Many network processing applications require wire-speed access to large data structures or a large amount of flow-level data, but the capacity of SRAMs is woefully inadequate in many cases. In this paper, we analyze a...
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ISBN:
(纸本)9781424458363
Many network processing applications require wire-speed access to large data structures or a large amount of flow-level data, but the capacity of SRAMs is woefully inadequate in many cases. In this paper, we analyze a robust pipelined memory architecture that can emulate an ideal SRAM by guaranteeing with very high probability that the output sequence produced by the pipelined memory architecture is the same as the one produced by an ideal SRAM under the same sequence of memory read and write operations, except time-shifted by a fixed pipeline delay of ¿. The design is based on the interleaving of DRAM banks together with the use of a reservation table that serves in part as a data cache. In contrast to prior interleaved memory solutions, our design is robust even under adversarial memory access patterns, which we demonstrate through a rigorous worst-case theoretical analysis using a combination of convex ordering and large deviation theory.
We demonstrate lasing in two-dimensional deterministic aperiodic nanostructures with optical pumping. The lasing modes are strongly localized within the structures. Such lasers combine the advantages of both photonic ...
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In this paper, an artificial neural network model is built up with two pathways: bottom-up sensory-driven pathway and top-down expectation-driven pathway, which are fused to train the neural network for visual object ...
In this paper, an artificial neural network model is built up with two pathways: bottom-up sensory-driven pathway and top-down expectation-driven pathway, which are fused to train the neural network for visual object recognition. During the supervised learning process, the bottom-up pathway generates hypotheses as network outputs. Then target label will be applied to update the bottom-up connections. On the other hand, the hypotheses generated by the bottom-up pathway will produce expectations on the sensory input through the top-down pathway. The expectations will be constrained by the real data from the sensory input which can be used to update the top-down connections accordingly. This two-pathway based neural network can also be applied to semi-supervised learning with both labeled and unlabeled data, where the network is able to generate hypotheses and corresponding expectations. Experiments on visual object recognition suggest that the proposed neural network model is promising to recover the object for the cases with missing data in sensory inputs.
Morphogenesis is the biological process that governs self-organized spatial pattern formation of cells during the embryonic development of multi-cellular organisms. Inspired by this process, we have proposed a morphog...
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Morphogenesis is the biological process that governs self-organized spatial pattern formation of cells during the embryonic development of multi-cellular organisms. Inspired by this process, we have proposed a morphogenetic framework for pattern formation and boundary coverage in a distributed swarm robotic system. The framework is based only on local communications among robots and will set up a local coordinate system. This paper focuses on the theoretical and empirical analysis of the framework regarding two aspects, namely, local communication load among the robots, and system performance such as system convergence time and average travel distance of robots for several pattern formation tasks. Results show that the proposed framework is efficient and scalable for self-organizing distributed swarm robotic systems with reasonable local communication load among robots.
Internet drives the diversification of network applications. As telecommunication operators widely deploy wireless mobile communication networks, the public can access network services if they are within the wireless ...
Internet drives the diversification of network applications. As telecommunication operators widely deploy wireless mobile communication networks, the public can access network services if they are within the wireless signal range of mobile base stations. Therefore, a mobile device with computing process ability can allow access to an ubiquitous network via mobile communication network. The Android platform released from Google allows users to modify source code freely, hence facilitating the development of software applications and improving user interface and performance. Such free authorization can safeguard developer's rights, and thus, it has commercial value. Based on the Android mobile phone, this study proposed the design and implementation of LBMMPS (Location Based Mobile Multimedia Pusher System), which pushes incident multimedia content to friends online in real time. The user can share incident videos, photos, and messages with other friends online in real time. By integrating GPS coordinates of incidents into Google Map, users can indicate the location where an incident occurs via a map interface. LBMMPS records the location of a moving trajectory of a special incident, and shows the incident's movements on the map.
Detecting human activities automatically in a video stream in various scenes is a challenging task. The major difficulty of this task lies in how to extract the spatial and temporal features of video sequences so that...
