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1st IEEE Summer School on Smart Cities, S3C 2017

作者： De Fatima Pereira Marquesone, Rosangela De Brito Carvalho, Tereza Cristina Melo Guimaraes, Lucas Batista Dias, Eduardo Mario Laboratory of Computer Networks and Architecture LARC Polytechnic School University of São Paulo São Paulo Brazil Department of Energy Engineering and Automation Polytechnic University of São Paulo São Paulo Brazil

ISBN: (纸本)9781538610633

Smart mobility is an emerging concept characterized by the use of disruptive technologies, such as cloud computing, Big Data and artificial intelligence. In this paper we propose a FIWARE-based component focus on improving the data analysis process, from data generated in services and applications existing in the smart mobility context. Our proposal aims to provide features that allows the development of solutions from the industry 4.0 concept and smart cities. Firstly, we briefly contextualize these terms, then we describe the characteristics and architectural design of our FIWARE component, highlighting how it can improve the support to smart services and applications. We also present real application scenarios where this component can be applied, specially considering the Brazilian cities. © 2017 IEEE.

关键词： Data handling

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ARM: A hybrid specification-based intrusion detection system for rank attacks in 6TiSCH networks

ARM: A hybrid specification-based intrusion detection system...

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International Conference on Emerging Technologies and Factory automation (ETFA)

作者： Areej Althubaity Huayi Ji Tao Gong Mark Nixon Reda Ammar Song Han Department of Computer Science and Engineering University of Connecticut Emerson Automation Solutions Future Architecture and Applied Research

6TiSCH network architecture has recently been introduced to combine the high reliability and low-power consumption of the TSCH (Time-Slotted Channel Hopping) mode of IEEE 802.15.4e MAC with the ease of integration offered by the IP-enabled upper layer protocols. 6TiSCH network uses RPL (Routing Protocol for Low Power and Lossy Networks) as its routing protocol to manage the network layer functionalities. RPL however is vulnerable to internal routing attacks such as Rank attack where a malicious node multicasts a fake position (Rank) or a fake path cost toward the sink node to lure nearby nodes to forward their packets through it. In this paper, we propose a hybrid specification-based intrusion detection system (IDS) that consists of centralized and distributed modules installed on the sink and RPL nodes respectively to prevent nodes from selecting an intruder as their successors. The proposed method also eliminates intruders' chances of becoming a time source and disrupt the synchronization of 6TiSCH networks. The results from our extensive simulations show that compared with existing countermeasures, the proposed IDS can effectively protect RPL topologies while only incurring limited network management overhead.

关键词： Routing Topology Monitoring Synchronization Network topology Intrusion detection

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SFIDE: A simulation infrastructure for data centers 49

SFIDE: A simulation infrastructure for data centers

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49th Summer computer Simulation Conference, SCSC 2017, Part of the 2017 Summer Simulation Multi-Conference, SummerSim 2017

作者： Penas, Ignacio Zapater, Marina Risco-Martín, José L. Ayala, José L. Green Integrated Systems Laboratory Technical University of Madrid Av. Complutense 30 Madrid28040 Spain Dpt. of Computer Architecture and Automation Complutense University of Madrid C/Prof. José García Santesmases 9 Madrid28040 Spain

ISBN: (纸本)9781510838284

Data centers are huge power consumers and have very high operational costs. Both industry and academia have proposed strategies at multiple levels (server, room layout, cooling, workload allocation, etc.) to increase the efficiency of these facilities. Testing the impact of variables so different in nature such as layout or workload allocation can only be managed by simulators. Current simulation infrastructures are either focused on data room thermal dynamics, or target only a specific stage of data center operations, such as workload allocation. Moreover, they are geared for specific use-cases such as HPC or cloud computing. In this paper we present a data center modeling and simulation framework, for both HPC and cloud applications, to assess data center performance, thermal behavior, energy efficiency and operational cost. Our goal is to show the possibilities of the current data center modeling and simulation framework. Furthermore, as we provide a fully configurable, flexible and scalable infrastructure any kind of policy, data center size or workload amount could easily be implemented over the simulator. We also provide the data sets used to validate our models and policies, obtained from real servers and data centers, so as to enable researchers to test their strategies in a realistic setup. © 2017 Society for Modeling & Simulation International (SCS).

