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Symbolic time-varying root-locus analysis for oscillator design

Symbolic time-varying root-locus analysis for oscillator des...

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Annual IEEE Northeast workshop on Circuits and Systems (NEWCAS)

作者： Yan Zhu Guoyong Shi Frank Lee Andy Tai School of Microelectronics Shanghai Jiaotong University Shanghai China Synopsys Inc. Mountain View CA USA

the small-signal analysis of an oscillator relative to a periodic steady-state (PSS) would generate periodic time-varying characteristic poles. Analyzing periodic root-loci can provide useful design information, which is not available from the existing circuit simulation tools. Although the numerical QZ algorithm can be used to generate periodic root-loci, this paper proposes an alternative symbolic computation method for repeated pole computation. It is demonstrated that the Muller algorithm can be used for finding the dominant periodic roots of a characteristic polynomial with periodic coefficients, whose efficiency is superior to the matrix-based numerical QZ method. Other advantages of symbolic root-locus analysis also are explored by applying the proposed method to the analysis of two oscillator circuits.

关键词： Oscillators data structures Boolean functions Polynomials Integrated circuit modeling Mathematical model Computational modeling

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Fuzzy c-means clustering with regularization by K-L information

Fuzzy c-means clustering with regularization by K-L informat...

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IEEE international Conference on Fuzzy Systems (FUZZ-IEEE)

作者： H. Ichihashi K. Miyagishi K. Honda Industrial Engineering Graduate School of Engineering Osaka Prefecture University Sakai Osaka Japan

the Gaussian mixture model or Gaussian mixture density decomposition(GMDD) use the likelihood function as a measure of fit. We show that just the same algorithm as the GMDD can be derived from a modified objective function of fuzzy c-means (FCM) clustering with the regularizer by K-L information, only when the parameter /spl lambda/ equals 2. Although the fixed-point iteration scheme of FCM is similar to that of the GMDD, the FCM has more flexible structure since the algorithm is based on the objective function method. In a slightly different manner such as installing a deterministic annealing or an addition of Gustafson and Kessel's (1979) constraint, the proposed algorithm is likely to provide more valid clustering results.

关键词： Clustering algorithms Annealing Phase change materials data mining Covariance matrix Fuzzy systems Industrial engineering Density measurement Flexible structures Temperature

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Energy-efficient Scheduling algorithms for data Center Resources in Cloud Computing

Energy-efficient Scheduling Algorithms for Data Center Resou...

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international workshop on Intelligent Communication and Social Networks

作者： Tamal Adhikary Amit Kumar Das Md. Abdur Razzaque A. M. Jehad Sarkar Green Networking Research Group Department of Computer Science & Engineering University of Dhaka Dept. of Digital Information Engineering College of Engineering Hankuk University of Foreign Studies

ISBN: (纸本)9781479909735

A significant amount of energy is consumed to render high-level computation tasks in large scale cloud computing applications. the state-of-the-art energy saving techniques based on centralized job placement approaches reduce the reliability of operation due to a single point of failure. Moreover, the existing works do not consider energy consumption cost for communication devices and network appliances which contribute a lot. In this paper, we have proposed a mechanism for cluster formation based on network vicinity among the data servers. We have developed two distributed and localized intra-cluster and inter-cluster VM scheduling algorithms based on energy calculation, resource requirement and availability. Our proposed scheduling algorithms manage VMs to reduce the energy consumption of both the servers and networking devices. Simulation results show that our proposed distributed VM scheduling algorithms can conserve significant amount of energy compared to state-of-the-art works.

关键词： Scheduling algorithms energy capacity Cloud Computing Single point failure energy consumption Servers communication equipment data center Voltmeter virtual machines Energy efficiency

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Business Metadata for the dataWarehouse

Business Metadata for the DataWarehouse

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international workshop on Enterprise Distributed Object Computing, EDOCW

作者： Veronika Stefanov Beate List Womens Postgraduate College for Internet Technologies Institute of Software Technology and Interactive Systems University of Technology Vienna Austria

Enterprise organizations use data Warehouses (DWHs) analyze their performance. Performance is judged regarding the achievement of goals. DWH data models are well established. there exist numerous domain-specific modeling approaches. Enterprises also often model their goals in terms of formal or semiformal goal models. the problem is that these two aspects - the data Warehouse and the Enterprise Goals - are described separately and not related to each other. We identify a need for combining these two aspects. If their relationship is made explicit, it can be used to enhance the way users access and interpret data in the DWH. To address this limitation, in this paper we introduce a weaving model between enterprise goals and DWH data. thus we present a domain-specific application of model weaving to an aspect of enterprise computing. We describe metamodels for both aspects as well as the weaving links between them, which allows to show the aspects separately but also in combination. We furthermore illustrate how to use the weaving links to create business metadata. Business metadata can be used in the DWH to describe the business context and implications of the data to the users, but is usually not available in today's DWHs. We apply our approach to a sample situation, which is used as a running example in the paper.

