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10th international AAAI Conference on Web and Social Media, ICWSM 2016

作者： Dallmann, Alexander Lemmerich, Florian Niebler, thomas Hotho, Andreas Data Mining and Information Retrieval Group University of Würzburg Germany GESIS - Leibniz Institute for Social Sciences Germany Data Mining and Information Retrieval Group University of Würzburg and L3S Hannover Germany

ISBN: (纸本)9781577357681

Semantic relatedness between words has been extracted from a variety of sources. In this ongoing work, we explore and compare several options for determining if semantic relatedness can be extracted from navigation structures in Wikipedia. In that direction, we first investigate the potential of representation learning techniques such as DeepWalk in comparison to previously applied methods based on counting co-occurrences. Since both methods are based on (random) paths in the network, we also study different approaches to generate paths from Wikipedia link structure. For this task, we do not only consider the link structure of Wikipedia, but also actual navigation behavior of users. Finally, we analyze if semantics can also be extracted from smaller subsets of the Wikipedia link network. As a result we find that representation learning techniques mostly outperform the investigated co-occurrence counting methods on the Wikipedia network. However, we find that this is not the case for paths sampled from human navigation behavior. ©2016, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Semantics

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Type-driven data layouts for improved vectorisation

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2016年第7期28卷 2092-2119页

作者： Sinkarovs, Artjoms Scholz, Sven-Bodo Heriot Watt Univ Sch Math & Comp Sci Edinburgh EH14 4AS Midlothian Scotland

Vector instructions of modern CPUs are crucially important for the performance of compute-intensive algorithms. Auto-vectorisation often fails because of an unfortunate choice of data layout by the programmer. this paper proposes a data layout inference for auto-vectorisation that identifies layout transformations that convert single instruction, multiple data-unfavourable layouts of data structures into favourable ones. We present a type system for layout transformations, and we sketch an inference algorithm for it. Finally, we present some initial performance figures for the impact of the inferred layout transformations. they show that non-intuitive layouts that are inferred through our system can have a vast performance impact on compute intensive programs. Copyright (c) 2015 John Wiley & Sons, Ltd.

关键词： vectorisation data parallelism hpc

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Unsupervised multi scale anomaly detection in streams of events

Unsupervised multi scale anomaly detection in streams of eve...

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international Conference on Signal Processing and Communication Systems, ICSPCS

作者： Quentin Plessis Masaki Suzuki Takeshi Kitahara KDDI R&D Laboratories Inc. Saitama Japan

ISBN: (纸本)9781509009428

Automatically detecting anomalies in streams of events is crucial for many applications in communications, security, healthcare, finance and real-time systems. In communication systems, it can be used to forecast equipment breakdowns or to detect unprecedented issues that do not trigger any alarms. Several methods have been proposed to detect anomalies in streams of events but they are not suited to detect large-scale anomalies with different durations and features. In this paper, we first propose a new data structure called s-digest to learn the distributions of values originating from streams of events for multiple time-scales. the structure is then used to conceive an unsupervised multi-scale method able to detect anomalies with different durations and characteristics. the method withstands high-throughput streams of events, is highly scalable and memory efficient. We then simulate a mobile network based on actual data from a commercial LTE network and apply our method to detect various anomalies and prove its accuracy and practicability.

关键词： data structures Mobile computing Mobile communication Memory management Context Approximation algorithms Algorithm design and analysis

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Application of Acceleration-based Damage Detection algorithms to Experimental data from Multi-story Steel structures 10

Application of Acceleration-based Damage Detection Algorithm...

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10th international workshop on Structural Health Monitoring (IWSHM)

作者： Liao, Yizheng Balafas, Konstantinos Kiremidjian, Anne Rajagopal, Ram Loh, Chin-Hsiung Stanford Univ Dept Civil & Environm Engn Stanford CA 94305 USA Natl Taiwan Univ Dept Civil Engn Taipei 10617 Taiwan

ISBN: (纸本)9781605952758

this paper presents a recent shake table experiment on two three-story steel frame structures with controllable damage. the performance and accuracy of SnowFort, a wireless infrastructure monitoring system, were tested. By analyzing the data, we show that this new system achieves the same accuracy as the wired sensing units. In addition, a structural damage detection algorithm based on Continuous Wavelet Transform was validated based on the experimental data.