关键词： Smart power grids

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User-profile-based analytics for detecting cloud security breaches

User-profile-based analytics for detecting cloud security br...

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IEEE International Conference on Big Data

作者： Trishita Tiwari Ata Turk Alina Oprea Katzalin Olcoz Ayse K. Coskun Electrical and Computer Engineering Boston University Boston MA USA Computer and Information Science Northeastern University Boston MA USA Computer Architecture and Automation Universidad Complutense de Madrid Spain

While the growth of cloud-based technologies has benefited the society tremendously, it has also increased the surface area for cyber attacks. Given that cloud services are prevalent today, it is critical to devise systems that detect intrusions. One form of security breach in the cloud is when cyber-criminals compromise Virtual Machines (VMs) of unwitting users and, then, utilize user resources to run time-consuming, malicious, or illegal applications for their own benefit. This work proposes a method to detect unusual resource usage trends and alert the user and the administrator in real time. We experiment with three categories of methods: simple statistical techniques, unsupervised classification, and regression. So far, our approach successfully detects anomalous resource usage when experimenting with typical trends synthesized from published real-world web server logs and cluster traces. We observe the best results with unsupervised classification, which gives an average F1-score of 0.83 for web server logs and 0.95 for the cluster traces.

关键词： Cloud computing Measurement Support vector machines Standards Anomaly detection Market research

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Reliable Code Generation and Test Environment demonstrated on a PI-Controller Design

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IFAC-PapersOnLine 2016年第3期49卷 465-470页

作者： Schwarz, M.H. Sheng, H. Üstoglu, I. Chabaan, W. Börcsök, J. Safety Computer Technology University of Kassel Germany Control and Automation Engineering Department Yildiz Technical University Istanbul Turkey Computer Architecture and System Programming University of Kassel Germany

This paper focuses on the latest version of a tool developed within the department to guide developer through the various steps of requirements, test-procedures and documentations to finally download the derived algorithm on a safety programmable logic controller (PLC). Requirements on how to develop and how to test software are steadily increasing due to international standards, which have to be obeyed in industries in general, and in the process- and automation industries in particular. A simple model is derived to be used to develop a PI controller that has to pass several steps to be qualified for execution on a PLC. The paper explains the different steps and describes the various problems that might occur. © 2016

关键词： Controllers Accident prevention Reliability Software testing Automated code generation automation industry International standards P i controller designs PI control Programmable Logic Controller (PLC) Simple modeling Test Environment

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Synthesis of La0.5Ca0.5-xxMnO3 nanocrystalline manganites by sucrose assisted auto combustion route and study of their structural, magnetic and magnetocaloric properties

arXiv

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arXiv 2019年

作者： Moumen, S. Ben Gagou, Y. Chettab, M. Mezzane, D. Amjoud, M. Fourcade, S. Hajji, L. Kutnjak, Z. Marssi, M.E. Amraoui, Y.E. Kopelevich, Y. Lukýanchuk, Igor A. LMCN F.S.T.G. Université Cadi Ayyad BP 549 Marrakech Morocco LPMC Université de Picardie Jules Verne 33 rue Saint-Leu Amiens Cédex80039 France LCMCB Université de Bordeaux Pessac33600 France Jozef Stefan Institute Jamova cesta 39 Ljubljana1000 Slovenia LaMCScI Faculté des Sciences Université Mohammed V Rabat Morocco Instituto de Fisica Gleb Wataghin Universidade Estadual de Campinas Unicamp 13083-859 Campinas Sao Paulo Brazil Department of Cybersecurity and Computer Engineering Faculty of Automation and Information Technologies Kyiv National University of Construction and Architecture Kyiv Ukraine

