Human behavior recognition has become a hot research topic in computer vision. In this paper, we propose an effective method to recognize human behaviors from sequences of depth maps, which provide additional body sha...
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In traditional collaborative filtering recommendation algorithms, users' grades are used to calculate the similarity between different items, which is used to predict the result of recommendation further. Same gra...
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In traditional collaborative filtering recommendation algorithms, users' grades are used to calculate the similarity between different items, which is used to predict the result of recommendation further. Same grades for different items from same user can't demonstrate the similarity between the items and will decrease the influence on items not so popular. To improve reliability of similarity of calculating, this paper weighs the grades according to proportion of corresponding grades based on the traditional algorithms, which is called collaborative filtering recommendation algorithm based on weighed grades. The result of experiments demonstrates this method of calculating considering the influence on items not so popular that traditional methods don't [1], increasing the accuracy of recommendation.
In this paper, we propose a novel subspace learning algorithm, termed as null space based discriminant sparse representation large margin (NDSLM). There are two contributions in the paper. First, we propose a new expe...
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ISBN:
(纸本)9781479919611
In this paper, we propose a novel subspace learning algorithm, termed as null space based discriminant sparse representation large margin (NDSLM). There are two contributions in the paper. First, we propose a new expectation to obtain the neighborhood information for large margin subspace learning, i.e., the within-neighborhood scatter and between-neighborhood scatter are modeled by the sparse reconstruction weights of the samples from the same class and different classes, respectively. Since the neighborhood information formed by sparse representation can capture non-linearities in the data, the proposed method possesses more discriminative information than the traditional large margin learning methods with the expectation using Euclidean distance, etc. Second, the large margin information integrated into the model of Fisher criterion makes the discriminating power of NDSLM further boosted. NDSLM addresses the small sample size problem by solving an eigenvalue problem in null space. Experiments on ORL, Yale, AR, Extended Yale B and CMU PIE five face databases are performed to evaluate the proposed algorithm and the results demonstrate the effectiveness of NDSLM.
Since the Internet of Things(IoT) secret information is easy to leak in data transfer,a data secure transmission model based on compressed sensing(CS) and digital watermarking technology is proposed here. Firstly,...
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Since the Internet of Things(IoT) secret information is easy to leak in data transfer,a data secure transmission model based on compressed sensing(CS) and digital watermarking technology is proposed here. Firstly, for node coding end, the digital watermarking technology is used to embed secret information in the conventional data carrier. Secondly, these data are reused to build the target transfer data by the CS algorithm which are called observed signals. Thirdly, these signals are transmitted to the base station through the wireless channel. After obtaining these observed signals, the decoder reconstructs the data carrier containing privacy information. Finally, the privacy information is obtained by digital watermark extraction algorithm to achieve the secret transmission of signals. By adopting the watermarking and compression sensing to hide secret information in the end of node code, the algorithm complexity and energy consumption are reduced. Meanwhile, the security of secret information is *** simulation results show that the method is able to accurately reconstruct the original signal and the energy consumption of the sensor node is also reduced significantly in consideration of the packet loss.
Degradation tests are often used to assess the reliability of products with long failure-time or few test units. Much of the previous work on reliability assessment methods has focused on constant-stress degradation t...
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Degradation tests are often used to assess the reliability of products with long failure-time or few test units. Much of the previous work on reliability assessment methods has focused on constant-stress degradation test( CSDT) and accelerated degradation test( ADT), mainly under the constant, step or progressive stresses. However,in actual testing environments,some stresses are difficult to control and vary with time irregularly,which are quite different from the three stresses mentioned above. In this paper a new approach was presented for reliability assessment with degradation data under irregular time-varying-stress( ITVS).Firstly,the conventional degradation path modeling method was improved by taking into account the influences of the variable stress on the degradation variable. Then,an example was conducted to show the effectiveness of our improved model.
Information recommendation between groups is one of the most important ways for information sharing and transmitting in social networks. However, it needs exponential time cost to achieve the exact optimal recommendat...
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Pi Calculus, a kind of process algebra has been widely used to describe distributed computation system currently, such as Web service and cloud platform. A variant of Pi Calculus, Pi-beam, is proposed with some import...
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Compared to the traditional SAR imaging algorithm, Back Projection(BP) algorithm is an accurate point-by-point imaging radar algorithm based on time-domain, with simple principle and without any approximation error in...
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ISBN:
(纸本)9781510822023
Compared to the traditional SAR imaging algorithm, Back Projection(BP) algorithm is an accurate point-by-point imaging radar algorithm based on time-domain, with simple principle and without any approximation error in the imaging process. However, because of intensive computation and low efficiency, it's a new challenge to storage to capacity, throughput and processing ability of DSPs, a single DSP is not enough to meet these demands. So a parallel implementation method of BP algorithm based on TMS320C6678 DSP is proposed in this *** put forward a large point FFT multi-core parallel processing method on 2/4/8 cores what is frequently used in BP algorithm, and a multi-core synchronization method based on distributed memory. Finally using the measured data, we verify the parallel method can greatly enhance the multi-core parallelism, and the real-time performance of BP algorithm has been significantly improved.
With the rapid development of global information and the increasing dependence on network for people, network security problems are becoming more and more serious. By analyzing the existing security assessment methods...
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With the rapid development of global information and the increasing dependence on network for people, network security problems are becoming more and more serious. By analyzing the existing security assessment methods, we propose a network security situation evaluation system based on modified D-S evidence theory is proposed. Firstly, we give a modified D-S evidence theory to improve the reliability and rationality of the fusion result and apply the theory to correlation analysis. Secondly, the attack successful support is accurately calculated by matching internal factors with external threats. Multi-module evaluation is established to comprehensively evaluate the situation of network security. Finally we use an example of actual network datasets to validate the network security situation evaluation system. The simulation result shows that the system can not only reduce the rate of false positives and false alarms, but also effectively help analysts comprehensively to understand the situation of network security.
In semiconductor manufacturing, wafer residency time constraints make the scheduling problem of cluster tools complicated. A process module (PM) in cluster tools is prone to failure. It is crucial to deal with any suc...
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