关键词： Damage detection

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PSRna: Prediction of small RNA secondary structures based on reverse complementary folding method

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JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY 2016年第4期14卷 1643001-1643001页

作者： Li, Jin Xu, Chengzhen Wang, Lei Liang, Hong Feng, Weixing Cai, Zhongxi Wang, Ying Cong, Wang Liu, Yunlong Harbin Engn Univ Coll Automat Harbin Peoples R China Indiana Univ Sch Med Ctr Computat Biol & Bioinformat 410 West 10th StSuite 5000 Indianapolis IN 46202 USA

Prediction of RNA secondary structures is an important problem in computational biology and bioinformatics, since RNA secondary structures are fundamental for functional analysis of RNA molecules. However, small RNA secondary structures are scarce and few algorithms have been specifically designed for predicting the secondary structures of small RNAs. Here we propose an algorithm named "PSRna" for predicting small-RNA secondary structures using reverse complementary folding and characteristic hairpin loops of small RNAs. Unlike traditional algorithms that usually generate multi-branch loops and 50 end self-folding, PSRna first estimated the maximum number of base pairs of RNA secondary structures based on the dynamic programming algorithm and a path matrix is constructed at the same time. Second, the backtracking paths are extracted from the path matrix based on backtracking algorithm, and each backtracking path represents a secondary structure. To improve accuracy, the predicted RNA secondary structures are filtered based on their free energy, where only the secondary structure with the minimum free energy was identified as the candidate secondary structure. Our experiments on real data show that the proposed algorithm is superior to two popular methods, RNAfold and RNAstructure, in terms of sensitivity, specificity and Matthews correlation coefficient (MCC).

关键词： Small RNA PSRna reverse complementary fold secondary structure path matrix

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A hardware-accelerated infrastructure for flexible sketch-based network traffic monitoring

A hardware-accelerated infrastructure for flexible sketch-ba...

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IEEE workshop on High Performance Switching and Routing

作者： theophilus Wellem Yu-Kuen Lai Chao-Yuan Huang Wen-Yaw Chung Department of Informatics Satya Wacana Christian University Salatiga Indonesia Department of Electronic Engineering Chung Yuan Christian University Zhongli Taiwan Department of Electrical Engineering Chung Yuan Christian University Zhongli Taiwan

ISBN: (纸本)9781479989515

Sketch-based data streaming algorithms are used in many network traffic monitoring applications to obtain accurate estimates of traffic flow. However, the flexibility is limited as hardware implementation of sketch counters may not be re-used for different measurement tasks. In this paper, we develop a generic hardware infrastructure for collecting flow statistics. the purpose is to achieve the goal of adopting various sketch-based algorithms with arbitrary flow aggregations for monitoring applications and measurement tasks in a flexible manner. Multiple-choice hashing with linear probing scheme is utilized for high-speed counter update process. Simulation results based on real traffic traces for monitoring applications are presented. the proposed hardware infrastructure is implemented on the NetFPGA-10G platform. the system is capable of processing network traffic at 53 Gbps in a worst-case scenario of 64-byte minimum-sized Ethernet frame.

关键词： Radiation detectors Monitoring Probes Hardware Random access memory data structures IP networks

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Computer Guided Product EMC Compliance on User's workshop by Means of Cloud Computing - Methodologies and algorithms 10

Computer Guided Product EMC Compliance on User's Workshop by...

