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Forum on Specification, Verification and Design Languages, FDL

作者： Vladimir Herdt Daniel Große Rolf Drechsler Christoph Gerum Alexander Jung Joscha-Joel Benz Oliver Bringmann Michael Schwarz Dominik Stoffel Wolfgang Kunz Institute of Computer Science University of Bremen Bremen Germany Embedded Systems Department Eberhard-Karls-University of Tuebingen Tuebingen Germany Department of Electrical and Computer Engineering University of Kaiserslautern Kaiserslautern Germany

Small embedded devices are highly specialized plat forms that integrate several peripherals alongside the CPU core. embedded devices extensively rely on Firmware (FW) to control and access the peripherals as well as other important functionality. This poses challenges to FW development since the FW must be adapted to each specific device configuration. Besides ensuring functional correctness to avoid errors and security vulnerabilities, an important design factor today is the control and adaptivity of a system with respect to non-functional properties, like for example application-specific timing budgets. Furthermore, optimizations of the FW and HW/SW interface play a very important role due to the tight resource constraints of small embedded devices. To satisfy these requirements new FW design methods are needed targeting FW generation, FW verification and FW *** paper presents such new methods to enable an early, efficient and systematic FW design taking the underlying HW architecture into account. We use the RISC-V Instruction Set Architecture (ISA) as a case study to demonstrate our methods.

关键词： Timing Pipelines Analytical models Optimization Context modeling Benchmark testing

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MovCloud: A Cloud-enabled Framework to Analyse Movement Behaviors

MovCloud: A Cloud-enabled Framework to Analyse Movement Beha...

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IEEE International Conference on Cloud Computing Technology and science

作者： Shreya Ghosh Soumya K Ghosh Rajkumar Buyya Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Indian Institute of Technology Kharagpur Kharagpur India Cloud Computing and Distributed Systems (CLOUDS) Lab The University of Melbourne Australia

Understanding human interests and intents from movement data are fundamental challenges for any location-based service. With the pervasiveness of sensor embedded smartphones and wireless networks and communication, the availability of spatio-temporal mobility trace (timestamped location information) is increasingly growing. Analysing these huge amount of mobility data is another major concern. This paper proposes a cloud-based framework named MovCloud to efficiently manage and analyse mobility data. Specifically, the framework presents a hierarchical indexing schema to store trajectory data in different spatio-temporal resolution, clusters the trajectories based on semantic movement behaviour instead of only raw latitude, longitude point and resolves mobility queries using MapReduce paradigm. MovCloud is implemented over Google Cloud Platform (GCP) and an extensive set of experiments on real-life data yield the effectiveness of the proposed framework. MovCloud has achieved ～ 28% better clustering accuracy and also executed three times faster than the baseline methods.

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Recognition of patient groups with sleep related disorders using bio-signal processing and deep learning

arXiv

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arXiv 2021年

作者： Jarchi, Delaram Andreu-Perez, Javier Kiani, Mehrin Vysata, Oldrich Kuchynka, Jiri Prochazka, Ales Sanei, Saeid Smart Health Technologies Group School of Computer Science and Electronic Engineering University of Essex ColchesterCO4 3SQ United Kingdom Embedded and Intelligent Systems Laboratory School of Computer Science and Electronics University of Essex ColchesterCO4 3SQ United Kingdom Department of Computing and Control Engineering University of Chemistry and Technology in Prague Prague 6166 28 Czech Republic Department of Neurology Faculty of Medicine in Hradec Králové Charles University Hradec Králové500 05 Czech Republic Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague 6160 00 Czech Republic School of Science and Technology Nottingham Trent University NottinghamNG11 8NS United Kingdom

