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A Machine Learning-Based Microwave Device Model for Fully Printed VO2 RF Switches

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A Machine Learning-Based Microwave Device Model for Fully Pr...

European Conference on Microwave

作者： Shuai Yang Ahmad Khusro Weiwei Li Mohammad Vaseem Mohammad Hashmi Atif Shamim CEMSE Division King Abdullah University of Science and Technology Electrical Engineering Program Thuwal Saudi Arabia Jamia Millia Islamia New Delhi India Nazarbayev University Astana Kazakhstan

ISBN: (数字)9782874870590

ISBN: (纸本)9781728170398

Fully printed vanadium dioxide (VO 2 ) based Radio Frequency (RF) switches have been recently developed for advanced frequency-reconfigurable RF electronics. A reliable and versatile model for the VO 2 switches is required for design and simulations in the modern Computer-Aided Design (CAD) tools. This paper proposes a machine learning (ML) based model for VO 2 RF switches, which is much more time and resource efficient as compared to the traditional device models. The computational efficiency, accuracy and robustness of the proposed model over a frequency range of 30 GHz is demonstrated through an excellent agreement between the modelled and measured results. The comparison between the measured and modelled results demonstrate a mean-square error (MSE) of lower than 5 × 10 -4 and 5 × 10 -3 for the magnitude and phase values over the complete frequency range.

关键词： Radio frequency Microwave measurement Solid modeling Analytical models Computational modeling Tools Frequency measurement

Alternative Role of Motif B in Template Dependent Polymerase Inhibition

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Chinese Journal of Chemical Physics 2022年第3期35卷 407-412,I0001页

作者： Xueying Luo Tiantian Xu Xin Gao Lu Zhang State Key Laboratory of Structural Chemistry Fujian Institute of Research on the Structure of MatterChinese Academy of SciencesFuzhou 350002China University of Chinese Academy of Sciences Beijing 100049China Computer Science Program ComputerElectrical and Mathematical Sciences and Engineering(CEMSE)DivisionKing Abdullah University of Science and TechnologyThuwal 23955-6900King-dom of Saudi Arabia KAUST Computational Bioscience Research Center(CBRC) King Abdullah University of Science and TechnologyThuwal 23955-6900Kingdom of Saudi Arabia Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry Xiamen 361005China

Severe acute respiratory syndrome coronavirus 2(SARS-Co V-2) relies on the central molecular machine RNA-dependent RNA polymerase(Rd Rp) for the viral replication and transcription. Remdesivir at the template strand has been shown to effectively inhibit the RNA synthesis in SARS-Co V-2 Rd Rp by deactivating not only the complementary UTP incorporation but also the next nucleotide addition. However, the underlying molecular mechanism of the second inhibitory point remains unclear. In this work, we have performed molecular dynamics simulations and demonstrated that such inhibition has not directly acted on the nucleotide addition at the active site. Instead, the translocation of Remdesivir from +1 to-1 site is hindered thermodynamically as the posttranslocation state is less stable than the pre-translocation state due to the motif B residue G683. Moreover, another conserved residue S682 on motif B further hinders the dynamic translocation of Remdesivir due to the steric clash with the 1′-cyano substitution. Overall,our study has unveiled an alternative role of motif B in mediating the translocation when Remdesivir is present in the template strand and complemented our understanding about the inhibitory mechanisms exerted by Remdesivir on the RNA synthesis in SARS-Co V-2 Rd Rp.

关键词： SARS-CoV-2 RNA-dependent RNA polymerase Inhibitory mechanism Nu-cleotide analog Molecular dynamics simulation

Exploring the Non - Hermitian Topology of Exceptional Points in Lasers and Fiber Loops

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Exploring the Non - Hermitian Topology of Exceptional Points...

