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19th International Conference on Information Integration and Web-Based Applications and Services, iiWAS2017

作者： Babalou, Samira Algergawy, Alsayed Lantow, Birger König-Ries, Birgitta Heinz-Nixdorf for Distributed Information Systems Friedrich Schiller University of Jena Germany Institute of Computer Science University of Rostock Germany

ISBN: (纸本)9781450352994

In an age where science is often interdisciplinary, it is frequently necessary to combine scientific data from different (sub-)disciplines and thus from different sources. Ontologies can play an important role in this integration process. However, existing ontologies will either cover just a part of the domain of interest or competing ontologies modeling the domain from different viewpoints exist. Therefore, before being able to leverage the power of ontologies, they themselves need to be integrated. The core of ontology integration is a mapping operation to identify corresponding concepts. This is a challenging task. To this end, we present a high-level integration workflow as a clear guideline for the whole process of ontology integration. We then analyze the mapping sub-workflow in more detail. We identify open issues in this integration step and discuss the ensuing challenges. © 2017 Association for Computing Machinery.

关键词： Ontology

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Large margin multi-modal multi-task feature extraction for image classification

arXiv

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arXiv 2019年

作者： Luo, Yong Wen, Yonggang Tao, Dacheng Gui, Jie Xu, Chao School of Electronics Engineering and Computer Science Peking University Beijing China Division of Networks and Distributed Systems School of Computer Engineering Nanyang Technological University Singapore Centre for Quantum Computation & Intelligent Systems Faculty of Engineering & Information Technology University of Technology Sydney Sydney Australia Centre for Quantum Computation & Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney 81 Broadway Street UltimoNSW2007 Australia Hefei Institute of Intelligent Machines Chinese Academy of Sciences Hefei230031 China Center for Research on Intelligent Perception and Computing National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing100190 China

The features used in many image analysis-based applications are frequently of very high dimension. Feature extraction offers several advantages in high-dimensional cases, and many recent studies have used multi-task feature extraction approaches, which often outperform single-task feature extraction approaches. However, most of these methods are limited in that they only consider data represented by a single type of feature, even though features usually represent images from multiple modalities. We therefore propose a novel large margin multi-modal multi-task feature extraction (LM3FE) framework for handling multi-modal features for image classification. In particular, LM3FE simultaneously learns the feature extraction matrix for each modality and the modality combination coefficients. In this way, LM3FE not only handles correlated and noisy features, but also utilizes the complementarity of different modalities to further help reduce feature redundancy in each modality. The large margin principle employed also helps to extract strongly predictive features so that they are more suitable for prediction (e.g., classification). An alternating algorithm is developed for problem optimization and each sub-problem can be efficiently solved. Experiments on two challenging real-world image datasets demonstrate the effectiveness and superiority of the proposed method. Copyright © 2019, The Authors. All rights reserved.

关键词： Feature extraction

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A testing framework architecture concept for automotive intrusion detection systems 7

A testing framework architecture concept for automotive intr...

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7. Tagung Automotive " Safety and Security 2017: Sicherheit und Zuverlassigkeit fur Automobile Informationstechnik - 7th Conference on Automotive - Safety and Security 2017: Safety and Reliability for Automotive Information Technology

作者： Corbett, Christopher Basic, Tobias Lukaseder, Thomas Kargl, Frank Audi AG Ingolstadt85045 Germany TU Darmstadt Department of Computer Science Germany Ulm University Institute of Distributed Systems Germany

ISBN: (纸本)9783885796633

Vehicles are the target of a rising number of hacking attacks. The integration of in-vehicle intrusion detection systems is a common approach to increase the overall system security. However' testing and evaluating these systems is difficult due to the lack of tools to generate realistic benign and malicious workloads as well as sharing these workloads with other researchers. Currently' testing tools are predominantly intended for Network Intrusion Detection System (NIDS) in company or industrial networks where their usefulness became apparent. Yet' in the automotive domain' development of testing tools is still in the early stages. Existing non-commercial automotive tools only focuson one specific bus technology each. However' in-vehicle communication exceeds bus technologyboundaries and a testing tool must cover multiple technologies. We propose a framework architecture concept for in-vehicle NIDS testing and evaluation to enable the creation of realistic network traffic and attacks in consideration of automotive specific challenges. Our concept provides the opportunity to share data without additional anonymization effort therefore improving cooperation and reproducibility of testing results.