Accurately diagnosing sleep disorders is essential for clinical assessments and treatments. Polysomnography (PSG) has long been used for detection of various sleep disorders. In this research, electrocardiography (ECG) and electromayography (EMG) have been used for recognition of breathing and movement-related sleep disorders. Bio-signal processing has been performed by extracting EMG features exploiting entropy and statistical moments, in addition to developing an iterative pulse peak detection algorithm using synchrosqueezed wavelet transform (SSWT) for reliable extraction of heart rate and breathing-related features from ECG. A deep learning framework has been designed to incorporate EMG and ECG features. The framework has been used to classify four groups: healthy subjects, patients with obstructive sleep apnea (OSA), patients with restless leg syndrome (RLS) and patients with both OSA and RLS. The proposed deep learning framework produced a mean accuracy of 72% and weighted F1 score of 0.57 across subjects for our formulated four-class problem. © 2021, CC BY-NC-ND.

关键词： Wavelet transforms

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Characterizing and optimizing Java-based HPC applications on Intel many-core architecture

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science China(Information sciences) 2017年第12期60卷 207-223页

作者： Yang YU Tianyang LEI Haibo CHEN Binyu ZANG School of Computer Science Fudan University Institute of Parallel and Distributed Systems Shanghai Jiao Tong University

The increasing demand for performance has stimulated the wide adoption of many-core accelerators like IntelR Xeon PhiTMCoprocessor, which is based on Intel’s Many Integrated Core architecture. While many HPC applications running in native mode have been tuned to run efficiently on Xeon Phi, it is still unclear how a managed runtime like JVM performs on such an architecture. In this paper, we present the first measurement study of a set of Java HPC applications on Xeon Phi under JVM. One key obstacle to the study is that there is currently little support of Java for Xeon Phi. This paper presents the result based on the first porting of Open JDK platform to Xeon Phi, in which the Hot Spot virtual machine acts as the kernel execution engine. The main difficulty includes the incompatibility between Xeon Phi ISA and the assembly library of Hotspot *** evaluating the multithreaded Java Grande benchmark suite and our ported Java Phoenix benchmarks, we quantitatively study the performance and scalability issues of JVM on Xeon Phi and draw several conclusions from the study. To fully utilize the vector computing capability and hide the significant memory access latency on the coprocessor, we present a semi-automatic vectorization scheme and software prefetching model in Hot *** with 60 physical cores and tuning, our optimized JVM achieves averagely 2.7 x and 3.5 x speedup compared to Xeon CPU processor by using vectorization and prefetching accordingly. Our study also indicates that it is viable and potentially performance-beneficial to run applications written for such a managed runtime like JVM on Xeon Phi.

关键词： many-core Java Xeon Phi HPC prefetching

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VisGraphNet: A complex network interpretation of convolutional neural features

arXiv

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arXiv 2021年

作者： Florindo, Joao B. Lee, Young-Sup Jun, Kyungkoo Jeon, Gwanggil Albertini, Marcelo K. Institute of Mathematics Statistics and Scientific Computing University of Campinas Rua Sérgio Buarque de Holanda 651 Cidade Universitária"Zeferino Vaz" - Distr. Barão Geraldo SP CampinasCEP 13083-859 Brazil Department of Embedded Systems Engineering Incheon National University 119 Academy-ro Yeonsu-gu Incheon22012 Korea Republic of Department of Computer Science Federal University of Uberlandia Av. Joao Naves de Avila 2121 room Minas Gerais Uberlandia1B150 Brazil

Here we propose and investigate the use of visibility graphs to model the feature map of a neural network. The model, initially devised for studies on complex networks, is employed here for the classification of texture images. The work is motivated by an alternative viewpoint provided by these graphs over the original data. The performance of the proposed method is verified in the classification of four benchmark databases, namely, KTHTIPS-2b, FMD, UIUC, and UMD and in a practical problem, which is the identification of plant species using scanned images of their leaves. Our method was competitive with other state-of-the-art approaches, confirming the potential of techniques used for data analysis in different contexts to give more meaningful interpretation to the use of neural networks in texture classification. © 2021, CC BY.

关键词： Complex networks

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Achieving efficient realization of kalman filter on CGRA through algorithm-architecture co-design 14th

Achieving efficient realization of kalman filter on CGRA thr...