Conference on Lasers and Electro-Optics Europe (CLEO EUROPE)

作者： Alexander Schumer Hadiseh Nasari Yuzhou G. N. Liu Gisela Lopez-Galmiche Jason Leshin Helena E. Lopez-Aviles Lei Ding Yousef Alahmadi Absar U. Hassan Qi Zhong Stefan Rotter Patrick LiKamWa Demetrios N. Christodoulides Mercedeh Khajavlkhan Institutefor Theoretical Physics Vienna University of Technology (TU Wien) Vienna Austria Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los Angeles USA CREOL The College of Optics & Photonics University of Central Florida Orlando FL USA Center of Excellence for Telecomm Applications Joint Centers of Excellence Program King Abdul Aziz City for Science and Technology Riyadh Saudi Arabia Department of Physics & Astronomy University of Southern California Los Angeles CA USA

ISBN: (纸本)9798350345995

When non-Hermitian eigenvalue surfaces form intertwined Riemann surfaces, the corresponding non-Hermitian singularities, also know as exceptional points (EPs), are located at the center of this specific topology. Various experimental platforms have recently been presented in which interesting new physics associated with these branch point singularities can be explored. In particular, it has been shown that dynamically encircling EPs may lead to a so-called chiral state transfer. The chirality in this context refers to the fact that in such an encircling protocol, the final state at the end of an EP -enclosing loop solely depends on the encircling direction (clockwise or counterclockwise), but not on the initial state. Such a chiral behavior is intrinsically linked to the state vector deviating from adiabatically following the system's eigenstates associated with the eigenvalue surfaces; instead, due to the non-Hermitian violation of the adiabatic theorem, non-adiabatic jumps let the system undergo transitions from lossy eigenstates to eigenstates with gain. Here, we present two experiments that implement concepts that go beyond this established paradigm.

关键词： Attenuation Chirality Fiber lasers Lasers Surfaces Waveguides

IoT smart wheelchair (I-SMILE): Ease of accessibility of persons with disability in society 5.0 to realize sustainable development goals in 2030

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AIP Conference Proceedings 2024年第1期3215卷

作者： Eriyadi Nata Syahputra Dananjaya Ariateja Tiara Rahayu Randi Agustio Corrina Lailatul Fadjri Wina Nur Saputri Electrical Engineering Study Program Departement of Defense Science and Technology Universitas Pertahanan Republik Indonesia Bogor Indonesia 16810 Biology Study Program Departement of Mathematics and Natural Sciences Universitas Pertahanan Republik Indonesia Bogor Indonesia 16810

WHO reports in 2022, that more than 2.5 billion people need assistive products such as wheelchairs in support of persons with disabilities. The research was conducted by making an I-SMILE prototype design and a mobile app mockup design. Followed by analysis and evaluation of the shortcomings of the built system are carried out consisting of the input part a network of sensors, the main control unit, and an output section consisting of several actuators. The results of the analysis of the trial are the ultrasonic sensor HC-SR04 itself where if the wheelchair approaches a barrier object such as a wall and others within a distance of 30 cm. MPU6050 sensor where this sensor is a Gyro sensor that is used to detect the level of the slope. The GPS sensor is Ublox Neo 7m which can use to monitor the position. The gas sensor is MQ 135 which can detect several gases such as alcohol, CO2, ammonia, and cigarette smoke. The heart rate detection sensor MAX 30100 monitors the heart rate in real-time, anti-decubitus cushion pillow, a belt for safe movement, three buttons for helping eat, go toilet, and ask for help, and all sensors monitor via smartphone. The innovation of the IoT Smart Wheelchair (I-SMILE) concept as an assistive technology in the society 5.0 era for increasing the functional independence of persons with disability. This is in line to achieve the 2030 SDGs towards the fulfillment of the rights of a person with disabilities in protection, quality, and sustainable education, and decent and equitable work.