关键词： Weaving Context modeling data warehouses data models Information analysis Investments data structures Multidimensional systems Performance analysis Information resources

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Secure Textual data Deduplication Scheme Based on data Encoding and Compression

Secure Textual Data Deduplication Scheme Based on Data Encod...

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international Conference and workshop on Computing and Communication (IEMCON)

作者： Ali Miri Fatema Rashid Computer Science Ryerson University Toronto Canada

ISBN: (纸本)9781728125312

As the need for storage has grown exponentially in recent years, cloud storage has been providing a solution to this need by providing users expanded capacity and access. Providing adequate security and privacy, and lowering storage costs are some of the key challenges facing this solution. A common practice used by cloud service providers (CSPs)-data deduplication - identifies identical copies of users' data, and removing all, but one copy to lower required storage overhead. However, this can result in serious privacy concerns. In this paper, we formulate a new secure deduplication scheme for textual data. Our proposed method uses data encoding and compression techniques that not only result in reduce storage space required, but also in saving in required transmission bandwidth. the security of the data against the semi-honest CSP and malicious users is ensured by using Burrows Wheel Transform encoding scheme. the encoded data is further compressed to gain effective savings in terms of storage and reduced size of the data. data encoding and data compression techniques are combined together to realize secure and efficient data deduplication. through our scheme, the CSP will not only achieve huge storage space savings through data compression and data deduplication, but can also provide the users a satisfactory level of security for their data in the cloud.

关键词： Encoding Encryption Cloud computing Servers Compression algorithms

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A Multi-dimensional Packet Classification Algorithm Based on Hierarchical All-Match B+ Tree

A Multi-dimensional Packet Classification Algorithm Based on...

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IEEE international Conference on High Performance Computing and Communications (HPCC)

作者： Gang Wang Yaping Lin Jinguo Li Xin Yao College of Information Science and Engineering Hunan University Changsha China

Packet classification is one of the most important enabling functions for network services. the previous trie-based hierarchical search structure suffers from backtracking and address length. this paper proposes a multi-dimensional packet classification algorithm based on hierarchical all-match B+tree. By utilizing the property that the IP prefixes of a rule set are nested to each other, we develop an all-match prefix tree (APT) based on B+tree and propose a two-stage hierarchical search structure HAPT. We further propose the packet classification and rule update algorithms on HAPT. By performing multi-way search without backtracking, the proposed classification algorithm can classify packets in O(logmN) and update rules in O(mlogmN). Furthermore, the proposed algorithm is suitable for both IPv4 and IPv6. theoretical analysis and evaluation results show that the proposed multi-dimensional packet classification algorithm improves the speed by a factor of 2-4 compared to state-of-the-art algorithm H-trie.

关键词： Classification algorithms IP networks Algorithm design and analysis data structures Time complexity Indexes

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the 10th CASCON workshop on cloud computing 18

The 10th CASCON workshop on cloud computing

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Proceedings of the 28th Annual international Conference on Computer Science and Software Engineering

作者： Marin Litoiu Joe Wigglesworth

In the last decade we have seen a dramatic change of the IT landscape. Cloud computing has changed the way the applications are developed, deployed and operated. At the same time, new application domains such as Internet of things (IoT) add new requirements for cloud, such as new cloud architectures, guarantee requirements for performance, privacy and security. IoT are families of technologies, protocols, software and algorithms that enable sensor-embedded-objects such as city infrastructure, buildings, farms, factories, appliances, health and personal accessories to connect to the Internet, push data and pull commands from cloud. the data emitted by sensors-enabled objects can be archived on the cloud, where it is fused and analyzed to make inferences that can be used to adapt the same objects or their environments. IoT technologies are key enablers for building new applications in a variety of domains, such as autonomous vehicles, automated farms, automated manufacturing, smart cities and buildings, and personalized healthcare [2],[3].

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Learning Bayesian Networks by Evolution for Classifier Combination

Learning Bayesian Networks by Evolution for Classifier Combi...

