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2017 IEEE International Conference on Industrial technology, ICIT 2017

作者： Chuang, Ying-Chun Chuang, Hung-Shiang Yang, Chun-Hsiang Chen, Tien-Chi Department of Electrical Engineering Kun Shan University No. 195 Kun-Da Road Yong-Kang District Tainan City71003 Taiwan Guangdong-Taiwan College of Industrial Science and Technology Dongguan University of Technology No. 251 Xueyuan Road Guancheng District Dongguan Guangdong Province China Mechanical and System Research Laboratories Industrial Technology Research Institute No. 195 Sec. 4 Chung Hsing Road Chutung Hsinchu31040 Taiwan Department of Computer and Communication Kun Shan University No. 195 Kun-Da Road Yong-Kang District Tainan City71003 Taiwan

ISBN: (纸本)9781509053209

This work develops a novel single-switch current-fed series-parallel resonant converter for use in direct current (DC) energy conversion systems. The converter comprises a class-E inverter and a series-parallel resonant tank with a bridge rectifier. It uses a single active power switch to reduce the cost of the energy conversion system and control circuits. With a simple circuit configuration and few components, a highly efficient circuit is realized. Experimental data were obtained using a laboratory prototype with an input voltage of 30 V, an output voltage of 16.5 V, an output power of 15.13 W, and a switching frequency of 60 kHz. The measured prototype efficiency was 93.3 % under a full load. Accordingly, the novel converter has great potential for use in low-power DC energy conversion systems. © 2017 IEEE.

关键词： Energy conversion

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Size effect on memristive properties of nanocrystalline ZnO film for resistive synaptic devices

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Journal of Physics: Conference Series 2018年第8期1124卷

作者： N A Shandyba I V Panchenko R V Tominov V A Smirnov M I Pelipenko E G Zamburg Y H Chu Department of Nanotechnology and Microsystems Southern Federal University Taganrog 347928 Russia UAC company BERIEV Taganrog 347923 Russia Department of Electrical & Computer Engineering National University of Singapore 117582 Singapore Department of Materials Science and Engineering National Chiao Tung University Hsinchu 1001 Taiwan Department of Electrophysics National Chiao Tung University Hsinchu 1001 Taiwan Institute of Physics Academia Sinica Taipei 11529 Taiwan Material and Chemical Research Laboratories Industrial Technology Research Institute Hsinchu 31040 Taiwan

Size effect on memristive properties of nanocrystalline ZnO film was investigated. It was shown, ZnO film thickness increase from 6.23±1.54 nm to 47.60±8.12 nm leads to high-resistance state (HRS) increase from 3.26±2.14 MΩ to 700.32±300.83 MΩ and low-resistance state (LRS) from 0.03±0.02 MΩ to 0.09±0.03 MΩ, respectively. The HRS/LRS ratio increases from 108 to 7742. The results can be useful for based on nanocrystalline ZnO films resistive synaptic devices manufacturing.

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Corrigendum to “Thin-film Si 1 − x Ge x HIT solar cells” [Solar Energy 103 (2014) 154–159]

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Solar Energy 2017年 153卷 781-781页

作者： Sabina Abdul Hadi Pouya Hashemi Nicole DiLello Evelina Polyzoeva Ammar Nayfeh Judy L. Hoyt Department of Electrical Engineering and Computer Science (EECS) Masdar Institute of Science and Technology 54224 Abu Dhabi United Arab Emirates Microsystems Technology Laboratories MIT Cambridge MA 02139 USA

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Simultaneous Power Encoding and Upconversion for All-Digital Transmitters Using Digital PWM

Simultaneous Power Encoding and Upconversion for All-Digital...

