. This paper presents a novel method to deal with the issue of image segmentation. Each image is first segmented coarsely, and represented as a graph model. Then, a semi-supervised algorithm is utilized to estimate the relevance between labeled nodes and unlabeled nodes to construct a relevance matrix. Finally, a normalized...
We study the important problem of source localization in the context of information spreads in large social networks. Specifically, we design a Maximum-Likelihood source localization algorithm that is especially suited to large social networks. Our proposed algorithm requires about 3% fewer sensor nodes than other single stage algorithms for the same level of accuracy in detection. For practical social...
One type of distributed systems is the client/server system consist of clients and servers. In order to improve the performance of such a system, client assignment strategy plays an important role. There are two criteria to evaluate the load on the servers — total load and load balance. The total load increases when the load balance decreases, vice versa. It has been proved that finding the best client...
We investigate a method to improve the compression ratio for hyperspectral data compression by use of a pre-processing step that gathers together correlated pixels before the transform is applied in a KLT-JPEG2000 based compression. Using a k-means clustering algorithm, the pixels can be grouped together before the application of the transform. Some similar methods have been studied, but k-means has...
Wireless sensor network is one of the most promising technology in wireless network. To design a sensor network, improving the lifetime of sensor node is critical issue. For these reason researchers in these field pay great attention to Medium Access Control (MAC) protocol. As most of the nodes are placed in remote and hazardous area, so when the power is down it is difficult to recharge them or it...
This paper presents a learning algorithm for adaptive network intrusion detection based on clustering and naïve Bayesian classifier, which induces a hybridization of unsupervised and supervised learning processes. The proposed approach scales up the balance detection rates for different types of network intrusions, and keeps the false positives at acceptable level in network intrusion detection....
Massive amount of genomics data are being produced nowadays by Next Generation Sequencing machines. The suffix array is currently the best choice for indexing genomics data, because of its efficiency and large number of applications. In this paper, we address the problem of constructing the suffix array on computer cluster in the cloud. We present a solution that automates the establishment of a computer...
One of the main challenges in Computer- Supported Collaborative Learning (CSCL) is group formation. Various approaches have been reported in the literature to tackle this problem, but none have offered an optimal solution. In this study a novel binary integer programming formulation was proposed to model the group formation problem and optimally assign each learner to the most appropriate group. In...
Link state IP protocols like OSPF and IS-IS work upon network state advertisements. Link state packets travel all over the network, advertising recent failure or changes in the network. It is IP router responsibility to execute the complex updating process which includes recalculating shortest paths and updating central and local forwarding tables. Since forwarding tables must be updated for forwarding...
Cluster is bunch of similar items. Unsupervised classification of patterns into clusters is known as clustering. It is useful in knowledge discovery in data. Clustering is able to deal with different data types. Fuzzy rules are used for data intelligence illustration purpose. User gets highly interpretable discovered clusters using fuzzy rules. To generate accurate fuzzy rules triangular membership...
Polymorphic worms are considered as the most dangerous threats to the Internet security, and the danger lies in changing their payloads in every infection attempt to avoid the security systems. In this paper, we propose an accurate signature generation system for zero-day polymorphic worms. We have designed a novel Double-honeynet system, which is able to detect zero-day polymorphic worms that have...
In this paper, we propose an interactive clothing image segmentation method based on super pixels and Graph Cuts. Firstly, we process the image from pixels to super pixels with the method of SLIC to reduce the computational loads and lower the effect of noise, and then a graph is constructed using super pixels as nodes. Finally, min-cut/max-flow algorithm is applied to solve the energy function. In...
In this paper, we propose an algorithm that detects overlapping communities in networks (graphs) based on a simple node behavior model. The key idea in the proposed algorithm is to find communities in an agglomerative manner such that every detected community S has the following property: For each node i ∈ S, we have (i) the fraction of nodes in S \ {i} that are neighbors of node i is greater than...
The tremendous growth in data volumes has created a need for new tools and algorithms to quickly analyze large datasets. Cluster analysis techniques, such as K-means can be used for large datasets distributed across several machines. The accuracy of K-means depends on the selection of seed centroids during initialization. K-means++ improves on the K-means seeder, but suffers from problems when it...
Frequent pattern mining has a critical role in mining associations, sequential patterns, correlations, causality, episodes, multidimensional patterns, emerging patterns, and many other significant data mining tasks. With the exponential growth of available data, most of the traditional frequent pattern mining algorithms become ineffective due to either huge resource requirements or large communications...
This paper introduces an automatic method for licenses plate detection that using local corners points features, clustering and some properties of license plate. Licenses plates are rich corner point's area that can be used with some properties of license plate to locate licenses plate location. The algorithm has four stages; firstly, the quality of image is improved via preprocessing operations....
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