This paper surveys research on the Resource Space Model RSM. RSM is a classification-based, multi-dimensional and content-based space model for efficiently and effectively managing various resources. As a non-relation...
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This paper surveys research on the Resource Space Model RSM. RSM is a classification-based, multi-dimensional and content-based space model for efficiently and effectively managing various resources. As a non-relational data model, it has a rather complete theoretical basis and has significant applications in faceted search and the future cyber-physical society. Applications in picture resources and email resources are introduced.
Although deep-learning based video recognition models have achieved remarkable success, they are vulnerable to adversarial examples that are generated by adding human-imperceptible perturbations on clean video samples...
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The pilot contamination is caused by non-orthogonal pilot sequences reuse in uplink, which affects the performance of Massive MIMO systems seriously, so it is necessary to mitigate pilot contamination. In this paper, ...
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The pilot contamination is caused by non-orthogonal pilot sequences reuse in uplink, which affects the performance of Massive MIMO systems seriously, so it is necessary to mitigate pilot contamination. In this paper, we propose a pilot contamination precoding scheme to mitigate multi-cell pilot contamination. In the uplink, we propose a cell-defined training scheme, where the same pilot sequence is used in the same cell, and different cells use orthogonal pilot sequences, which eliminates inter-cell interference and introduces intra-cell interference artificially. In the downlink, we adopt Truncated Polynomial Expansion (TPE) precoding to reduce intra-cell interference, since the truncated polynomial of TPE precoding can replace the matrix inversion of Regularized Zero-Forcing (RZF) precoding, which reduces the complexity of RZF precoding and approximates the performance of RZF precoding by suitable truncation orders. Simulation results show the effectiveness of the proposed scheme.
Recent research has demonstrated that Deep Neural Networks (DNNs) are vulnerable to adversarial patches which introduce perceptible but localized changes to the input. Nevertheless, existing approaches have focused on...
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A novel compact broadband circularly polarized (CP) antenna is proposed for use in the Global Navigation Satellite System (GNSS). Circular polarization for the presented antenna is achieved by introducing two L-shaped...
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ISBN:
(纸本)9781538616093
A novel compact broadband circularly polarized (CP) antenna is proposed for use in the Global Navigation Satellite System (GNSS). Circular polarization for the presented antenna is achieved by introducing two L-shaped branches in the ground plane and inverted L-shaped microstrip fed. The antenna exhibits a wide impedance bandwidth of 44.9% (1.14-1.8GHz) for reflection coefficient<-10dB and an axial ratio (AR) bandwidth of 36.9% (1.15-1.67GHz) for AR<3dB. The CP bandwidth (reflection coefficient<-10dB and AR<3dB) can cover all GNSS frequency bands. Although simple in structure, the antenna can meet the requirements for handheld wireless terminals.
Searching frequent patterns in transactional databases is considered as one of the most important data mining problems and Apriori is one of the typical algorithms for this task. Developing fast and efficient algorith...
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In this paper,we study a class of nonlinear fractional integro-differential equations,the fractional derivative is described in the Caputo *** the properties of the Caputo derivative,we convert the fractional integro-...
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In this paper,we study a class of nonlinear fractional integro-differential equations,the fractional derivative is described in the Caputo *** the properties of the Caputo derivative,we convert the fractional integro-differential equations into equivalent integral-differential equations of Volterra type with singular kernel,then we propose and analyze a spectral Jacobi-collocation approximation for nonlinear integro-differential equations of Volterra *** provide a rigorous error analysis for the spectral methods,which shows that both the errors of approximate solutions and the errors of approximate fractional derivatives of the solutions decay exponentially in L^(∞)-norm and weighted L^(2)-norm.
It is well known that a triangle can be divided by mid-point refinement into four sub-triangles with the same shape. Similarly, a tetrahedron can be parted into eight subtetrahedra, which are generally not uniform in ...
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It is well known that a triangle can be divided by mid-point refinement into four sub-triangles with the same shape. Similarly, a tetrahedron can be parted into eight subtetrahedra, which are generally not uniform in shape. This paper proves that there exist a set of tetrahedra, which is called isometrically subdivisible tetrahedra(IST) and can be divided into eight isometric subtetrahedra, including identical and reflection ones. And a new classification of tetrahedra is put forward, based on which all tetrahedra can be categorized into 26 classes according to both the number of maximum equal edges and topological relations. The IST belongs only to three of the classes. That result provides a new viewpoint of spatial structure and may be used to tile or subdivide space uniformly or isometrically.
Object navigation,whose goal is to let the agent to reach some places(or objects),has been a popular topic in embodied Artificial Intelligence(AI)***,in our real-world applications,it is more practical to find the tar...
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Object navigation,whose goal is to let the agent to reach some places(or objects),has been a popular topic in embodied Artificial Intelligence(AI)***,in our real-world applications,it is more practical to find the targets with particular goals,raising the new requirements of finding the places to achieve the particular *** this paper,we define a new task of affordance navigation,whose goal is to find possible places to accomplish the required functions,achieving some particular *** first introduce a new dataset for affordance navigation,collected by the proposed affordance *** order to avoid the high cost of labor,the groundtruth of each episode which is annotated with the interaction data provided by the AI2-THOR *** addition,we also propose an affordance navigation framework,where an Object-to-Manipulation Graph(OMG)is constructed and optimized to emphasize the corresponding nodes(including object nodes and manipulation nodes).Finally,a navigation policy is implemented(trained by reinforcement learning)to guide the navigation to the target *** results on AI2-THOR simulator illustrate the effectiveness of the proposed approach,which achieves significant gains of 14.0%and 11.7%(on success rate and Success weighted by Path Length(SPL),respectively)over the baseline model.
As people come into contact with image data more often, high quality and clear images attract more attention. Many methods have been proposed to deal with image noise problem including deep learning (DL). However most...
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