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Neuromorphic computing takes inspiration from how the brain works to explore novel computing paradigms. Recently, neuromorphic architectures using spiking neurons were proposed for unsupervised learning of pattern- and feature-based representations. These approaches typically use a common WTA architectural motif of lateral inhibition that introduces competition between the neurons. In this paper,...
This paper proposes an approach to construct effectiveness evaluation model semi-automatically based on system architecture such as Department of Defense Architecture Framework (DoDAF). The effectiveness evaluation index system is firstly generated based on architecture models including Capability Dependencies (CV-4), Capability to Operational Activities Mapping (CV-6), Operational Activity to Systems...
The protection of content confidentiality as well as of access and pattern confidentiality of data moved to the cloud have been recently the subject of several investigations. The distributed shuffle index addresses these issues by randomly partitioning data among three independent cloud providers. In this paper, we describe the implementation of the distributed shuffle index in the high-performance...
In ultra-dense cellular networks, research works on enhancing cell edge performance receive considerable attention. Based on interlaced clustering, we propose a heuristic sparse beamforming strategy to improve the cell edge throughput effectively in distributed antenna systems (DASs). In our scheme, each cluster pattern (CP) is divided into several adaptive cells, where all the remote antenna units...
A 2-D Cellular Neural Network structure with space invariant neural weights is widely used in image processing applications. Recent advances VLSI technology appears to be very promising to use discrete time CNNs for real time vision applications. In this paper, a system-on-chip implementation which consists of a new CNN emulator design and a processor which performs template learning algorithm is...
Evaluating architecture of aircraft power supply system precisely is the basis of optimizing aircraft architecture design. The multi-index evaluation of its architecture involves reliability, expense, maintainability, weight and power quality, which provides designers with the optimal decision information, including two steps: normalize individual evaluation index and export each single-index result;...
The Outer-Open Gomoku is a new Gomoku game with three goals: “maintaining connect five”, “simple rule” and “fairness”. This paper introduces the design idea and the implementation of our Outer-Open Gomoku program OOGiveMeFive. It takes advantage of the modern instruction set architecture, inverse bitboard, reducing instruction numbers and search space, etc., to obtain a good performance of searching...
A novel, generic, framework for supporting self-organisation and self-management in hierarchical systems is presented. The framework allows for the incorporation of local self-organising and self-managing strategies at each level in the hierarchy. These local strategies determine the behaviour of that level and the effects of these strategies can be communicated to, and used by, the strategies in...
In this paper, we present an optimized framework that can efficiently perform massive spatial queries on the current GPUs. To benefit the widely adopted filter-and-verify paradigm from GPUs, the skewed workloads are first associated with certain cells in a scaled spatial grid, such that the following range verification cost against the massive spatial objects can be significantly reduced. Particularly...
Hybrid digital-analog (HDA) architectures have been widely developed for efficient digital transmission of analog speech, audio or video data. By considering the advantage of both digital and analog components, HDA systems gain better performances than purely analog and digital schemes in a wide range of channel conditions. However, HDA systems described in previous works are mostly designed for continuous-valued...
Many commercial DBMSs based on a column-oriented storage method have been used to analyze large-scale data. However, the column-oriented DBMS is difficult to use for processing big-data analysis updated in real time, because the column-oriented storage performs inefficient OLTP when processing row-oriented updates. Therefore, we attempted to enable the column-oriented DBMS to efficiently process OLTP...
With the advent of cloud computing, renewable energy is integrated into data center power supply systems increasingly. The power statistics collection may not be available due to the instability of renewable energy, which results in incomplete data. The incomplete energy data will significantly disturb the management of data centers. We further propose a filling algorithm based on complete tolerance...
Web search constitutes an important class of dataintensive online services in data centers. Optimizing search systems for energy efficiency, timely response and high search quality (i.e., how relevant the returned results are to a search query), however, is very challenging, as a search system involves a distributed architecture with hundreds of thousands of index serving nodes (ISNs) that return...
Similarity-oriented services serve as a foundation in a wide range of data analytic applications such as machine learning, target advertising, and real-time decisions. Both industry and academia strive for efficient and scalable similarity discovery and querying techniques to handle massive, complex data records in the real world. In addition to performance, data security and privacy become an indispensable...
Text analytics has become increasingly important in the past few years because of the substantial growth in the amount of research, business, and government needs. An efficient text analytics system is likely to require high-powered regular expression matching (REGEX), as REGEX operations dominate the whole execution time. Some approaches have exploited the parallelism of graphic processing units...
This paper focuses on resource allocation in heterogeneous Ultra Dense small-cell Networks (UDNs), in which massive overlaid small cells are under the coverage of a macro cell. In UDN, both co-tier and cross-tier interference need to be taken into account. When increasing the deployment density of Small-cell Base Stations (SBSs) and the unreasonable energy usage, it results in serious interference...
We present an architecture for software-defined multicast that provides scalable and reliable multicast services. We consider the Bit Indexed Explicit Replication (BIER) architecture and Traffic Engineering for BIER (BIER-TE) for packet transport to mitigate scalability concerns of traditional IP multicast. We briefly discuss the advantages of an SDN-based multicast architecture leveraging BIER and...
Clustering is a common data mining procedure that groups multi-dimensional points with similar components to form different subsets. Among all of the clustering algorithms, DBSCAN is one of the most popular algorithms owing to finding clusters with arbitrary shapes and noise of datasets. However, with data volumes growing and the execution time of algorithms becoming longer, numerous methods have...
The effects of human mobility in Device-to-Device (D2D) communication are not well understood, but with the recent proliferation of D2D, communications have become a critical research emphasis. However, very little is understood on how human mobility and D2D communication are interdependent. The unpredictability of human mobility is one of the root causes in properly visualizing and designing an efficient...
Recurrent Neural Network (RNN) are a popular choice for modeling temporal and sequential tasks and achieve many state-of-the-art performance on various complex problems. However, most of the state-of-the-art RNNs have millions of parameters and require many computational resources for training and predicting new data. This paper proposes an alternative RNN model to reduce the number of parameters...
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