Perovskite manganite La0.5Ca0.5-xxMnO3 (LCMO) nanomaterials were elaborated using the sucrose modified auto combustion method. Rietveld refinements of the X-ray diffraction patterns of the crystalline structure confirm a single-phase orthorhombic state with Pbnm space group (No. 62). The Ca-vacancies were voluntarily created in the LCMO structure in order to study their influence on the magnetic behaviour in the system. The magnetic susceptibility was found to be highly enhanced in the sample with Ca-vacancies. Paramagnetic-to-ferromagnetic phase transition was evidenced in both samples around 254 K. This transition is, characterized by a drastic jump of the susceptibility in the sample with Ca-vacancies. The maximum of entropy change, observed for both compounds at magnetic field of 6T was 2.30 J kg-1K-1 and 2.70 J kg-1K-1 for the parent compound and the lacunar one respectively. The magnetocaloric adiabatic temperature change value calculated by indirect method was 5.6 K and 5.2 K for the non-lacunar and Ca-vacancy compound, respectively. The Ca-lacunar La0.5Ca0.5-xxMnO3 (x=0.05) reported in this work demonstrated overall enhancement of the magnetocaloric effect over the LCMO. The technique used to elaborate LCMO materials was beneficial to enhance the magnetocaloric effect and magnetic behaviour. Therefore, we conclude that this less costly environmentally friendly system can be considered as more advantageous candidate for magnetic refrigeration applications then the commonly Gd-based compounds. Copyright © 2019, The Authors. All rights reserved.

关键词： Sugar (sucrose)

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DECODING DYNAMIC AUDITORY ATTENTION DURING NATURALISTIC EXPERIENCE

DECODING DYNAMIC AUDITORY ATTENTION DURING NATURALISTIC EXPE...

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International Symposium on Biomedical Imaging

作者： Liting Wang Xintao Hu Meng Wang Jinglei Lv Junwei Han Shijie Zhao Qinglin Dong Lei Guo Tianming Liu School of Automation Northwestern Polytechnical University Cortical Architecture Imaging and Discovery Lab Department of Computer Science and Bioimaging Research Center The University of Georgia

ISBN: (纸本)9781509011735

Equipped with selective auditory attention (SAA), people are able to rapidly shift their attention to auditory events of interest. Although abstract neuroimaging paradigms are fundamental for exploring the neural basis of SAA, whether those findings are valid in a more naturalistic condition and how the types of auditory stimuli affect SAA are largely unknown. Here we propose a brain decoding study to explore SAA using naturalistic auditory excerpts in three categories (pop music, classical music and speech) as stimuli for functional magnetic resonance imaging (fMRI). We adopted a computational auditory attention model to estimate attentional allocation for the excerpts. We then extracted brain activity features from fMRI data via sparse representation and used them to decode the auditory attention allocation. Our experimental results showed that the primary auditory cortex was commonly involved in the attentional processing of the three categories and the contribution of distinct brain networks to the decoding model in each group. Our study on the one hand provides novel insights into neural SAA in naturalistic experience, on the other hand shows the possibility of leveraging neuroimaging studies by integrating naturalistic stimuli and computational auditory information processing approaches.

关键词： Dynamic auditory attention naturalistic experience brain decoding sparse representation

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EXPLORING HUMAN BRAIN ACTIVATION VIA NESTED SPARSE CODING AND FUNCTIONAL OPERATORS

EXPLORING HUMAN BRAIN ACTIVATION VIA NESTED SPARSE CODING AN...

