In the environment of the Internet of Things for heat meter, insecurity of the object name service (ONS) is likely to lead to the leakage of user privacy. In order to solve this problem, an identity authentication alg...
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In the environment of the Internet of Things for heat meter, insecurity of the object name service (ONS) is likely to lead to the leakage of user privacy. In order to solve this problem, an identity authentication algorithm is proposed. First, the certificate authority may generate parameters of elliptic curve and its own public key and private key, and announce the parameters and its own public key, so that the registered users can inquire and use them. Second, the client registers at the certificate authority. The certificate authority will generate the public key of the client and the evidence of the client's private key which is signed by private key of the certificate authority. If the generated evidence of private key passes verification of the client, the client will generate its own private key. When a client sends a query request to an ONS server, the ONS server will authenticate identity of the client. If the client gets through the authentication, the ONS server will respond to the query request. The experimental result shows that this algorithm has high security and can avoid the ONS server providing query service for illegitimate client, so as to ensure the security of user privacy.
The set of frequent closed itemsets is much smaller than the one of all frequent itemsets. Meanwhile it retains the completeness. In this paper, we propose an ITBitree-based algorithm, called ITBitreeFCIM (ITBitree Fr...
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The set of frequent closed itemsets is much smaller than the one of all frequent itemsets. Meanwhile it retains the completeness. In this paper, we propose an ITBitree-based algorithm, called ITBitreeFCIM (ITBitree Frequent Closed Itemsets Miner), for mining the frequent closed itemsets directly. A novel structure termed ITBitree (Itemset Tidset Binary Tree) is defined to store the transaction and itemset information. Frequent closed itemsets are generated directly by searching the right nodes in each layer and the right nodes in their respective search space deeply from this tree using top-down strategy. For the items with same support in the adjacent layers or the items with the same Tids, we use item merging technique to prune the search space. The searched space is used to avoid the generation of duplicates and enormous closure checks. In the process we do not need to check whether a candidate itemset is closed, so we save a lot of time. The experiment proofs the efficiency of the proposed approach.
Synchronization decay of resting state EEG has shown that cognitive dysfunction in mild cognitive impairment (MCI) was relevant to a loss of functional connectivity in intermediate frequency bands. A new estimator ana...
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Synchronization decay of resting state EEG has shown that cognitive dysfunction in mild cognitive impairment (MCI) was relevant to a loss of functional connectivity in intermediate frequency bands. A new estimator analysis method called new S estimator (NSE) proposed recently by us quantifies synchronization between neuronal signals at multiple *** paper meant to explore the behavior of synchronization of multichannel EEG in MCI and healthy normal controls at rest, and preliminarily make clear the clinical significance of the NSE in MCI *** (EEG) were recorded from 10 MCI patients and 12 age-matched healthy normal controls (NC). NSE values were computed both across the all frequency band and separately in the delta, theta, alpha, beta (including beta1, beta2 and beta3), and gamma bands. The Montreal Cognitive Assessment (MoCA) was used to assess the symptom severity of MCI patients and *** values in the alpha and beta1 bands were significantly lower in MCI patients than in NC. NSE values in the alpha and beta1 bands were positively correlated with the MoCA scores in all participants (MCI and NC). In MCI patients, NSE values in the alpha and beta1 bands were also positively correlated with MoCA *** results suggest that NSE values are a useful correlate of EEG synchronization in MCI patients.
Most of algorithms based on bit vector for mining frequent pattern always produce candidate itemsets and scan the same data repeatedly;this increases the running time and the space consumption. In this paper, an algor...
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Most of algorithms based on bit vector for mining frequent pattern always produce candidate itemsets and scan the same data repeatedly;this increases the running time and the space consumption. In this paper, an algorithm BVDAHL based on bit vector decomposition and hash linklist for mining frequent patterns on data streams which solves the above issues, is proposed. The itemsets (transactions) whose corresponding number of 1 is k, denoted as k-one itemsets (k-one transactions). The arrival transactions are converted into bit vectors, and permutations and combinations are used to decompose converted results, then the decomposed itemsets are stored in the hash linklist. In hash function, according to the position of 1 of bit vector to compute the address, if the transaction has same address and same content that already exists in data domain, then the value adds one in count domain, otherwise the pointer in pointer domain points to the next node directly, it is no need to deal with conflict. Afterwards the property of anti-monotonic will be used to prune the k+1-one transactions in bit vector table if there exists infrequent k-one itemsets that decomposed by such k+1-one transactions. Then the algorithm repeats the above processes until the transaction in bit vector table can not be decomposed. Finally we will receive the frequent itemsets by comparing the obtained value of count domain in hash linklist with minSup. Experiment results show that BVDAHL is very efficiency and scalable.
In the peer-to-peer (P2P) live streaming systems, a single stream is decomposed into multiple sub-streams. For the participating nodes, data blocks of different sub-streams are stored in different sub-buffers for sync...
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Algorithms based on row enumeration always scan and construct conditional transposed tables, which increases the execution time and space cost. To address this problem, we adopt the DAG (Directed Acyclic Graph) to com...
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Algorithms based on row enumeration always scan and construct conditional transposed tables, which increases the execution time and space cost. To address this problem, we adopt the DAG (Directed Acyclic Graph) to compress the dataset to save the memory space. In DAG, each node is related to a rowid, and each two nodes have a corresponding directed edge which stores the common items of the two rowids. Each row is given an integer according to its coming order and the DAG follows that order. A directed acyclic graph records the relation between rows and items by doing AND(&) operation with the nodes' binary code of the edges. We also present DAGHDDM which is a new approach for mining frequent closed itemsets in high dimensional datasets. In this algorithm, we adopt the BitTable to compress the dataset firstly, and then construct DAG according to the BitTable. We increase the same items of the adjacent edges to implement pattern growth, traverse the DAG in reversal way and adopt a close-checking method to generate all frequent closed itemsets. It scans the dataset only once and does not generate candidate itemsets. The experimental results show that the proposed DAGHDDM algorithm can decrease the cost of time.
We consider the problem of pilot design for sparse multipath channel estimation in multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system in this *** order to reconstruct MIMO s...
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ISBN:
(纸本)9781467321006
We consider the problem of pilot design for sparse multipath channel estimation in multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system in this *** order to reconstruct MIMO sparse channel,the prevalent compressed sensing (CS) theory is *** to random pilot construction,a deterministic pilot de- sign method is exploited to form the measurement matrix by deterministically extracting some rows of Fourier matrix that satisfies Restricted Isometry Property (RIP).Two families of continuous functions,namely f1 -SL0 and f 2-SL0,are investi- gated in this paper to approximate A 0norm for MIMO sparse channel *** results suggest that the de- terministic pilot design scheme performs as well as the random one at both low and high signal noise ratio (SNR).Moreover,f1 - SL0 and f 2-SL0 outperform A 1-dantzig algorithm with faster running time and better anti-noisy performance.
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