In this paper, we study the relationship between the network-based inference method and global ranking method in personal recommendation. By some theoretical analysis, we prove that the recommendation result under the...
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ISBN:
(纸本)9781467386456
In this paper, we study the relationship between the network-based inference method and global ranking method in personal recommendation. By some theoretical analysis, we prove that the recommendation result under the global ranking method is the limit of applying network-based inference method with infinite times.
In this paper we explore non-orthogonal multiple access (NOMA) in millimeter-wave (mmWave) communications (mmWave-NOMA). In particular, we consider a typical problem, i.e., maximization of the sum rate of a 2-user mmW...
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Location based services are the hottest applications on mobile device nowadays. Indoor wireless position is the key technology to enable location based service to work well indoors, where Global Position system normal...
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ISBN:
(纸本)9781509019168
Location based services are the hottest applications on mobile device nowadays. Indoor wireless position is the key technology to enable location based service to work well indoors, where Global Position system normally couldn't work. The main tendency of indoor wireless position is based on Bluetooth and RSSI (radio signal strength indicator). RSSI is the key parameter for wireless position. But values of RSSI are affected by environment factors easily. Because of this reason, results got from the indoor location technology are usually imprecise and unacceptable. In this paper, an adaptive algorithm based on Distance-Loss model in complex environment is introduced to deal with such problems. The algorithm makes the model adapt to the environment by several parameters which are not influenced by environment. The stability and the accuracy of the algorithm is evidenced by a series of strict experiences.
The rise of cloud computing and the Internet not only bring change on the data center, but also lead to transformation in software development, deployment, operation and maintenance. With the continuous improvement of...
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The rise of cloud computing and the Internet not only bring change on the data center, but also lead to transformation in software development, deployment, operation and maintenance. With the continuous improvement of the current cloud computing and the internet environment, how to make better use of cloud computing platform, and how to serve the users is a popular field of computer software is a big challenge. In recent years, with the further development of concepts like micro-services and containers, software will further step forward to the Cloudware. This paper discusses how to deploy Cloudware in cloud environment, and proposes a new method to construct the PaaS platform which can directly deploy software on the cloud without any modification, while achieving a new model by the browser services. By using micro-service architecture, we achieving good performance of extension, scalable deployment, faults tolerance and flexible configuration. Finally, we evaluate this method by constructing a complete framework and carrying out an interactive delay experiment that directly focuses on users' experience, which also shows the effectiveness of this method.
The deep two-stream architecture [23] exhibited excellent performance on video based action recognition. The most computationally expensive step in this approach comes from the calculation of optical flow which preven...
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ISBN:
(纸本)9781467388511
The deep two-stream architecture [23] exhibited excellent performance on video based action recognition. The most computationally expensive step in this approach comes from the calculation of optical flow which prevents it to be real-time. This paper accelerates this architecture by replacing optical flow with motion vector which can be obtained directly from compressed videos without extra calculation. However, motion vector lacks fine structures, and contains noisy and inaccurate motion patterns, leading to the evident degradation of recognition performance. Our key insight for relieving this problem is that optical flow and motion vector are inherent correlated. Transferring the knowledge learned with optical flow CNN to motion vector CNN can significantly boost the performance of the latter. Specifically, we introduce three strategies for this, initialization transfer, supervision transfer and their combination. Experimental results show that our method achieves comparable recognition performance to the state-of-the-art, while our method can process 390.7 frames per second, which is 27 times faster than the original two-stream method.
Feature representation is the critical factor for the computer-aided Alzheimer's disease (AD) diagnosis. Deep polynomial network (DPN) is a novel deep learning algorithm, which can effectively learn feature repres...
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ISBN:
(纸本)9781479923519
Feature representation is the critical factor for the computer-aided Alzheimer's disease (AD) diagnosis. Deep polynomial network (DPN) is a novel deep learning algorithm, which can effectively learn feature representation from small samples. In this work, a stacked DPN (S-DPN) algorithm is proposed to further improve feature representation. We then propose a multi-modality S-DPN (MM-S-DPN) algorithm to fuse multi-modality neuroimaging data and learn more discriminative and robust feature representation for AD classification. Experiments are performed on ADNI dataset with MRI and PET images as multi-modality data. The results indicate that S-DPN is superior to DPN and stacked auto-encoder algorithms. Moreover, MM-S-DPN achieves best performance compared with single-modality S-DPN and other multi-modality feature learning based algorithms.
Liveness is a basic property of a system and the liveness issue of unbounded Petri nets remains one of the most difficult problems in this *** work proposes a novel method to decide the liveness of a class of unbounde...
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Liveness is a basic property of a system and the liveness issue of unbounded Petri nets remains one of the most difficult problems in this *** work proposes a novel method to decide the liveness of a class of unbounded generalized Petri nets calledω-independent unbounded nets,breaking the existing limits to one-place-unbounded *** algorithm to construct a macro liveness graph(MLG)is developed and a critical condition based on MLG deciding the liveness ofω-independent unbounded nets is *** are provided to demonstrate its effectiveness.
As a powerful analysis tool of Petri nets, reachability trees are fundamental for systematically investigating many characteristics such as boundedness, liveness and reversibility. This work proposes a method to gener...
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This paper discusses the cloud desktop technology, virtualization technology and penetration testing technology used in the network attack and defense training platform, and introduces the design and implementation pr...
This paper discusses the cloud desktop technology, virtualization technology and penetration testing technology used in the network attack and defense training platform, and introduces the design and implementation process of the network attack and defense training platform. This paper focuses on the cloud desktop construction scheme based on B/S structure, and aims to enhance the flexibility and convenience of network attack and defense training platform.
In recent years, the Bag-of-Words (BoW) model has been widely used in most state-of-the-art large-scale image re-trieval systems. However, the standard BoW based systems suffer from low discriminative power of local f...
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