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Single-Input Polarization-Sensitive Optical Coherence Tomography Through a Catheter

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arXiv 2023年

作者： Jones, Georgia L. Xiong, Qiaozhou Liu, Xinyu Bouma, Brett E. Villiger, Martin Wellman Center for Photomedicine Massachusetts General Hospital Harvard Medical School BostonMA02114 United States Institute for Medical Engineering and Science Massachusetts Institute of Technology CambridgeMA02142 United States School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore Singapore Eye Research Institute Singapore National Eye Centre Singapore169856 Singapore Academic Clinical Program Duke-NUS Medical School Singapore169857 Singapore

Intravascular polarimetry with catheter-based polarization-sensitive optical coherence tomography (PS-OCT) complements the high-resolution structural tomograms of OCT with morphological contrast available through polarimetry. Its clinical translation has been complicated by the need for modification of conventional OCT hardware to enable polarimetric measurements. Here, we present a signal processing method to reconstruct polarization properties of tissue from measurements with a single input polarization state, bypassing the need for modulation or multiplexing of input states. Our method relies on a polarization symmetry intrinsic to round-trip measurements and uses the residual spectral variation of the polarization states incident on the tissue to avoid measurement ambiguities. We demonstrate depth-resolved birefringence and optic axis orientation maps reconstructed from in-vivo data of human coronary arteries. We validate our method through comparison with conventional dual-input state measurements and find a mean cumulative retardance error of 13.2deg without observable bias. The 95% limit of agreement between depth-resolved birefringence is 2.80 ‧ 10−4, which is less than the agreement between two repeat pullbacks of conventional PS-OCT (3.14 ‧ 10−4 ), indicating that the two methods can be used interchangeably. The hardware simplification arising from using a single input state may be decisive in realizing the potential of polarimetric measurements for assessing coronary atherosclerosis in clinical practice. © 2023, CC BY.

关键词： Tissue

Intrinsic synaptic plasticity of ferroelectric field effect transistors for online learning

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arXiv 2021年

作者： Saha, Arnob Nafiul Islam, A.N.M. Zhao, Zijian Deng, Shan Ni, Kai Sengupta, Abhronil School of Electrical Engineering & Computer Science Pennsylvania State University University ParkPA16802 United States Microsystems Engineering Ph.D. program Rochester Institute of Technology RochesterNY14623 United States

Nanoelectronic devices emulating neuro-synaptic functionalities through their intrinsic physics at low operating energies is imperative toward the realization of brain-like neuromorphic computers. In this work, we leverage the non-linear voltage dependent partial polarization switching of a ferroelectric field effect transistor to mimic plasticity characteristics of biological synapses. We provide experimental measurements of the synaptic characteristics for a 28nm high-k metal gate technology based device and develop an experimentally calibrated device model for large-scale system performance prediction. Decoupled read-write paths, ultra-low programming energies and the possibility of arranging such devices in a cross-point architecture demonstrate the synaptic efficacy of the device. Our hardware-algorithm co-design analysis reveals that the intrinsic plasticity of the ferroelectric devices has potential to enable unsupervised local learning in edge devices with limited training data. Copyright © 2021, The Authors. All rights reserved.

关键词： E-learning

Meaningful human control: actionable properties for AI system development

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arXiv 2021年

作者： Siebert, Luciano Cavalcante Lupetti, Maria Luce Aizenberg, Evgeni Beckers, Niek Zgonnikov, Arkady Veluwenkamp, Herman Abbink, David Giaccardi, Elisa Houben, Geert-Jan Jonker, Catholijn M. van den Hoven, Jeroen Forster, Deborah Lagendijk, Reginald L. AiTech Interdisciplinary Research Program on Meaningful Human Control Delft University of Technology Delft Netherlands Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft Netherlands Faculty of Industrial Design Engineering Delft University of Technology Delft Netherlands Faculty of Mechanical Maritime and Materials Engineering Delft University of Technology Delft Netherlands Faculty of Technology Policy and Management Delft University of Technology Delft Netherlands