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Asia-Pacific Microwave Conference

作者： Omer Tanovic Rui Ma Koon Hoo Teo Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA USA Mitsubishi Electric Research Laboratories Cambridge MA USA

Pulse-width modulation (PWM) has recently become very popular power encoding method in all-digital transmitter (ADT) architectures, which employ switch-mode power amplifiers (SMPA) for high power efficiency. Main drawback of PWM is high level of in-band harmonic distortion when digitally implemented, which limits its usage in transceivers realized for software defined radio. Furthermore, upconversion to RF frequency in such ADT systems is commonly done in digital domain. This introduces additional design difficulties, since significant amount of out-of-band harmonic noise, originating from PWM power encoding process, gets folded back into the input signal frequency band, further increasing the total in-band distortion. This paper presents a novel method for simultaneous multilevel power encoding and upconversion to RF frequency, by the means of a ΔΣM-PWM hybrid architecture. It fully exploits time-domain characterization of multilevel carrier-based digital PWM, to both provide optimal parameter selection for ΔΣM (which gives truly aliasing-free digital PWM), and to utilize harmonic nature of the PWM output for upconversion to digital RF frequency. Experiments with an arbitrary waveform generator are used to demonstrate effectiveness of the proposed novel power encoding scheme. The novel algorithm uses 3-level digital PWM and offers in-band SNR of more than -40dB.

关键词： Pulse width modulation Encoding Radio frequency Harmonic analysis Baseband Bandwidth

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Probing the semiconductor to semimetal transition in InAs/GaSb double quantum wells by magneto-infrared spectroscopy

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Physical Review B 2017年第4期95卷 045116-045116页

作者： Y. Jiang S. Thapa G. D. Sanders C. J. Stanton Q. Zhang J. Kono W. K. Lou K. Chang S. D. Hawkins J. F. Klem W. Pan D. Smirnov Z. Jiang School of Physics Georgia Institute of Technology Atlanta Georgia 30332 USA Department of Physics University of Florida Gainesville Florida 32611 USA Department of Electrical and Computer Engineering Department of Physics and Astronomy and Department of Materials Science and NanoEngineering Rice University Houston Texas 77005 USA SKLSM Institute of Semiconductors Chinese Academy of Sciences Beijing 100083 China Synergetic Innovation Center of Quantum Information and Quantum Physics University of Science and Technology of China Hefei Anhui 230026 China Sandia National Laboratories Albuquerque New Mexico 87185 USA National High Magnetic Field Laboratory Tallahassee Florida 32310 USA

We perform a magnetoinfrared spectroscopy study of the semiconductor to semimetal transition of InAs/GaSb double quantum wells from the normal to the inverted state. We show that owing to the low carrier density of our samples, the magnetoabsorption spectra evolve from a single cyclotron resonance peak in the normal state to multiple absorption peaks in the inverted state with distinct magnetic field dependence. Using an eight-band Pidgeon-Brown model, we explain all the major absorption peaks observed in our experiment. We demonstrate that the semiconductor to semimetal transition can be realized by manipulating the quantum confinement, the strain, and the magnetic field. Our work paves the way for band engineering of optimal InAs/GaSb structures for realizing novel topological states as well as for device applications in the terahertz regime.

关键词： Band gap Landau levels Semiconductors Quantum wells Infrared spectroscopy

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Nano-Intrinsic true random number generation

arXiv

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arXiv 2017年

作者： Kim, Jeeson Ahmed, Taimur Nili, Hussein Truong, Nhan Duy Yang, Jiawei Jeong, Doo Seok Sriram, Sharath Ranasinghe, Damith C. Kavehei, Omid Nanoelectronic and Neuroinspired Research Laboratory RMIT University VIC3000 Australia Functional Materials and Microsystems Research Group RMIT University VIC3000 Australia Department of Electrical and Computer Engineering University of California Santa BarbaraCA93106 United States Wenzhou Medical University China Electronic Materials Research Centre Korea Institute of Science and Technology Seoul136-791 Korea Republic of Auto-ID Labs School of Computer Science University of Adelaide SA5005 Australia

Recent advances in predictive data analytics and ever growing digitalization and connectivity with explosive expansions in industrial and consumer Internet-of-Things (IoT) has raised significant concerns about security of people's identities and data. It has created close to ideal environment for adversaries in terms of the amount of data that could be used for modeling and also greater accessibility for side-channel analysis of security primitives and random number generators. Random number generators (RNGs) are at the core of most security applications. Therefore, a secure and trustworthy source of randomness is required to be found. Here, we present a differential circuit for harvesting one of the most stochastic phenomenon in solid-state physics, random telegraphic noise (RTN), that is designed to demonstrate significantly lower sensitivities to other sources of noises, radiation and temperature fluctuations. We use RTN in amorphous SrTiO3-based resistive memories to evaluate the proposed true random number generator (TRNG). Successful evaluation on conventional true randomness tests (NIST tests) has been shown. Robustness against using predictive machine learning and side-channel attacks have also been demonstrated in comparison with non-differential readouts methods. Copyright © 2017, The Authors. All rights reserved.