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10th IEEE international Conference on Industrial and Information Systems (ICIIS)

作者： Wu, Wei Wu, Yuejia WEIWU INFO Inst Innovat Lisbon Portugal Zhoushan Puhua Elec Info Tech LTD Dept Cloud Comp Technol Zhoushan Peoples R China

ISBN: (纸本)9781479918768

All products are obligated to pass Electromagnetic Compatibility (EMC) tests before sale. Due to the uncertainty of Electromagnetic Interference (EMI) location in product, the product EMC compliance is expensive and time consuming. In this paper we present a novel solution to assist industrial users in product EMC compliance, which is a public Computer Aided EMC compliance service platform in Cloud, accessible through Internet by Desktop, Laptop, Pad or Smart Phone. the industrial users may measure voltage signals on EUT with a general-purpose oscilloscope, and upload the data to platform where the data are analyzed and the analysis results indicate the EMI location and EMI level on EUT, to guide users efficiently and effectively modify EUT to approach EMC compliance. It is low cost and easy to use, users only pay the Computing time in Cloud, no software installation, no operation skill and no EMC expertise are required. Methodologies and algorithms of proposed solution are introduced, and illustrated by example.

关键词： EMf EMC CAD SAAS Cloud Computing

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10th international workshop on databases in Networked Information Systems, DNIS 2015

10th International Workshop on Databases in Networked Inform...

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10th international workshop on databases in Networked Information Systems, DNIS 2015

ISBN: (纸本)9783319163123

the proceedings contain 21 papers. the special focus in this conference is on Big data Analysis, Knowledge Management, Business data Analytics and Visualization. the topics include: Discovering chronic-frequent patterns in transactional databases;high utility rare itemset mining over transaction databases;synthetic evidential study as primordial soup of conversation;interactive tweaking of text analytics dashboards;covariance structure and systematic risk of market index portfolio;moving from relational data storage to decentralized structured storage system;comparing infrastructure monitoring with cloud stack compute services for cloud computing systems;a large sky survey project and the related big data analysis;query languages for domain specific information from PTF astronomical repository;mining business process logs for root cause analysis of anomalous incidents;modeling personalized recommendations of unvisited tourist places using genetic algorithms and a decentralised approach to computer aided teaching via interactive documents.

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10th international Symposium on algorithms and Experiments for Sensor Systems, Wireless Networks and Distributed Robotics, ALGOSENSORS 2014

10th International Symposium on Algorithms and Experiments f...

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10th international Symposium on algorithms and Experiments for Sensor Systems, Wireless Networks and Distributed Robotics, ALGOSENSORS 2014

ISBN: (纸本)9783662460177

the proceedings contain 13 papers. the special focus in this conference is on Robot Planning, data structures on Graphs and Wireless Networks. the topics include: Multi robot foremost coverage of time-varying graphs;strategies for parallel unaware cleaners;minimum-traveled-distance gathering of oblivious robots over given meeting points;computing the dynamic diameter of non-deterministic dynamic networks is hard;improved spanners in networks with symmetric directional antennas and minimum latency aggregation scheduling in wireless sensor networks.

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Application of Function Points and data Mining Techniques for Software Estimation - A Combined Approach 1

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25th international workshop on Software Measurement / 10th international Conference on Software Process and Product Measurement (IWSM-Mensura)

作者： Pospieszny, Przemyslaw Czarnacka-Chrobot, Beata Kobylinski, Andrzej Warsaw Sch Econ Inst Informat Syst & Digital Econ PL-02513 Warsaw Poland

ISBN: (数字)9783319242859

ISBN: (纸本)9783319242859;9783319242842

Project estimation is recognized as one of the most challenging processes in software project management on which project success is dependable. Traditional estimation methods based on expert knowledge and analogy tend to be error prone and deliver overoptimistic assessments. Methods derived from function points are good sizing tools but do not reflect organizations' specific project management culture. Due to those deficiencies in recent years data mining techniques are explored as an alternative estimation method. the aim of this paper is to present a combined approach of functional sizing measurement and three data mining techniques for effort and duration estimation at project early stages: generalized linear models, artificial neural networks and CHAID decision trees. the estimation accuracy of these models is compared in order to determine their potential usefulness for deployment within organizations. Moreover a merged approach of combining algorithms' results is proposed in order to increase prediction accuracy and overcome possibility of overfitting occurrence.

关键词： Project estimation Effort and duration estimation Software measurement Functional size measurement Function points data mining Predictive algorithms

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