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11th IEEE International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2017

作者： Florencias-Oliveros, Olivia Aguera-Perez, Agustin Gonzalez-De-La-Rosa, Juan-Jose Palomares-Salas, Jose-Carlos Sierra-Fernandez, Jose-Maria Montero, Alvaro Jimenez Spain Department of Automation Engineering Electronics Architecture Computer Networks Polytechnic School of Algeciras University of Cadiz Spain

ISBN: (纸本)9781509049639

This paper proposes a technique based in the graphical cluster analysis to be implemented in Smart Power Quality Analyzers (SPQA), a proposal Instrument Class S, according to the standard UNE-EN 61000-4-30, with the goal of monitoring electrical grids where new events arise as a consequence of the penetration of new energy resources. In the presence of an electrical fault the instrument triggers the measurement procedure, according to a settled threshold of the PQ, and calculates the higher-order statistics (HOS) features in the time domain that enable the classification. Performance results over a battery of 160 signals show two clusters (sags and transients), with an acceptable accuracy of 80%. The work also presents the concept of the uncertainty inter-cluster area. The analysis of the intensity cluster disturbances helps the grid operator characterizing better the database and introducing some qualitative criteria for monitoring the smart grid. © 2017 IEEE.

关键词： Power quality

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Data hiding algorithm for hevc using intra-coded frames 50

Data hiding algorithm for hevc using intra-coded frames

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50th Summer computer Simulation Conference, SCSC 2018, Part of the 2018 Summer Simulation Multi-Conference, SummerSim 2018

作者： Rodríguez, David Botella, Guillermo Del Barrio, Alberto A. Cuesta, David Computer Science Faculty Universidad Complutense de Madrid Prof. José García Santesmases 9 Madrid Spain La Paz University Hospital Spain Department of Computer Architecture and Automation Universidad Complutense de Madrid Prof. José García Santesmases 9 Madrid Spain Technical Direction Admr. Infraestructuras Ferroviarias Sor Ángela de la Cruz 3 Madrid Spain

ISBN: (纸本)9781510860209

This paper proposes a method to hide information in a video and to recover it after having been encoded under the standard H.265/HEVC. The process is based on manipulating the luminance properties of the YUV video sequence, without the need to modify the HEVC standard. Results show that the quality loss due to embedding the message is negligible in comparison with the original video. Besides, the proposed recovery method is able to extract all the information from the encoded video. © 2018 Society for Modeling & Simulation International (SCS).

关键词： Steganography

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Advanced migraine prediction simulation system 49

Advanced migraine prediction simulation system

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

作者： Pagán, Josué Moya, José M. Mittal, Saurabh Ayala, José L. Department of Computer Architecture and Automation CCS-Center for Computational Simulation Complutense University of Madrid Madrid Spain LSI - Electronic Engineering Department CCS-Center for Computational Simulation Technical University of Madrid Madrid Spain Complex Systems Research Lab Dunip Technologies LLC HerndonVA United States Department of Computer Architecture and Automation Computer Science Faculty Complutense University of Madrid Spain

ISBN: (纸本)9781510838284

In the Internet of Things (IoT) era, there is growing interest in wireless monitoring sensors for detection, classification and prediction of health symptoms. The prediction of symptoms in chronic diseases such as migraines brings new hope to improve patients' lives. The prediction of a migraine symptomatic event through monitoring hemodynamic variables has been previously demonstrated in our earlier work. In this paper, a simulation-based approach for a real-Time migraine prediction system is described. The simulation has been implemented using the specifications of the formal description language Discrete EVent Systems (DEVS). The simulation system is a proof of concept that is ready for testing in a real-world ambulatory monitoring environment. The results obtained encourage developing a hardware/software (HW/SW) cosimulation system that incorporates Hardware-in-The-Loop (HIL) components as prior step to the expensive and slow hardware implementation of a complete migraine prediction device. When such a system is used in a real-Time setting, it can simulate failures in sensors and trigger alarms for active patient response. © 2017 Society for Modeling & Simulation International (SCS).

关键词： Forecasting

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Building accurate models to determine the current CPU utilization of a host within a virtual machine allocated on it 49

Building accurate models to determine the current CPU utiliz...