关键词： Stochastic systems

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Optimal distributed control for platooning via sparse coprime factorizations

Optimal distributed control for platooning via sparse coprim...

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2016 American Control Conference, ACC 2016

作者： SabǍu, Şerban OarǍ, Cristian Warnick, Sean Jadbabaie, Ali Electrical and Computer Engineering Dept. Stevens Institute of Technology HobokenNJ United States Automatic Control Dept. University Politehnica Bucharest Romania Information and Decision Algorithms Laboratories Faculty of the Computer Science Department Brigham Young University United States Electrical and Systems Engineering Dept. University of Pennsylvania United States

ISBN: (纸本)9781467386821

We introduce a novel distributed control architecture for disturbances attenuation in heterogeneous platoons of linear and time-invariant autonomous agents that inherits the performance achievable by the leader-follower control policies. We provide a Youla-like parameterization for the class of all distributed controllers such that the sparsity constraints are imposed on the controllers' left coprime factors, outlining a new concept of structural constraints in distributed control. The proposed scheme lends itself to optimal controller design via norm based costs, it guarantees string stability and completely eliminates the accordion effect from the behavior of the platoon. The distributed controller is proven to attain global optimality for heterogeneous platoons and H2 costs and can easily reconfigure such as to remain optimal during formation merging/exiting maneuvers. The scheme is amenable to a GPS time base synchronization mechanism, allowing for the exact compensation of the time delays induced by the wireless communications. © 2016 American Automatic Control Council (AACC).

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3D Visual Perception for Self-Driving Cars using a Multi-Camera System: Calibration, Mapping, Localization, and Obstacle Detection

arXiv

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arXiv 2017年

作者： Häne, Christian Heng, Lionel Lee, Gim Hee Fraundorfer, Friedrich Furgale, Paul Sattler, Torsten Pollefeys, Marc Department of Electrical Engineering and Computer Sciences University of California Berkeley BerkeleyCA94720 United States Department of Computer Science ETH Zürich Universitätstrasse 6 Zürich8092 Switzerland Information Division DSO National Laboratories 12 Science Park Drive Singapore118225 Singapore Department of Computer Science National University of Singapore 13 Computing Drive Singapore117417 Singapore Institute for Computer Graphics & Vision Graz University of Technology Inffeldgasse 16 GrazA-8010 Austria Department of Mechanical and Process Engineering ETH Zürich Leonhardstrasse 21 Zürich8092 Switzerland Microsoft One Microsoft Way RedmondWA98052 United States

Cameras are a crucial exteroceptive sensor for self-driving cars as they are low-cost and small, provide appearance information about the environment, and work in various weather conditions. They can be used for multiple purposes such as visual navigation and obstacle detection. We can use a surround multi-camera system to cover the full 360-degree field-of-view around the car. In this way, we avoid blind spots which can otherwise lead to accidents. To minimize the number of cameras needed for surround perception, we utilize fisheye cameras. Consequently, standard vision pipelines for 3D mapping, visual localization, obstacle detection, etc. need to be adapted to take full advantage of the availability of multiple cameras rather than treat each camera individually. In addition, processing of fisheye images has to be supported. In this paper, we describe the camera calibration and subsequent processing pipeline for multi-fisheye-camera systems developed as part of the V-Charge project. This project seeks to enable automated valet parking for self-driving cars. Our pipeline is able to precisely calibrate multi-camera systems, build sparse 3D maps for visual navigation, visually localize the car with respect to these maps, generate accurate dense maps, as well as detect obstacles based on real-time depth map extraction. Copyright © 2017, The Authors. All rights reserved.