关键词： Vehicles

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Frame-based behavior preservation in refactoring 24

Frame-based behavior preservation in refactoring

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24th IEEE International Conference on Software Analysis, Evolution, and Reengineering, SANER 2017

作者： Maruyama, Katsuhisa Hayashi, Shinpei Yoshida, Norihiro Choi, Eunjong Department of Computer Science Ritsumeikan University Japan Department of Computer Science Tokyo Institute of Technology Japan Center for Embedded Computing Systems Nagoya University Japan Graduate School of Information Science Nara Institute of Science and Technology Japan

ISBN: (纸本)9781509055012

Behavior preservation often bothers programmers in refactoring. This poster paper proposes a new approach that tames the behavior preservation by introducing the concept of a frame. A frame in refactoring defines stakeholder's individual concerns about the refactored code. Frame-based refactoring preserves the observable behavior within a particular frame. Therefore, it helps programmers distinguish the behavioral changes that they should observe from those that they can ignore. © 2017 IEEE.

关键词： Libraries Registers computer science Testing Stakeholders embedded computing Information science

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Latency Reduction in Narrowband 4G LTE Networks

Latency Reduction in Narrowband 4G LTE Networks

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International Symposium on Wireless Communication systems (ISWCS)

作者： Zubair Amjad Axel Sikora Jean-Philippe Lauffenburger Benoit Hilt Institute of Reliable Embedded Systems and Communication Electronics (ivESK) Offenburg University of Applied Sciences Offenburg Germany Institute of Research in Computer Science Mathematics Control and Signals (IRIMAS) University of Haute Alsace Mulhouse France

The next generation cellular networks are expected to improve reliability, energy efficiency, data rate, capacity and latency. Originally, Machine Type Communication (MTC) was designed for low-bandwidth high-latency applications such as, environmental sensing, smart dustbin, etc., but there is additional demand around applications with low latency requirements, like industrial automation, driver-less cars, and so on. Improvements are required in 4G Long Term Evolution (LTE) networks towards the development of next generation cellular networks for providing very low latency and high reliability. To this end, we present an in-depth analysis of parameters that contribute to the latency in 4G networks along with a description of latency reduction techniques. We implement and validate these latency reduction techniques in the open-source network simulator (NS3) for narrowband user equipment category Cat-Ml (LTE-M) to analyze the improvements. The results presented are a step towards enabling narrowband Ultra Reliable Low Latency Communication (URLLC) networks.

关键词： Long Term Evolution Uplink Dynamic scheduling 3GPP Delays Reliability Narrowband

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A deep learning-based approach for banana leaf diseases classification

A deep learning-based approach for banana leaf diseases clas...

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Datenbanksysteme fur Business, Technologie und Web, BTW 2017 Workshopband - Database systems for Business, Technology and Web, BTW 2017 Workshop

作者： Amara, Jihen Bouaziz, Bassem Algergawy, Alsayed MIRACL Laboratory Tunisia MIRACL Laboratory Higher Institute of Computer Science and Multimedia University of Sfax Tunisia Institute for Computer Science Friedrich-Schiller University of Jena Heinz-Nixdorf for distributed information systems Germany

ISBN: (纸本)9783885796602

Plant diseases are important factors as they result in serious reduction in quality and quantity of agriculture products. Therefore, early detection and diagnosis of these diseases are important. To this end, we propose a deep learning-based approach that automates the process of classifying banana leaves diseases. In particular, we make use of the LeNet architecture as a convolutional neural network to classify image data sets. The preliminary results demonstrate the effectiveness of the proposed approach even under challenging conditions such as illumination, complex background, different resolution, size, pose, and orientation of real scene images. © 2017 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： Classification (of information)

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Decoding Interleaved Gabidulin Codes using Alekhnovich's Algorithm

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Electronic Notes in Discrete Mathematics 2017年 57卷 175-180页

作者： Puchinger, Sven Müelich, Sven Mödinger, David Rosenkilde né Nielsen, Johan Bossert, Martin Institute of Communications Engineering Ulm University Ulm Germany Institute of Distributed Systems Ulm University Ulm Germany Department of Applied Mathematics & Computer Science Technical University of Denmark Lyngby Denmark

We prove that Alekhnovich's algorithm can be used for row reduction of skew polynomial matrices. This yields an O(ℓ3n(ω+1)/2log⁡(n)) decoding algorithm for ℓ-Interleaved Gabidulin codes of length n, where ω is t... 详细信息

We prove that Alekhnovich's algorithm can be used for row reduction of skew polynomial matrices. This yields an O(ℓ³n^(ω+1)/2log⁡(n)) decoding algorithm for ℓ-Interleaved Gabidulin codes of length n, where ω is the matrix multiplication exponent. © 2017 Elsevier B.V.

关键词： Characteristic Zero Gabidulin Codes Low-Rank Matrix Recovery

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Real-time low SNR signal processing for nanoparticle analysis with deep neural networks 11

Real-time low SNR signal processing for nanoparticle analysi...

