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2nd IEEE International Conference on Electronic engineering, ICEEM 2021

作者： El-Fiky, Azza Shouman, Marwa Ahmed Hamada, Salwa El-Sayed, Ayman Karar, Mohamed Esmail Electronics Research Institute Department of Informatics Cairo Egypt Menoufia University Faculty of Electronic Engineering Department of Computer Science and Engineering Minuf Egypt Menoufia University Faculty of Electronic Engineering Dept. Industrial Electronics and Control Engineering Minuf Egypt

ISBN: (纸本)9781665418423

Chest radiography presents one of the main medical imaging modalities for diagnosing lung diseases. To assist radiologists during interventional procedures, this paper aims at proposing a transfer learning-based classifier to automatically identify 14 different thoracic diseases in Chest X-ray (CXR) images. The proposed method is relied on deep residual neural networks with 50 layers (ResNet-50) to accomplish the diagnostic task of many chest diseases. In this study, a public dataset of 112, 120 frontal radiograph images for Chest X-ray has been used for validating the proposed deep learning classifier. It achieved the best performance of multi-label classification of normal and 14 different lung diseases with an average area under curve (AUC) of 0.911 and F1-score of 0.66. This study demonstrated that the proposed ResNet-50 classifier as a transfer learning model outperforms other relevant methods in the previous studies for automatic multi-label classification of chest X-rays. © 2021 IEEE.

关键词： computer aided diagnosis

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Differential Co-expression Network Analysis to Investigate Sexual Dimorphism in Colon Cancer

Differential Co-expression Network Analysis to Investigate S...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Caterina Alfano Lorenzo Farina Manuela Petti PhD program in Network Oncology and Precision Medicine Sapienza University of Rome Rome Italy Dept. of Computer Control and Management Engineering PhD program in Network Oncology and Precision Medicine Sapienza University of Rome Rome Italy Dept. of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

Colorectal cancer is the third most diagnosed cancer in the world, but it has a higher mortality rate in men compared to women. However, we are not close to understanding how and why sex influences the outcome of the disease. This study focuses on mRNA expression profiles of colon cancer patients to look for molecular differences in the development of colon cancer between men and women. We used paired expression data (i.e., data collected in pairs of normal and cancer cells, by taking samples from the same individual), we identified differentially expressed genes (cancer vs normal) and computed co-expression and differential co-expression gene networks (men vs women). Doing so, we inferred the main changes and alterations happening in cancer tissues, and specifically how these changes were different among men and women. We found that the co-expression networks of women and men affected by colon cancer are quite different and we reported the genes that show the most differences in this comparison, checking if they could also be associated to sexual dimorphism or sexual hormones. Among these genes we found a interesting presence of genes associated to the Wnt signaling pathway which has been found to be regulated by estrogen and whose activation is strongly linked with colon cancer.

关键词： Network analyzers Biochemistry Colon Bioinformatics Cancer

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A moment matching-based loop shaping design with closed-loop pole placement

A moment matching-based loop shaping design with closed-loop...

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European control Conference (ECC)

作者： T. C. Ionescu O. V. Iftime R. Ştefan Dept. of Automatic Control & Systems Eng Politehnica Univ. of Bucharest Bucharest Romania “G. Mihoc-C. Iacob” Institute of Mathematical Statistics and Applied Mathematics of the Romanian Academy Bucharest Romania Department of Economics Econometrics and Finance Faculty of Economics and Business University of Groningen Nettelbosje 2 Groningen The Netherlands Department of Automatic Control and Systems Engineering University Politehnica Bucharest Bucharest Romania

In this paper, moment matching-based loop shaping design for finite-dimensional linear systems is considered. First, the time-domain moment matching model reduction problem with complex-conjugated pole-zero placement is revisited. We explicitly calculate the free parameters such that the reduced order model, achieving moment-matching at complex-conjugated interpolation points, has pairs of complex-conjugated poles and zeros placed in desired locations. Then, we recast the problem of closed-loop pole placement in terms of moment-matching, with the moments equal to −1 and 0, respectively. Consequently, the free parameters of a model achieving both moment matching at complex-conjugated points and closed-loop pole placement at prescribed locations are determined. Furthermore, we combine the classical loop shaping method with closed-loop pole placement via moment matching to design a robust controller for stable, minimum-phase, proper systems. We illustrate the proposed moment matching-based loop shaping approach on a benchmark example.

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Correlation between wearable inertial sensor data and standardised Parkinson’s disease axial impairment measures using machine learning

Correlation between wearable inertial sensor data and standa...