关键词： Calibration

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Evaluating race and sex diversity in the world's largest companies using deep neural networks

arXiv

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arXiv 2017年

作者： Chekanov, Konstantin Mamoshina, Polina Yampolskiy, Roman V. Timofte, Radu Scheibye-Knudsen, Morten Zhavoronkov, Alex Youth Laboratories Ltd Diversity Ai Group Skolkovo Innovation Center Nobel Street 5 Moscow143026 Insilico Medicine Emerging Technology Centers Jhu 1101 33rd Street BaltimoreMD21218 United States Computer Science Department University of Oxford Oxford United Kingdom Computer Engineering and Computer Science Duthie Center for Engineering University of Louisville LouisvilleKY40292 United States Computer Vision Lab Department of Information Technology and Electrical Engineering Eth Zürich Switzerland Center for Healthy Aging Department of Cellular and Molecular Medicine University of Copenhagen Biogerontology Research Foundation 2354 Chynoweth House Trevissome Park TruroTR4 8UN United Kingdom Moscow Institute of Physics and Technology Institutskiy per. 9 Dolgoprudny141701 Russia

Diversity is one of the fundamental properties for survival of species, populations and organizations. Recent advances in deep learning allow for the rapid and automatic assessment of organizational diversity and possible discrimination by race, sex, age and other parameters. Automating the process of assessing the organizational diversity using the deep neural networks and eliminating the human factor may provide a set of real-time unbiased reports to all stakeholders. In this pilot study we applied the deep learned predictors of race and sex to the executive management and board member profiles of the 500 largest companies from the 2016 Forbes Global 2000 list and compared the predicted ratios to the ratios within each company's country of origin and ranked them by the sex-, age- and race- diversity index (DI). While the study has many limitations and no claims are being made concerning the individual companies, it demonstrates a method for the rapid and impartial assessment of organizational diversity using deep neural networks. Copyright © 2017, The Authors. All rights reserved.

关键词： Deep neural networks

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Gene expression imputation across multiple brain regions provides insights into schizophrenia risk (vol 51, pg 659, 2019)

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NATURE GENETICS 2019年第6期51卷 1068-1068页

作者： Huckins, Laura M. Dobbyn, Amanda Ruderfer, Douglas M. Hoffman, Gabriel Wang, Weiqing Pardinas, Antonio F. Rajagopal, Veera M. Als, Thomas D. Nguyen, Hoang T. Girdhar, Kiran Boocock, James Roussos, Panos Fromer, Menachem Kramer, Robin Domenici, Enrico Gamazon, Eric R. Purcell, Shaun Demontis, Ditte Borglum, Anders D. Walters, James T. R. O'Donovan, Michael C. Sullivan, Patrick Owen, Michael J. Devlin, Bernie Sieberts, Solveig K. Cox, Nancy J. Im, Hae Kyung Sklar, Pamela Stahl, Eli A. Pamela Sklar Division of Psychiatric Genomics Icahn School of Medicine at Mount Sinai New York NY USA Department of Genetics and Genomics Icahn School of Medicine at Mount Sinai New York NY USA Department of Psychiatry Icahn School of Medicine at Mount Sinai New York NY USA Icahn Institute for Genomics and Multiscale Biology Icahn School of Medicine at Mount Sinai New York NY USA Vanderbilt University Medical Center Nashville TN USA MRC Centre for Neuropsychiatric Genetics and Genomics Cardiff University Cardiff UK Department of Biomedicine Aarhus University Aarhus Denmark The Lundbeck Foundation Initiative for Integrative Psychiatric Research iPSYCH Denmark Center for Integrative Sequencing Aarhus University Aarhus Denmark Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los Angeles CA USA Human Brain Collection Core National Institute of Mental Health Bethesda MD USA Laboratory of Neurogenomic Biomarkers Centre for Integrative Biology (CIBIO) University of Trento Trento Italy Clare Hall University of Cambridge Cambridge UK University of North Carolina at Chapel Hill Chapel Hill NC USA Karolinska Institutet Stockholm Sweden Department of Psychiatry University of Pittsburgh Pittsburgh PA USA Systems Biology Sage Bionetworks Seattle WA USA Section of Genetic Medicine Department of Medicine University of Chicago Chicago IL USA Integrated Technology Research Laboratories Pharmaceutical Research Division Takeda Pharmaceutical Company Limited Fujisawa Japan Neuropsychiatry Section Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Neuropsychiatric Signaling Program Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Psychiatry JJ Peters Virginia Medical Center Bronx NY USA Department of Neuroscience Icahn School of Medicine at Mount Sinai New York New York NY USA Friedman Brain Institute

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression.

关键词： Gene expression Genome-wide association studies Schizophrenia Transcriptomics

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