How can humans remain in control of artificial intelligence (AI)-based systems designed to perform tasks autonomously? Such systems are increasingly ubiquitous, creating benefits - but also undesirable situations where moral responsibility for their actions cannot be properly attributed to any particular person or group. The concept of meaningful human control has been proposed to address responsibility gaps and mitigate them by establishing conditions that enable a proper attribution of responsibility for humans;however, clear requirements for researchers, designers, and engineers are yet inexistent, making the development of AI-based systems that remain under meaningful human control challenging. In this paper, we address the gap between philosophical theory and engineering practice by identifying, through an iterative process of abductive thinking, four actionable properties for AI-based systems under meaningful human control, which we discuss making use of two applications scenarios: automated vehicles and AI-based hiring. First, a system in which humans and AI algorithms interact should have an explicitly defined domain of morally loaded situations within which the system ought to operate. Second, humans and AI agents within the system should have appropriate and mutually compatible representations. Third, responsibility attributed to a human should be commensurate with that human’s ability and authority to control the system. Fourth, there should be explicit links between the actions of the AI agents and actions of humans who are aware of their moral responsibility. We argue that these four properties will support practically-minded professionals to take concrete steps toward designing and engineering for AI systems that facilitate meaningful human control. Copyright © 2021, The Authors. All rights reserved.

关键词： Artificial intelligence

Deep Learning with Greedy Layer-Wise Compound Scaling for Temperature and Humidity Prediction in Solar Dryer Dome

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SSRN

SSRN 2022年

作者： Cenggoro, Tjeng Wawan Elwirehardja, Gregorius Natanael Dominic, Nicholas Setiawan, Karli Eka Rahutomo, Reza Djuana, Endang Gunawan, Fergyanto E. Budiman, Arief S. Romeli, Sugiarto Pardamean, Bens Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Electrical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta11440 Indonesia Industrial Engineering Department BINUS Graduate Program Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia Department of Manufacturing and Mechanical Engineering and Technology Oregon Institute of Technology Klamath FallsOR97601 United States PT. Impack Pratama Industri Jakarta Indonesia

Drying has been an eco-friendly and cost-efficient method to reduce post-harvest losses of agricultural crops. In various countries, the technique has been widely utilized in the form of Solar Dryer Dome (SDD) buildings. Accurate indoor microclimate forecasting is very important to implement smart control systems in SDDs that can maintain the ideal conditions, as the availability of solar energy is limited only at daytimes and the temperature may drop significantly during nighttimes in remote areas. The microclimate variables that play an important role in maintaining ideal environmental conditions include temperature and relative humidity. © 2022, The Authors. All rights reserved.

关键词： Forecasting

CONVERGENCE SPEED AND APPROXIMATION ACCURACY OF NUMERICAL MCMC

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arXiv 2022年

作者： Cui, Tiangang Dong, Jing Jasra, Ajay Tong, Xin T. School of Mathematics Monash University Australia Graduate School of Business Columbia University United States Applied Mathematics and Computational Science Program Computer Electrical Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Saudi Arabia Department of Mathematics National University of Singapore Singapore

When implementing Markov Chain Monte Carlo (MCMC) algorithms, perturbation caused by numerical errors is sometimes inevitable. This paper studies how perturbation of MCMC affects the convergence speed and Monte Carlo estimation accuracy. Our results show that when the original Markov chain converges to stationarity fast enough and the perturbed transition kernel is a good approximation to the original transition kernel, the corresponding perturbed sampler has similar convergence speed and high approximation accuracy as well. We discuss two different analysis frameworks: ergodicity and spectral gap, both are widely used in the literature. Our results can be easily extended to obtain non-asymptotic error bounds for MCMC estimators. We also demonstrate how to apply our convergence and approximation results to the analysis of specific sampling algorithms, including Random walk Metropolis and Metropolis adjusted Langevin algorithm with perturbed target densities, and parallel tempering Monte Carlo with perturbed densities. Finally we present some simple numerical examples to verify our theoretical claims. Copyright © 2022, The Authors. All rights reserved.

关键词： Inverse problems