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Detecting human activities automatically in a video stream in various scenes is a challenging task. The major difficulty of this task lies in how to extract the spatial and temporal features of video sequences so that the human activities can be recognized. To tackle this problem, we propose a new classifier model using a BCM-based spiking neural network, where the auto-regulated plasticity and meta-plasticity of the BCM network will help to extract the temporal features for the classifier. In the proposed model, the weight, weight plasticity, and meta-plasticity of the BCM network are regulated by a gene regulatory network (GRN), which plays a key role in neural development and neuromodulation. Meanwhile, the GRN will also be influenced by the activity of the neurons it resides in, resulting in a closed loop between the neural network and GRN. By using this new classifier model, only the spatial features need to be extracted from image frames in the preprocessing. Extensive experimental results have demonstrated the efficiency of the proposed model for online human activity detection.
Most experimental realizations of quantum key distribution are based on the Bennett-Brassard 1984 (the so-called BB84) protocol. In a typical optical implementation of this scheme, the sender uses an active source to ...
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Most experimental realizations of quantum key distribution are based on the Bennett-Brassard 1984 (the so-called BB84) protocol. In a typical optical implementation of this scheme, the sender uses an active source to produce the required BB84 signal states. While active state preparation of BB84 signals is a simple and elegant solution in principle, in practice passive state preparation might be desirable in some scenarios, for instance, in those experimental setups operating at high transmission rates. Passive schemes might also be more robust against side-channel attacks than active sources. Typical passive devices involve parametric down-conversion. In this paper, we show that both coherent light and practical single-photon sources are also suitable for passive generation of BB84 signal states. Our method does not require any externally driven element, but only linear optical components and photodetectors. In the case of coherent light, the resulting key rate is similar to the one delivered by an active source. When the sender uses practical single-photon sources, however, the distance covered by a passive transmitter might be longer than that of an active configuration.
Privacy protection in Service-Oriented Architecture (SOA) is an open problem. As privacy protection can be considered as a contractual issue, the solution for the problem of privacy protection in SOA requires the use ...
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Privacy protection in Service-Oriented Architecture (SOA) is an open problem. As privacy protection can be considered as a contractual issue, the solution for the problem of privacy protection in SOA requires the use of electronic contracts. This is important, as the service consumer's confidence of the protection of their privacy is a factor for the success of electronic services (e-services). This confidence may increase if the service consumer and provider can establish a contract, which states how the provider deals with information collected from the consumer. The service consumer can sign the contract if the privacy protection practices described in it meet what the consumer defines as appropriate practices. The goal of this paper is to use contract and ontology for privacy protection in SOA. Privacy contracts follow an approach based on feature modeling. In addition, they use a base ontology that provides a common privacy vocabulary.
The use of heterogeneous distributed systems, such as Clusters of Clusters (CoC) and computational grids, enables the development of complex computational systems. However some of these systems require services to be ...
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The use of heterogeneous distributed systems, such as Clusters of Clusters (CoC) and computational grids, enables the development of complex computational systems. However some of these systems require services to be easily composed and executed while maintaining the dependencies among them; both the services and the dependencies can be represented as workflows. Moreover, Web Services have been adopted in distributed systems, and WS-BPEL is the standard for Web Services composition. Accordingly, the objective of this work is to enable the execution of WS-BPEL workflows in a CoC. In order to achieve this execution, an extension to the WS-BPEL language is presented that includes the specification of Quality of Services (QoS), along with the required computational resources for service execution in CoCs. Additionally, this paper presents an infrastructure that enables the execution of such workflows in CoCs. Finally, a case study using SHARCNET as a CoC is discussed in order to evaluate the proposed approach.
We demonstrate reversible tuning of photonic-crystal cavity resonance by 2.7nm using a photochromic film of spiropyran. Exposure of spiropyran to ultraviolet light redshifts the cavity resonance that can be reversed b...
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