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International Conference on Robotics and Artificial Intelligence (ICRAI)

作者： Muhammad Bilal Ali Raza Mohsin Rizwan Muhammad Ahsan Hafiz Farhan Maqbool Syed Abbas Zilqurnain Naqvi Al-Khawarizmi Institute of Computer Science UET1 Lahore HCR2 Lab National Center of Robotics and Automation Lahore Pakistan Dept. of Mechatronics & Control Engineering National Center of Robotics and Automation Lahore Pakistan Dept. of Mechatronics & Control Engineering UET Lahore Lahore Pakistan

The central aim of this research is to propose a solution to rehabilitate historic places using a robotic manipulator. In this pursuit, the objective is to clean flat or curved surfaces of mihrab/muqarnas and to write lost Arabic inscriptions on spandrel using 7 Degree of freedom (DOF) robotic manipulator. Inverse kinematics solution for 7 DOF is derived by fixing redundant joint and solving the remaining 6 DOF inverse kinematics. Image processing techniques are used to get data from the given image for the robotic calligraphy operation on the spandrel to restore the lost inscriptions. Path planning exercise is implemented to navigate the end-effector on the desired path to write lost inscriptions and to clean curved surfaces of muqarnas. Proposed solutions are verified by simulation using MATLAB. The results showed that the manipulator successfully tracked the given path to perform the desired operation in mihrab as well as calligraphy operation on spandrel.

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Energy-Optimal Configurations for Single-Node HPC Applications

Energy-Optimal Configurations for Single-Node HPC Applicatio...

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International Conference on High Performance Computing & Simulation (HPCS)

作者： Vitor R. G. Silva Alex F. A. Furtunato Kyriakos Georgiou Carlos A. V. Sakuyama Kerstin Eder Samuel Xavier-de-Souza Dept. of Electronics and Microeletronics University of Mons Mons Belgium Directorate of Information Technology Instituto Federal do Rio Grande do Norte Natal Brazil Dept. of Computer Science University of Bristol Bristol United Kingdom Dept. of Computer Engineering and Automation Universidade Fedral do Rio Grande do Norte Natal Brazil

ISBN: (数字)9781728144849

ISBN: (纸本)9781728144856

Energy efficiency is a growing concern for modern computing, especially for HPC due to operational costs and the environmental impact, considering that processors have an important role in this energy consumption. In this work, we propose a methodology to find energy-optimal frequency and number of active cores to run single-node HPC applications using an application-agnostic power model of the architecture and an architecture-aware performance model of the application. We characterize the application performance using machine learning, specifically the “Support Vector Regression” algorithm. Besides that, the power consumption is estimated by modeling CMOS dynamic and static power without knowledge of the application. So, The energy-optimal configuration is estimated by minimizing the product these two models outcomes, the power model and the performance model. Then, the final model can be used to find better frequency and number of cores to aim energy efficiency application execution. Results were obtained for four PARSEC applications and, with five different inputs shows that the proposed approach used substantially less energy when compared to the DVFS governor, in best cases and worst cases.

关键词： Semiconductor device modeling Program processors Power demand Mathematical model Integrated circuit modeling Sockets Energy consumption

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Advanced migraine prediction hardware system 50

Advanced migraine prediction hardware system

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

作者： Henares, Kevin Pagán, Josué Ayala, José L. Risco-Martín, José L. Dept. of Computer Architecture and Automation Complutense University of Madrid Madrid Spain Electronic Engineering Department Universidad Politécnica de Madrid Spain CCS-Center for Computational Simulation Madrid Spain Dept. of Computer Architecture and Automation Complutense University of Madrid CCS-Center for Computational Simulation Madrid Spain

ISBN: (纸本)9781510860209

Migraine is one of the most disabling neurological diseases. Its prevalence reaches 15% of the population in developed countries and lead to high economic costs for private and national health systems. There is no cure for the migraine yet. Objective and accurate migraine prediction turns necessary in order to increase the effectiveness of the current treatments. To tackle this problem authors demonstrated in previous works the feasibility of the migraine modeling and presented a DEVS-based model for migraine prediction in a real time framework. This work presents the first step to bring migraine predictive models and simulations to real devices for the first time in the literature. To do this, the DEVS-based model has been ported to a robust hardware description language (VHDL) to be implemented into a FPGA. This paper leads to the final stage: the physical implementation of a predictive migraine monitoring device. © 2018 Society for Modeling & Simulation International (SCS).