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11th International Conference on Bio-Inspired systems and Signal Processing, BIOSIGNALS 2018 - Part of 11th International Joint Conference on Biomedical Engineering systems and Technologies, BIOSTEC 2018

作者： Lenssen, Jan Eric Toma, Anas Seebold, Albert Shpacovitch, Victoria Libuschewski, Pascal Weichert, Frank Chen, Jian-Jia Hergenröder, Roland CS VII - Computer Graphics TU Dortmund University Otto-Hahn-Straße 16 Dortmund44227 Germany CS XII - Embedded Systems TU Dortmund University Otto-Hahn-Straße 16 Dortmund44227 Germany Leibniz-Institute for Analytical Science ISAS e.V. Bunsen-Kirchhoff-Straße 11 Dortmund44139 Germany

ISBN: (纸本)9789897582790

In this work, we improve several steps of our PLASMON ASSISTED MICROSCOPY OF NANO-SIZED OBJECTS (PAMONO) sensor data processing pipeline through application of deep neural networks. The PAMONO-biosensor is a mobile nanoparticle sensor utilizing SURFACE PLASMON RESONANCE (SPR) imaging for quantification and analysis of nanoparticles in liquid or air samples. Characteristics of PAMONO sensor data are spatiotemporal blob-like structures with very low SIGNAL-TO-NOISE RATIO (SNR), which indicate particle bindings and can be automatically analyzed with image processing methods. We propose and evaluate deep neural network architectures for spatiotemporal detection, time-series analysis and classification. We compare them to traditional methods like frequency domain or polygon shape features classified by a Random Forest classifier. It is shown that the application of deep learning enables our data processing pipeline to automatically detect and quantify 80 nm polystyrene particles and pushes the limits in blob detection with very low SNRs below one. In addition, we present benchmarks and show that real-time processing is achievable on consumer level desktop GRAPHICS PROCESSING UNITs (GPUs). Copyright © 2018 by SCITEPRESS – science and Technology Publications, Lda. All rights reserved.

关键词： Signal to noise ratio

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Demo Abstract: Panoptes: A Cheap, Extensible, Open-Source Multi-camera Tracking System

Demo Abstract: Panoptes: A Cheap, Extensible, Open-Source Mu...

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International Symposium on Information Processing in Sensor Networks (IPSN)

作者： Manomit Bal Javier Yu Karthik Dantu Distributed Robotics and Networked Embedded Systems Lab (DRONES) Computer Science and Engineering University at Buffalo

ISBN: (纸本)9781467391474

We are developing an extensible, open-source framework that can localize and track rigid bodies using a network of cameras (both RGB and depth). This system is motivated by two design goals - (i) ease of setup, and (ii) ability to be agnostic of individual cameras and recognition algorithms. The goal of this implementation is to be a poor man's motion capture system that can be quickly set up for experimentation and provide accurate 3-D pose of the rigid body and scalable across cameras and the volume of coverage.

关键词： Cameras Robot sensing systems Three-dimensional displays Feature extraction Libraries Calibration Open source software

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SARRC: Secure Auditing and Re-signing of Revoked Customer Chunks by Cloud Using Regression Method

SARRC: Secure Auditing and Re-signing of Revoked Customer Ch...

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Information Processing (ICINPRO), International Conference on

作者： C M Geeta Usharani R G Shreyas Raju S Raghavendra Rajkumar Buyya K R Venugopal S S Iyengar L M Patnaik Department of Computer Science and Engineering University Visvesvaraya College of Engineering Bangalore University Cloud Computing and Distributed Systems (CLOUDS) Lab The University of Melbourne Australia Bangalore University Bengaluru India Department of Computer Science and Engineering Florida International University USA INSA National Institute of Advanced Studies Indian Institute of Science Campus Bangalore India

ISBN: (数字)9781538677964

ISBN: (纸本)9781538677971

The demand of deploying information has enormously increased within the last decade. Numerous distributed computing service suppliers have emerged (for eg., Microsoft Azure, Dropbox) in order to satisfy the requirements for information repository and high performance computation. The customers using the cloud repository services can conveniently arrange as a cluster and distribute information among themselves. Information proprietor computes the signatures for every chunk and deploys in the distributed server in order to allow the public verifier to perform public integrity verification on the information stored on the cloud server. In Panda scheme [1], by using the proxy re-signatures, Cloud Service Provider (CSP) verifies and re-signs the revoked customer chunks in favor of the existing customers. The malicious CSP might use the Resign key deliberately to transform the signature of one customer to another. Apart from this, conspiracy amidst the mischievous cloud server and the repudiated customer reveals the private key information of the customers present in the cluster. We propose Secure Auditing and Re-signing of Revoked Customer Chunks by Cloud Using Regression Method. Re-key computed by the information proprietor using regression method is highly secure and the mischievious cloud cannot detect the private information of the customers in the cluster. Our mechanism is collusion resistant, reduces computation cost of re-sign key by information proprietor and in addition CSP securely performs auditing and re-signing of repudiated customer chunks.

关键词： Servers Cloud computing Transforms Resistance computer science Authentication

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