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Mediterranean Electrotechnical Conference (MELECON)

作者： Luigi Borzi’ Alessandro Manoni Alessandro Zampogna Fernanda Irrera Antonio Suppa Gabriella Olmo Dept. Control and Computer Engineering Politecnico di Torino Turin Italy Dept. Information Engineering Electronics and Telecommunication Sapienza University Rome Italy Dept. Human Neurosciences Sapienza University Rome Italy IRCCS NEUROMED Institute Pozzilli Italy

ISBN: (数字)9781665442800

ISBN: (纸本)9781665442817

Wearable sensors represent a valuable means for monitoring motion signs and symptoms of Parkinson’s disease (PD). In this paper, we explore the potential of a single inertial sensor to yield information correlated to the patient’s subjective perception of axial motion impairment during daily activities. This latter is expressed using as a relevant metric the sum of MDS-UPDRS items 2.11-2.13. Methods: thirty-one patients with PD were enrolled in this study, and asked to perform a timed-up-and-go test while wearing an inertial sensor on their thigh. Several time- and frequency-domain features were extracted from the inertial signals. They were fed to a random forest regression model for the prediction of the axial impairment metric. The model was optimized using 10-fold cross-validation and performance were assessed using leave-one-subject-out test. Results: Pearson correlation coefficient with the addressed metric of 0.76 (0.86) and mean absolute error of 1.70 (1.52) were obtained in patients under (not under) dopaminergic therapy. Moreover, moderate to strong correlations were found between the predicted score and some important disease progression, axial impairment, and motor performance metrics. Conclusion: a single wearable inertial sensor may be used for assessing motor disabilities of patients with PD.

关键词： Measurement Correlation Inertial sensors Thigh Predictive models Feature extraction Biomedical monitoring

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Towards an improvement of the forecast of wind resources in europe: application of unsupervised machine learning on future projections of polar vortex

Towards an improvement of the forecast of wind resources in ...

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2020 Summer computer Simulation Conference, SCSC 2020, Held at the 2020 Summer Simulation Multi-Conference, SummerSim 2020

作者： Montes, María Rodríguez Ayarzagüena, Blanca Mata-García, María Guijarro Complutense University of Madrid Spain Dept. Earth Physics and Astrophysics Complutense University of Madrid Spain Dept. Computer Architecture and Automatic Control Complutense University of Madrid Spain

ISBN: (纸本)9781713819462

Studying the impact of climate change on wintertime polar stratosphere is of particular relevance not only for climate knowledge but also for tropospheric projections. Machine learning provides a way to extract information from different climate models and combine the data in a such way that patterns are clearer, so predictions can be inducted. The methods used in this study have been region growing algorithm, K-means and combination of predictions. The final results show three clusters of response trends for the intensity and location of the stratospheric polar night jet. The prediction shows an increase in zonal wind intensity over the 2xCO2 and 4xCO2 concentration points and a decrease in the related latitude. Our methods can be extended for more climate models and simulation periods, and will allow not only to map the behavior of the polar night jet, but other stratospheric and tropospheric features and interactions between them. ©2020 Society for Modeling & Simulation International (SCS)

关键词： Climate models

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I Can Read Your Mind: control Mechanism Secrecy of Networked Dynamical Systems under Inference Attacks

arXiv

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arXiv 2022年

作者： He, Jianping Li, Yushan Cai, Lin Guan, Xinping The Dept. of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China The Dept. of Electrical and Computer Engineering University of Victoria BC Canada

Recent years have witnessed the fast advance of security research for networked dynamical system (NDS). Considering the latest inference attacks that enable stealthy and precise attacks into NDSs with observation-based learning, this article focuses on a new security aspect, i.e., how to protect control mechanism secrets from inference attacks, including state information, interaction structure and control laws. We call this security property as control mechanism secrecy, which provides protection of the vulnerabilities in the control process and fills the defense gap that traditional cyber security cannot handle. Since the knowledge of control mechanism defines the capabilities to implement attacks, ensuring control mechanism secrecy needs to go beyond the conventional data privacy to cover both transmissible data and intrinsic models in NDSs. The prime goal of this article is to summarize recent results of both inference attacks on control mechanism secrets and countermeasures. We first introduce the basic inference attack methods on the state and structure of NDSs, respectively, along with their inference performance bounds. Then, the corresponding countermeasures and performance metrics are given to illustrate how to preserve the control mechanism secrecy. Necessary conditions are derived to guide the secrecy design. Finally, thorough discussions on the control laws and open issues are presented, beckoning future investigation on reliable countermeasure design and tradeoffs between the secrecy and control performance. Copyright © 2022, The Authors. All rights reserved.

关键词： Cybersecurity

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The Circuit Technique for Reducing the Zero Level of the JFET Op-Amp on the Push-Pull Folded-Cascode

The Circuit Technique for Reducing the Zero Level of the JFE...