关键词： Field programmable gate arrays (FPGA)

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Mathematical modeling of the two-stage chaotic colpitis oscillator 14

Mathematical modeling of the two-stage chaotic colpitis osci...

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14th International Conference on Advanced Trends in Radioelectronics, Telecommunications and computer engineering, TCSET 2018

作者： Semenov, Andriy O. Savytskyi, Anton Yu. Bisikalo, Oleg V. Kulakov, Pavlo I. Dept. of Radio-Frequency Engineering Vinnytsia National Technical University Vinnytsia Ukraine Faculty for Computer Systems and Automation Vinnytsia National Technical University Vinnytsia Ukraine

ISBN: (纸本)9781538625569

The mathematical modeling of the Chaotic Colpitts Oscillator with two stages is carried out in the paper. The following results of mathematical modeling are obtained: oscillator's phase portrait in the planes of normalized dynamic variables;oscillator's phase portraits in the spaces of normalized dynamic variables;time diagrams of generated chaotic oscillations;amplitude-frequency and phase-frequency characteristics of generated chaotic oscillations. © 2018 IEEE.

关键词： Oscillators Mathematical model Oscillators mathematical modeling Mathematical Model Amplitude plane Colpitts oscillator

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Removal notice to "VitSeg: Weakly supervised vitiligo segmentation in skin image" [Comput. Med. Imag. Graph. 85 (2020) 101779]

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computerized medical imaging and graphics : the official journal of the computerized Medical Imaging Society 2021年 91卷 101954页

作者： Zhangxing Bian Siyu Xia Chao Xia Ming Shao Key Laboratory of Measurement and Control of CSE Ministry of Education School of Automation Southeast University Nanjing China Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA. Key Laboratory of Measurement and Control of CSE Ministry of Education School of Automation Southeast University Nanjing China. School of Electronics Information and Electrical Engineering ShangHai Jiao Tong University Shanghai China. Dept. of Computer and Information Science University of Massachusetts Dartmouth Dartmouth MA USA.

This article has been removed: please see Elsevier Policy on Article Withdrawal (https://***/about/our-business/policies/article-withdrawal). This article has been removed at the request of the Authors and Editor-in-Chief because complete consent was not obtained by the authors in accordance with journal policy prior to publication. The authors and the journal sincerely apologize for this oversight.

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On Achieving Reliable Communication in IEC 61499

On Achieving Reliable Communication in IEC 61499

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IEEE International Conference on Emerging Technologies and Factory automation

作者： Udayanto Dwi Atmojo Valeriy Vyatkin Zoran Salcic Dept. of Electrical Engineering and Automation Aalto University Finland Dept. of Electrical and Computer Engineering The University of Auckland New Zealand

This paper proposes a novel extension for communication in the IEC 61499 standard. Inspired by the features found in the formal programming language SystemJ, the extension supports reliable and guaranteed communication in distributed execution of function block application(s)/program(s). The extension utilizes mechanisms agnostic on underlying network protocols and are based on formal semantics that guarantee data delivery. The use of proposed extension, called channel, is demonstrated in an industrial automation-type example.

关键词： IEC 61499 Reliable communication Blocking Channel Formal semantics Distributed control

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Grouped Correlational Generative Adversarial Networks for Discrete Electronic Health Records

Grouped Correlational Generative Adversarial Networks for Di...

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IEEE International Conference on Bioinformatics and Biomedicine

作者： Fan Yang Zhongping Yu Yunfan Liang Xiaolu Gan Kaibiao Lin Quan Zou Yifeng Zeng Dept. of Automation Xiamen University ByteDance Corporation School of Computer and Information Engineering Xiamen University of Technology Institute of Fundamental and Frontier Sciences Uni. of Elect. Sci. and Tech. of China School of Computing Teesside University

ISBN: (纸本)9781728118680

Using Generative Adversarial Networks (GANs) to generate synthetic Electronic Health Records (EHR) has attracted increasing attention. However, in existing approaches, the events in EHRs are treated as separate variables which are indiscriminately entered into the model, without taking into account the meaning and grouping of them. Besides, the efficacy of treatment is often neglected. In this paper, we first embed the efficacy information into the disease diagnosis, and then propose Grouped Correlational GAN (GcGAN) to explicitly learn inherent correlations between different groups of variables. We also introduce a dense connection to strengthen the generator capacity in GcGAN. Experimental results on real-world data demonstrate that the generated data from GcGAN are able to simulate real-world data in terms of distribution statistics. The results on multi-label treatment recommendation tasks show that GcGAN can boost the performances by augmenting the training dataset with the generated data and outperforms state-of-the-art approaches. It can also automatically distinguish between disease-specific drugs and adjuvant drugs, which enhances the model interpretability.