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international Conference on Document Analysis and Recognition

作者： Claudio De Stefano Francesco Fontanella Alessandra Scotto di Freca Angelo Marcelli Universita degli Studi di Cassino e del Lazio Meridionale Cassino Lazio IT DAEIMI Universita’ di Cassino Cassino FR Italy DAEIMI Univ. di Cassino Cassino Italy DIIIE Universita’ di Salerno Fisciano SA Italy

Combining classifier methods have shown their effectiveness in a number of applications. Nonetheless, using simultaneously multiple classifiers may result in some cases in a reduction of the overall performance, since the responses provided by some of the experts may generate consensus on a wrong decision even if other experts provided the correct one. To reduce these undesired effects, in a previous study, we proposed a combining method based on the use of a Bayesian Network. In this paper, we present an improvement of that method which allows to solve some of the drawbacks exhibited by standard learning algorithms for Bayesian Networks. the proposed method is based on an Evolutionary Algorithm which uses a specifically devised data structure to encode direct acyclic graphs. this data structure allows to effectively implement crossover and mutation operators. the experimental results, obtained by using three standard databases, confirmed the effectiveness of the method.

关键词： Bayesian methods Probability distribution data structures Evolutionary computation Pattern recognition Text analysis Genetic mutations databases Machine learning Weight measurement

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3D reconstruction and virtual exploration of submerged structures: A case study in the underwater archaeological site of Baia (Italy)

3D reconstruction and virtual exploration of submerged struc...

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13th international Symposium on Virtual Reality, Archaeology, and Cultural Heritage, VAST 2012 - 10th EUROGRAPHICS workshop on Graphics and Cultural Heritage

作者： Gallo, A. Angilica, A. Bianco, G. De Filippo, F. Muzzupappa, M. Davidde, B. Bruno, F. Italy ISCR Istituto Superiore per la Conservazione Ed Il Restauro Rome Italy

ISBN: (纸本)9783905674392

the 3D reconstruction of underwater scenes is almost a requirement for a number of applications that need to gather 3D data from fauna, flora or submerged structures. In the Cultural Heritage field, 3D models of finds and archaeological sites are widely used, either for scientific research or for dissemination to the public. 3D imaging techniques based on multi-view capture are a valid and effective tool in underwater applications, because they require to capture the scene by different viewpoints using just one still or movie camera, installed on robots or handled by a scuba diver. In this paper we test a technique for 3D reconstructions from images captured by multiple views in a case study of submerged structures in the underwater archaeological site of Baia (Italy). this case study is particularly critical due to the high level of turbidity, the heavy presence of marine flora and the changing of lighting conditions, common in shallow water. All these disturbances cause a decrease of the contrast and an alteration of the colours in the acquired images. the 3D model of a portion of the site has been reconstructed in a virtual environment, both for studying and dissemination fruition purposes. In particular, a 3D application has been developed in order to allow the exploration of the site, the measurement of the architectonical elements and the simulation of the movements of a robot that performs specific operations of restoration and preservation. © the Eurographics Association 2012.

关键词： Virtual reality

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Accurate Detection of Superspreaders on Multi-Pipeline Switches

Accurate Detection of Superspreaders on Multi-Pipeline Switc...

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international Conference on Computer and Communications (ICCC)

作者： Cenman Wang Bowen Zheng Fan Yang Ye Tian Anhui Key Laboratory on High Performance Computing School of Computer Science and Technology University of Science and Technology of China Hefei China

ISBN: (数字)9798331507077

ISBN: (纸本)9798331507084

In various network monitoring tasks, the detection of superspreaders has become increasingly crucial. However, latest superspreader detection algorithms and data structures assume the target switch with a single pipeline, while state-of-the-art programmable switches actually comprise multiple independent pipelines. In current method for deploying super-spreader detection applications on multi-pipeline switches, a separate measurement data structure instance is employed for each pipeline. However, under multi-path routing, this simplistic approach leads to lower detection accuracy due to hash collisions. To address this issue, in this paper, we present PipelineAlloc, a HyperLogLog-based superspreader detection system designed for multi-pipeline switches. In order to reduce hash collisions in measurement data structures, PipelineAlloc assigns an egress pipeline as the monitor pipeline for each source IP address. PipelineAlloc introduces novel measurement data structures in the ingress pipelines for temporarily storing statistics of the source and destination IP addresses of packets, and uses packets to carry these measurement data to egress pipelines, which serve as the monitor pipelines. the HyperLogLog-based measurement data structures in egress pipelines are updated using data carried by packets. Experiments driven by real-world traffic traces show that PipelineAlloc outperforms existing solutions in terms of detection accuracy.

关键词： Accuracy Scalability Current measurement Pipelines Switches data structures Routing IP networks Detection algorithms Monitoring

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