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14th International Symposium on Applied Reconfigurable Computing, ARC 2018

作者： Merchant, Farhad Vatwani, Tarun Chattopadhyay, Anupam Raha, Soumyendu Nandy, S.K. Narayan, Ranjani Institute for Communication Technologies and Embedded Systems RWTH Aachen University Aachen Germany Hardware and Embedded Systems Lab Nanyang Technological University Singapore Singapore Scientific Computation Laboratory Indian Institute of Science Bangalore India Computer Aided Design Laboratory Indian Institute of Science Bangalore India Morphing Machines Pvt. Ltd. Bangalore India

ISBN: (纸本)9783319788890

In this paper, we present efficient realization of Kalman Filter (KF) that can achieve up to 65% of the theoretical peak performance of underlying architecture platform. KF is realized using Modified Faddeeva Algorithm (MFA) as a basic building block due to its versatility and REDEFINE Coarse Grained Reconfigurable Architecture (CGRA) is used as a platform for experiments since REDEFINE is capable of supporting realization of a set algorithmic compute structures at run-time on a Reconfigurable Data-path (RDP). We perform several hardware and software based optimizations in the realization of KF to achieve 116% improvement in terms of Gflops over the first realization of KF. Overall, with the presented approach for KF, 4-105x performance improvement in terms of Gflops/watt over several academically and commercially available realizations of KF is attained. In REDEFINE, we show that our implementation is scalable and the performance attained is commensurate with the underlying hardware resources. © Springer International Publishing AG, part of Springer Nature 2018.

关键词： Kalman filters

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STLDAS: Secure Two Level Deduplication and Auditing of Shared Data in Cloud

STLDAS: Secure Two Level Deduplication and Auditing of Share...

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IEEE Region 10 Symposium

作者： C M Geeta G Mithila Lakshmi 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 India Cloud Computing and Distributed Systems (CLOUDS) Lab School of Computing and Information Systems 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

With the cloud repository service furnished by the cloud computing, users can comfortably arrange themselves as a cluster and distribute information effectively. In order to empower public verifier to audit the distributed information, clients in the cluster need to Figure out signatures on complete chunks of collaborative information. Every client in the cluster modifies and signs his respective chunks, and deploys in the cloud server. Hence specific chunks of shared information are normally signed by specific clients. If anyone of the customers' is found malicious, he is immediately repudiated from the cluster. The prevailing clients in the cluster are permitted to re-sign the chunks that were earlier signed by this eliminated client. This approach is inefficient due to the massive amount of collaborative information in the cloud. By exploiting the approach of proxy re-signatures, the CSP is acknowledged to re-sign chunks in support of the prevailing clients during customer repudiation. When many clients deploy the same information to the cloud repository, repository space has identical copies, hence deduplication technology is usually utilized to lower the capacity and bandwidth prerequisites of the utilities by removing repetitious information and hoarding only an original replica of them. In order to assimilate both data honesty and deduplication in cloud, we present a novel Secure Two Level Deduplication and Auditing of Shared Data in Cloud (STLDAS) mechanism. Experimental results show that our mechanism achieves secure deduplication and appreciable improvement in tag generation.

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Precision of sung notes in carnatic music 19

Precision of sung notes in carnatic music

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19th International Society for Music Information Retrieval Conference, ISMIR 2018

作者： Viraraghavan, Venkata Subramanian Murthy, Hema A. Aravind, R. TCS Research and Innovation Embedded Systems and Robotics Bangalore India Department of Electrical Engineering Indian Institute of Technology Madras India Department of Computer Science and Engineering Indian Institute of Technology Madras India