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International Symposium on Biomedical Imaging

作者： Shu Zhang Xiang Li Lei Guo Tianming Liu Cortical Architecture Imaging and Discovery Lab Department of Computer Science and Bioimaging Research Center The University of Georgia School of Automation Northwestern Polytechnical University

ISBN: (纸本)9781509011735

Traditional task-based fMRI activation detection methods, such as the general linear model (GLM), assume that the fMRI signals of activated brain regions follow the external stimulus paradigm. Typically, these activated regions are detected independently in a voxel-wise fashion, and the interaction among voxels is nevertheless neglected. Despite the wide use and remarkable success of GLM, the temporal and spatial relationships among activated regions remain unveiled. In response to this challenge, we present a novel method that combines two-stage sparse representation framework and the operator modulations (integral and derivative) to explore the temporal and spatial organizations underlying fMRI-derived activations in the brain. The two-stage sparse representation framework is designed to deal with big data and the functional operator is focused on finding the refined activation areas in the brain under task performances. Experiments demonstrated that diverse temporal and spatial organizations between activated regions exist and different functional operators may lead to different activation areas, thus significantly supplementing to the available principle of GLM that has been widely used in the human brain mapping field.

关键词： Functional Operator Activation Detection Nested Sparse Codings

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Adaptive compressed sensing at the fingertip of Internet-of-Things sensors: An ultra-low power activity recognition 20

Adaptive compressed sensing at the fingertip of Internet-of-...

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20th Design, automation and Test in Europe, DATE 2017

作者： Fallahzadeh, Ramin Ortiz, Josue Pagan Ghasemzadeh, Hassan School of Electrical Engineering and Computer Science Washington State University PullmanWA99164-2752 United States Department of Computer Architecture and Automation Complutense University of Madrid Madrid Spain

ISBN: (纸本)9783981537093

With the proliferation of wearable devices in the Internet-of-Things applications, designing highly power-efficient solutions for continuous operation of these technologies in life-critical settings emerges. We propose a novel ultra-low power framework for adaptive compressed sensing in activity recognition. The proposed design uses a coarse-grained activity recognition module to adaptively tune the compressed sensing module for minimized sensing/transmission costs. We pose an optimization problem to minimize activity-specific sensing rates and introduce a polynomial time approximation algorithm using a novel heuristic dynamic optimization tree. Our evaluations on real-world data shows that the proposed autonomous framework is capable of generating feedback with -80% confidence and improves power reduction performance of the state-of-the-art approach by a factor of two. © 2017 IEEE.

关键词： Compressed sensing

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FMRI DATA CLASSIFICATION BASED ON HYBRID TEMPORAL AND SPATIAL SPARSE REPRESENTATION

FMRI DATA CLASSIFICATION BASED ON HYBRID TEMPORAL AND SPATIA...

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International Symposium on Biomedical Imaging

作者： Huan Liu Mianzhi Zhang Xintao Hu Yudan Ren Shu Zhang Junwei Han Lei Guo Tianming Liu School of Automation Northwestern Polytechnical University Cortical Architecture Imaging and Discovery Lab Department of Computer Science and Bioimaging Research Center The University of Georgia

ISBN: (纸本)9781509011735

Task-based functional magnetic resonance imaging (tfMRI) is widely used to localize brain regions or networks in response to various cognitive tasks. However, given two groups of tfMRI data acquired under distinct task paradigms, it is not clear whether there exist intrinsic inter-group differences in signal composition patterns, and if so, whether these differences could be used for data discrimination. The major challenges originate from the high dimensionality and low signal-to-noise ratio of fMRI data. In this paper, we proposed a novel framework using hybrid temporal and spatial sparse representation to tackle above challenges. We applied the proposed framework to the Human Connectome Project (HCP) tfMRI data. Our experimental results demonstrated that the task types of fMRI data can be successfully classified, achieving a 100% classification accuracy. We also showed that both task-related components and resting state networks (RSNs) can be reliably identified. Our study provides a novel data-driven approach to detecting discriminative inter-group differences in fMRI data based on signal composition patterns, and thus potentially can be used to control fMRI data quality and to infer biomarkers in brain disorders.

关键词： FMRI classification hybrid temporal and spatial sparse representation

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