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IEEE Region 8 International Conference on Computational Technologies in Electrical and Electronics engineering, SIBIRCON

作者： Nikolay Prokopenko Alexey Titov Vladislav Chumakov Anna Bugakova Dept. of Scientific Research Dept. of Information Systems and Radio Engineering Don State Technical University Institute for Design Problems in Microelectronics of the RAS Rostov-on-Don Zelenograd Russia Dept. of Automatic Control Systems Southern Federal University Rostov-on-Don Russia Dept. of Scientific Research Dept. of Information Systems and Radio Engineering Don State Technical University Rostov-on-Don Russia

ISBN: (纸本)9781665464819

In the paper, the authors describe the improved operational amplifier architecture (op-amp). Complementary FETs with the p-n-junction control were used in the design of this op-amp, depletion-mode complementary MOS can also be used. The character of the suggested op-amp is to create conditions that contribute to obtaining low systematical constituent offset voltage (V off ), which significantly depends on the change in the drain-gate specifications of transistors when the static voltages on their drains change. It should be noted that the high symmetric of the static regimen of the input transistors and output transistors of the folded-cascode of the suggested op-amp is supplied to reduce this constituent V off in the considered op-amp circuit. computer modelling of the op-amp carried out in the LTSpice was fulfilled in the large range of temperatures (from -197°C to 27°C). The suggested circuit design minimizes the systematical constituent V off (below 30 µV) and increases the open-loop gain of op-amp to 60 dB. The JFET op-amp circuitry suggested in the paper is advised to analog-to-digital and analog interfaces, incl. those operating at exposure to radiation and low temperatures.

关键词： Operational amplifiers Temperature distribution Computational modeling Instruments Mathematical analysis Liquid nitrogen JFETs

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Intelligent Operational Decision Support System for Sugar Factory Resource Efficiency

Intelligent Operational Decision Support System for Sugar Fa...

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International Conference on Modern Electrical and Energy Systems (MEES)

作者： Nataliia Lutska Nataliia Zaiets Lidiia Vlasenko Stefan Junge Dept. of Automation and Computer Technologies of Control Systems National University of Food Technologies Kyiv Ukraine Dept. of Automation and Robotic Systems National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine Dept. of Software Engineering and Cyber Security State University of Trade and Economics Kyiv Ukraine Dept. of Packaging Technology Berlin University of Applied Sciences Berlin Germany

With the economic crisis that is looming over the world due to changes in the energy sector and a reduction in the supply of certain types of products, energy and resource efficiency issues are becoming more relevant for the food industry. Also important is the preservation of the environment and the implementation of Cleaner Production trends. Most enterprises follow the concept of Industry 4.0 and increase efficiency through the implementation of intelligent methods, in particular machine learning. The paper proposes a neural network model of sugar production. The model makes it possible to predict the main estimates of resource efficiency used to correct the technological modes of production by the operator-technologist. The structure of the operational decision support system has been developed and is used by personnel to model and predict changes in resource efficiency estimates and KPIs calculated on their basis. Its feature is the integration of methods for achieving resource efficiency, improving environmental performance and ensuring KPIs. To do this, at the initial stage, an analysis of the main flows that affect resource efficiency and an assessment of their importance was carried out. Ensuring Production Performance is confirmed by the simulation and the adequacy of the created neural network accuracy of more than 95%.

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Contagion Propagation with Rule-Based Reasoning and Decentralized control in an Agent-Based Susceptible-Infected-Recovered-Susceptible Infodemic Model

Contagion Propagation with Rule-Based Reasoning and Decentra...

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Big Data, Knowledge and control Systems engineering (BdKCSE)

作者： Cristian Berceanu Nadia Arshad Monica Patrascu Dept. of Automatic Control and Systems Engineering Complex Systems Laboratory University Politehnica of Bucharest Bucharest Romania Dept. of Global Public Health and Primary Care Section for Epidemiology and Medical Statistics University of Bergen Bergen Norway Complex Systems Laboratory University Politehnica of Bucharest Dept. of Global Public Health and Primary Care Centre for Elderly and Nursing Home Medicine University of Bergen Bergen Norway

In recent years, and especially during the on-going pandemic, the interest in investigating the dynamics of infodemics has increased to unprecedented levels. In this study we propose an agent-based model for the spread of misinformation, disinformation, and other similar information. The model is based on the susceptible-infected-recovered-susceptible epidemic interpretation. We introduce a rule-based reasoning module to model individual bias in the perception of information based on the psychology concept of illusion of knowledge. We integrate this module into a deliberative-reactive agent controller structure and a decentralized control scheme for the multi-agent system. Results show significant differences between the outputs of the proposed model and the classical version, impressing on the effects of considering local agent individuality when modeling human psycho-social interactions.

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Live Demo: E2P-Events to Polarization Reconstruction from PDAVIS Events

Live Demo: E2P-Events to Polarization Reconstruction from PD...

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2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Delbruck, Tobi Wang, Zuowen Mei, Haiyang Haessig, Germain Joubert, Damien Haque, Justin Chen, Yingkai Milde, Moritz B. Gruev, Viktor Univ. of Zurich and ETH Zurich Sensors Group Institute of Neuroinformatics Switzerland Center for Vision Automation & Control High-Performance Vision Systems AIT Austrian Institute of Technology Vienna Austria Western Sydney University Intl. Centre for Neuromorphic Systems The MARCS Institute Sydney Australia University of Illinois at Urbana-Champaign Dept. of Electrical and Computer Engineering UrbanaIL United States

This demonstration shows live operation of of PDAVIS polarization event camera reconstruction by the E2P DNN reported in the main CVPR conference paper Deep Polarization Reconstruction with PDAVIS Events (paper 9149 [... 详细信息

ISBN: (纸本)9798350302493

关键词： Polarization

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