ISBN: (纸本)9782954035123

Carnatic music is replete with continuous pitch movement called gamakas and can be viewed as consisting of constant-pitch notes (CPNs) and transients. The stationary points (STAs) of transients – points where the pitch curve changes direction – also carry melody information. In this paper, the precision of sung notes in Carnatic music is studied in detail by treating CPNs and STAs separately. There is variation among the nineteen musicians considered, but on average, the precision of CPNs increases exponentially with duration and settles at about 10 cents for CPNs longer than 0.5 seconds. For analyzing STAs, in contrast to Western music, rāga (melody) information is found to be necessary, and errors in STAs show a significantly larger standard deviation of about 60 cents. To corroborate these observations, the music was automatically transcribed and re-synthesized using CPN and STA information using two interpolation techniques. The results of perceptual tests clearly indicate that the grammar is highly flexible. We also show that the precision errors are not due to poor pitch tracking, singer deficiencies or delay in auditory feedback. © V S Viraraghavan, H A Murthy, R Aravind.

关键词： Music

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HomeCA: Scalable Secure IoT Network Integration 49

HomeCA: Scalable Secure IoT Network Integration

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49. Jahrestagung der Gesellschaft fur Informatik: 50 Jahre Gesellschaft fur Informatik - Informatik fur Gesellschaft, INFORMATIK 2019 - 49th Annual Meeting of the German Informatics Society: 50 years of the German Informatics Society - computer science for Society, INFORMATICS 2019

作者： Müller, Robert Schmitt, Corinna Kaiser, Daniel Waldvogel, Marcel Department of Computer and Information Science Distributed Systems Laboratory Universität Konstanz Konstanz78457 Germany Research Institute Code Universität der Bundeswehr München Werner-Heisenberg-Weg 39 Neubiberg85577 Germany Security and Networking Research Group Netlab Maison du Nombre 6 University of Luxembourg Avenue de la Fonte Esch-sur-Alzette4364 Luxembourg

ISBN: (纸本)9783885796886

Integrating Internet of Things (IoT) devices into an existing network is a nightmare. Minimalistic, unfriendly user interfaces, if any;badly chosen security methods, most notably the defaults;lack of long term security;and bugs or misconAgurations are plentiful. As a result, an increasing number of owners operate unsecure devices. Our investigations into the root causes of the problems resulted in the development of Home CertiAcate Authority (HomeCA). HomeCAincludes a comprehensive set of secure, vendor-independent interoperable practices based on existing protocols and open standards. HomeCA avoids most of the current pitfalls in network integration by design. Long-term protocol security, permission management, and secure usage combined with simpliAed device integration and secure key updates on ownership acquisition pave the way toward scalable, federated IoT security. © 2019 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： Network security

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Geo-Cloudlet: Time and Power Efficient Geospatial Query Resolution using Cloudlet

Geo-Cloudlet: Time and Power Efficient Geospatial Query Reso...

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International Conference on Advanced Computing, ICAC

作者： Jaydeep Das Anwesha Mukherjee Soumya K. Ghosh Rajkumar Buyya Advanced Technology Development Centre Indian Institute of Technology Kharagpur West Bengal India Department of Computer Science Mahishadal Raj College Purba Medinipur West Bengal India Department of Computer Science and Engineering Indian Institute of Technology Kharagpur West Bengal India Cloud Computing and Distributed Systems (CLOUDS) Lab School of Computing and Information Systems The University of Melbourne VIC Australia

ISBN: (数字)9781728152868

ISBN: (纸本)9781728152875

Geospatial data analysis is an emerging area of research today due to the potential to enable varied location-aware services. The existing centralized cloud-based analysis becomes time and computing-intensive for huge amount of geospatial data processing. This paper addresses the challenge of time and power-efficiency in QoS-aware geospatial query resolution. We propose a cloudlet based hierarchical paradigm, namely Geo-Cloudlet, where the cloudlets contain the geospatial data of the districts. The state and national level geospatial data are stored inside the state cloud and country cloud respectively. The query resolution is performed by either the cloudlet or by the state cloud or country cloud depending upon the geographical region related to the query. The experimental analysis illustrates that the proposed architecture Geo-Cloudlet reduces the latency up to 61.3% and power consumption up to 61.1% over the use of only remote cloud servers for geospatial query resolution.

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