关键词： generative adversarial network electronic health record multi-label classification deep learning Electronic Health Records Machine Learning Disease diagnosis

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Privacy-Preserving Linear Regression for Brain-computer Interface Applications

Privacy-Preserving Linear Regression for Brain-Computer Inte...

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2018 IEEE International Conference on Big Data, Big Data 2018

作者： Agarwal, Anisha Dowsley, Rafael McKinney, Nicholas D. Wu, Dongrui Lin, Chin-Teng Cock, Martine De Nascimento, Anderson School of Engineering and Technology University of Washington Tacoma United States Dept. of Computer Science Aarhus University Aarhus Denmark School of Automation Huazhong University of Science and Technology Wuhan China School of Software University of Technology Sydney Australia Dept. of Applied Math. Comp. Sc. and Statistics Ghent University Belgium

ISBN: (纸本)9781538650356

Many machine learning (ML) applications rely on large amounts of personal data for training and inference. Among the most intimate exploited data sources is electroencephalogram (EEG) data. The emergence of consumer-grade, low-cost brain-computer interfaces (BCIs) and corresponding software development kits1 is bringing the use of BCI within reach of application developers. The access that BCI applications have to neural signals rightly raises privacy concerns. Application developers can easily gain knowledge beyond the professed scope from unprotected EEG signals, including passwords, ATM PINs, and other personal data [1]. The challenge we address is how to engage in meaningful ML with EEG data while protecting the privacy of users. © 2018 IEEE.

关键词： Electroencephalography

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Closed Loop Fault Detectability Based on a Gap-Metric 2

Closed Loop Fault Detectability Based on a Gap-Metric

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2nd IEEE Conference on Control Technology and Applications, CCTA 2018

作者： Sekunda, Andre Ding, Steven Kjolstad Poulsen, Niels Niemann, Henrik Department of Electrical Engineering Automation and Control Tech. University of Denmark Kgs. LyngbyDk-2800 Denmark Dept. of Automatic Control and Complex Systems University of Duisburg-Essen Duisburg47057 Germany Dept. of Applied Mathematics and Computer Science Tech. University of Denmark Kgs. LyngbyDk-2800 Denmark

ISBN: (纸本)9781538676981

Systems are often controlled using feedback loops. Fault diagnosis schemes are usually designed assuming that there is no feedback loop. Therefore fault diagnosis methods need to accommodate for the feedback loop. One such method is active fault diagnosis based on a fault signature system. This method is derived using the YJBK parametrisation, named after Youla, Jabr, Bongiorno and Kucera. It uses the derived fault signature system to determine the detectability of possible faults in the system. Deriving the fault signature system requires knowledge about the controller. This paper demonstrates the possibility of estimating the detectability of faults in the fault signature system using a gap-metric. The gap-metric has the advantage of only requiring knowledge about the plant. By using the gap-metric it is possible to estimate the detectability of faults without using information about the controller. © 2018 IEEE.

关键词： Fault detection

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Object-Based Probabilistic Place Recognition for Indoor Human Environments

Object-Based Probabilistic Place Recognition for Indoor Huma...

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International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO)

作者： Alejandra C. Hernández Clara Gómez Ramón Barber Oscar Martínez Mozos System Engineering and Automation Dept. Carlos III University of Madrid Madrid Spain Dept. of Electronics Computer Tech. and Projects Technical University of Cartagena Cartagena Spain

ISBN: (纸本)9781538695777;9781538695760

Giving a robot autonomy and independence in a human environment implies not only having to move safely but also the ability to understand the environment where it is located. Scene understanding is one of the most challenging tasks in robotics because the design, the objects and the arrangement of them in the scene varies considerably. In this paper we present a Probabilistic Place Recognition Model applied to mobile robots and able to work in indoor human environments. A model of uncertainties is proposed based on the information about the objects in the scene and the relationships between them. This information can influence the final decision about the probability of the presence of a robot in a place. The experimental results obtained of common indoor human environments demonstrate the ability of the model to predict place categories considering the information of the objects and the relations between them. Using more information in the prediction process makes the model more descriptive, scalable and better adapted for human-robot and robot-environment interaction.

关键词： Uncertainty Probabilistic logic Robot sensing systems Feature extraction Visualization Predictive models

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