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

作者： Briongos, Samira Malagón, Pedro Risco, José L. Moya, José M. Department of Computer Architecture and Automation Computer Science Faculty Complutense University of Madrid Spain LSI - Electronic Engineering Department CCS-Center for Computational Simulation Universidad Poliécnica de Madrid Madrid Spain

ISBN: (纸本)9781510838284

In cloud computing environments there are several virtual machines running in the same host. This fact opens the door for possible side channel-Attacks. Prior to perform an attack it is mandatory to determine coresidency with the victim. An synchronized variation in the CPU activity in the host is a possible indicator of the presence of neighboring processes. However, cloud providers do not give information about the hosts CPU load, so we have to figure out a way of estimating it. We estimate the host CPU load considering its impact on the performance of a virtual machine (VM) running on it. In this work, we show that it is possible to calculate the CPU load of the host by executing a reference process, measuring the time it takes to execute, and using this information as an input to generate the CPU load models. We explore regression methods and regression methods tuned with genetic algorithms for the model generation. As a result, considering a CPU load value between 0 (no load) and 100 (maximum load), we obtain models which compute the host load with a mean squared error of around 5%, 10% and 30% (depending on the host architecture) when estimating the load every second. © 2017 Society for Modeling & Simulation International (SCS).

关键词： Genetic algorithms

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Mathematical Control Model of Secondary Coextrusion Composition Preparation

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IOP Conference Series: Earth and Environmental Science 2020年第3期459卷

作者： V V Dyadichev A V Kolesnikov A V Dyadichev V.I. Vernadsky Crimean Federal University Academy of Construction and Architecture Engineering Center 'Bio-positive Construction and Resource-saving' 3 Pavlenko Str. Simferopol Crimea 295000 Russia Lugansk National University named after Vladimir Dal Department of Automation and Computer-Integrated Technologies 20-A Molodezhnyi Sq. Lugansk 91034 Ukraine

The control of polymer waste recycling process is an important modern problem. A partial solution to the problem can be got by using coextrusion technology. As a result of its application with respect to polymer waste, we can get a multilayer qualitative product, containing waste and safe for usage. Because of economic causes, the problem of using this technology is the correct preparation of secondary coextrusion composition based on the requirements to the quality of the obtained product. The scientific paper presents the mathematical control model of secondary polymer composition preparation. The developed model allows carrying out an operational control of composition components consumption, determining and correcting the consumption of the most expensive astringent component in order to guarantee the required quality of the product. The mathematical model is the basis for construction of intellectual automated systems for controlling polymer waste recycling process by coextrusion technology.

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Simulation and implementation of a lowcost platform to improve the quality of biological images 49

Simulation and implementation of a lowcost platform to impro...

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

作者： Fabregat, Hermenegildo Del Barrio, Alberto A. Botella, Guillermo Computer Science Faculty Universidad Complutense de Madrid Prof. José García Santesmases 9 Madrid Spain Department of Computer Architecture and Automation Universidad Complutense de Madrid Prof. José García Santesmases 9 Madrid Spain

ISBN: (纸本)9781510838284

The development of fluorescence microscopy techniques has help advance in the understanding of molecular mechanisms present at biological systems, as the case of cell migration (Castillo-Lluva et al. 2010, Castillo- Lluva et al. 2013). These techniques allows studying the location, distribution as well as the movement of molecules that have been fluorescently tagged at a high resolution, even dealing with live cells (Rieckher 2017). In this paper a filtering and pattern recognition flow is simulated and implemented on a low-cost hardware platform in order to automate the detection of circular and ellipsoidal cells within the microscopic images. Results show that images keep a high quality after filtering and that 78.4% of the objects are properly recognized. © 2017 Society for Modeling & Simulation International (SCS).

关键词： Neural networks

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Self-Awareness for Autonomous Systems

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PROCEEDINGS OF THE IEEE 2020年第7期108卷 971-975页

作者： Dutt, Nikil Regazzoni, Carlo S. Rinner, Bernhard Yao, Xin Nikil Dutt (Fellow IEEE) received the Ph.D. degree from the University of Illinois at Urbana–Champaign Champaign IL USA in 1989.""He is currently a Distinguished Professor of computer science (CS) cognitive sciences and electrical engineering and computer sciences (EECS) with the University of California at Irvine Irvine CA USA. He is a coauthor of seven books. His research interests include embedded systems electronic design automation (EDA) computer architecture distributed systems healthcare Internet of Things (IoT) and brain-inspired architectures and computing.""Dr. Dutt is a Fellow of ACM. He was a recipient of the IFIP Silver Core Award. He has received numerous best paper awards. He serves as the Steering Committee Chair of the IEEE/ACM Embedded Systems Week (ESWEEK). He is also on the steering organizing and program committees of several premier EDA and embedded system design conferences and workshops. He has served on the Editorial Boards for the IEEE Transactions on Very Large Scale Integration (VLSI) Systems and the ACM Transactions on Embedded Computing Systems and also previously served as the Editor-in-Chief (EiC) for the ACM Transactions on Design Automation of Electronic Systems. He served on the Advisory Boards of the IEEE Embedded Systems Letters the ACM Special Interest Group on Embedded Systems the ACM Special Interest Group on Design Automationt and the ACM Transactions on Embedded Computing Systems. Carlo S. Regazzoni (Senior Member IEEE) received the M.S. and Ph.D. degrees in electronic and telecommunications engineering from the University of Genoa Genoa Italy in 1987 and 1992 respectively.""He is currently a Full Professor of cognitive telecommunications systems with the Department of Electrical Electronics and Telecommunication Engineering and Naval Architecture (DITEN) University of Genoa and a Co-Ordinator of the Joint Doctorate on Interactive and Cognitive Environments (JDICE) international Ph.D. course started initially as EU Erasmus Mundus Project and

Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”), proactivity (“act on its own initiative”), and sociality (“interact with other agents”) as fundamental properties \n[1]\n. Autonomous systems will undoubtedly pervade into our everyday lives, and we will find them in a variety of domains and applications including robotics, transportation, health care, communications, and entertainment to name a few. \nThe articles in this month’s special issue cover concepts and fundamentals, architectures and techniques, and applications and case studies in the exciting area of self-awareness in autonomous systems.

关键词： Special issues and sections Autonomous systems Self-aware Robot sensing systems Computational modeling

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A DCT and neural network based system to obtain the characteristics of biological images 49

A DCT and neural network based system to obtain the characte...

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

作者： Fariña, Daniel Botella, Guillermo Del Barrio, Alberto A. Computer Science Faculty Universidad Complutense de Madrid Prof. José García Santesmases 9 Madrid Spain Dept. of Computer Architecture and Automation Universidad Complutense de Madrid Prof. José García Santesmases 9 Madrid Spain

ISBN: (纸本)9781510838284

The purpose of this paper is to determine the suitability of low-cost and low-power FPGA boards for acceleration, focused especially on cells classification in microscopy images. Our approach is based on simulation by means of using Matlab and Simulink. An implementation of the DCT is presented for the extraction of characteristics along with a classification Neural Network. Results show the execution time of the algorithms, their efficiency in terms of accuracy and the limitations of the hardware. The presented system is able to process 640x480 images in 0.53 seconds on average, with a total execution time of 5.04 seconds due to the transfer overhead. © 2017 Society for Modeling & Simulation International (SCS).

关键词： Simulink

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SIMULATION AND IMPLEMENTATION OF A LOW-COST PLATFORM TO IMPROVE THE QUALITY OF BIOLOGICAL IMAGES 17

SIMULATION AND IMPLEMENTATION OF A LOW-COST PLATFORM TO IMPR...

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computer Simulation Conference

作者： Hermenegildo Fabregat Alberto A. Del Barrio Guillermo Botella Computer Science Faculty Universidad Complutense de Madrid Department of Computer Architecture and Automation Universidad Complutense de Madrid

ISBN: (纸本)9781510838284

The development of fluorescence microscopy techniques has help advance in the understanding of molecular mechanisms present at biological systems, as the case of cell migration (Castillo-Lluva et al. 2010, Castillo-Lluva et al. 2013). These techniques allows studying the location, distribution as well as the movement of molecules that have been fluorescently tagged at a high resolution, even dealing with live cells (Rieckher 2017). In this paper a filtering and pattern recognition flow is simulated and implemented on a low-cost hardware platform in order to automate the detection of circular and ellipsoidal cells within the microscopic images. Results show that images keep a high quality after filtering and that 78.4% of the objects are properly recognized.

关键词： Microscopic images Filter Pattern recognition Neural network FiL

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A DCT AND NEURAL NETWORK BASED SYSTEM TO OBTAIN THE CHARACTERISTICS OF BIOLOGICAL IMAGES 17

A DCT AND NEURAL NETWORK BASED SYSTEM TO OBTAIN THE CHARACTE...

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Simulation Multiconference

作者： Daniel Farina Guillermo Botella Alberto A. Del Barrio Computer Science Faculty Universidad Complutense de Madrid Dept. of Computer Architecture and Automation Universidad Complutense de Madrid

ISBN: (纸本)9781510838284

The purpose of this paper is to determine the suitability of low-cost and low-power FPGA boards for acceleration, focused especially on cells classification in microscopy images. Our approach is based on simulation by means of using Matlab and Simulink. An implementation of the DCT is presented for the extraction of characteristics along with a classification Neural Network. Results show the execution time of the algorithms, their efficiency in terms of accuracy and the limitations of the hardware. The presented system is able to process 640×480 images in 0.53 seconds on average, with a total execution time of 5.04 seconds due to the transfer overhead.

关键词： FPGA in the Loop Cell recognition Matlab Simulink Neuronal Network Cell recognition MATLAB execution time Neural network discrete cosine transforms DCT gene Artificial neural networks images

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