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International Conference on High Performance Computing & Simulation (HPCS)

作者： Fatma Karray Melek Maalaoui Abdulfattah M. Obeid Alberto Garcia-Ortiz Mohamed Abid Computer and Embedded System laboratory National Engineering School of Sfax Sfax Tunisia Digital Research Center of Sfax Sfax Tunisia National Center for Electronics and Photonics Technology King Abdulaziz City for Science and Technology (KACST) Riyadh Saudi Arabia Institute of Electrodynamics and Microelectronics (ITEM.ids) Bremen Germany

ISBN: (数字)9781728144849

ISBN: (纸本)9781728144856

The world migration towards automatic and wire-less systems results an increased usage of Wireless Sensor Networks (WSNs). The noticeable popularity of WSNs has imposed enlarged computational in-node demands. Hence, the recourse to fully-integrated and sophisticated systems with low power is a challenging task. Since wireless sensor nodes have limited power resources, it is important to find a balance between energy consumption and computational performance. The traditional software optimizations are not usually suited or enough to find this tradeoff. Consequently, the use of codesign methodology and the careful implementation of hardware accelerator with low frequency processors could offer a good compromise between energy consumption and performance. In this paper, we present a SoC WSN node prototype based on Leon 3 processor for leak detection in water pipeline using Kalman Filter (KF). A hardware acceleration of the KF has been designed and implemented to reduce energy consumption. We have compared also the software implementation of the algorithm and its hardware acceleration in terms of the execution time, the energy consumption and the area requirements. The results show about 97% reduction in energy consumption and execution time without noticeable increased area.

关键词： Wireless sensor networks Leak detection Hardware Mathematical model Pipelines Wireless communication Signal processing algorithms

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A convergence proof of projected fast iterative soft-thresholding algorithm for parallel magnetic resonance imaging

arXiv

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arXiv 2019年

作者： Zhang, Xinlin Lu, Hengfa Guo, Di Bao, Lijun Huang, Feng Qu, Xiaobo Department of Electronic Science Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance School of Electronic Science and Engineering National Model Microelectronics College Xiamen University Xiamen361005 China School of Computer and Information Engineering Fujian Provincial University Key Laboratory of Internet of Things Application Technology Xiamen University of Technology Xiamen361024 China Neusoft Medical System Shanghai200241 China

The boom of non-uniform sampling and compressed sensing techniques dramatically alleviates the prolonged data acquisition problem of magnetic resonance imaging. Sparse reconstruction, thanks to its fast computation and promising performance, has attracted researchers to put numerous efforts on it and has been adopted in commercial scanners. Algorithms for solving the sparse reconstruction models play an essential role in sparse reconstruction. Being a simple and efficient algorithm for sparse reconstruction, pFISTA has been successfully extended to parallel imaging, however, its convergence criterion is still an open question, confusing users on the setting of the parameter which assures the convergence of the algorithm. In this work, we prove the convergence of the parallel imaging version pFISTA. Specifically, the convergences of two well-known parallel imaging reconstruction models, SENSE and SPIRiT, solved by pFISTA are proved. Experiments on brain images demonstrate the validity of the convergence criterion. The convergence criterion proofed in this work can help users quickly obtain the satisfy parameter that admits faithful results and fast convergence speeds. Copyright © 2019, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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Image reconstruction with low-rankness and self-consistency of k-space data in parallel MRI

arXiv

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arXiv 2019年

作者： Zhang, Xinlin Guo, Di Huang, Yiman Chen, Ying Wang, Liansheng Huang, Feng Qu, Xiaobo Department of Electronic Science Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance School of Electronic Science and Engineering National Model Microelectronics College Xiamen University Xiamen361005 China School of Computer and Information Engineering Fujian Provincial University Key Laboratory of Internet of Things Application Technology Xiamen University of Technology Xiamen361024 China Department of Computer Science School of Information Science and Engineering Xiamen University Xiamen361005 China Neusoft Medical System Shanghai200241 China

Parallel magnetic resonance imaging has served as an effective and widely adopted technique for accelerating scans. The advent of sparse sampling offers aggressive acceleration, allowing flexible sampling and better reconstruction. Nevertheless, faithfully reconstructing the image from limited data still poses a challenging task. Recent low-rank reconstruction methods exhibit superiority in providing a high-quality image. However, none of them employ the routinely acquired calibration data for improving image quality in parallel magnetic resonance imaging. In this work, an image reconstruction approach named STDLR-SPIRiT was proposed to explore the simultaneous two-directional low-rankness (STDLR) in the k-space data and to mine the data correlation from multiple receiver coils with the iterative self-consistent parallel imaging reconstruction (SPIRiT). The reconstruction problem was then solved with a singular value decomposition-free numerical algorithm. Experimental results of phantom and brain imaging data show that the proposed method outperforms the state-of-the-art methods in terms of suppressing artifacts and achieving the lowest error. Moreover, the proposed method exhibits robust reconstruction even when the auto-calibration signals are limited in parallel imaging. Overall the proposed method can be exploited to achieve better image quality for accelerated parallel magnetic resonance imaging. Copyright © 2019, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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Preface

引用

CEUR Workshop Proceedings 2021年 2899卷

作者： Kovalev, Igor Semenkin, Eugene Gulyaev, Yuri Barakaev, Nusratilla Shaidurov, Vladimir Škraba, Andrej Tsarev, Roman Legalov, Alexander Saramud, Mikhail Grosspietsch, Karl-Erwin Stupina, Alena Department of Computer Science Siberian Federal University Krasnoyarsk Russia Department of system analysis and operations research of Reshetnev University Krasnoyarsk Russia International and Russian Union of Scientific and Engineering Associations Moscow Russia Rector of Bukhara Engineering Technological Institute Bukhara Uzbekistan Institute of Computational Modeling SB RAS Krasnoyarsk Russia University of Maribor UM Faculty of Organizational Sciences - Cybernetics and Decision Support Systems Laboratory Slovenia Department of Informatics Siberian Federal University Krasnoyarsk Russia Faculty of Computer Science School of Software Engineering HSE University Moscow Russia Department of Informatics Siberian Federal University Krasnoyarsk Russia European Organization for Information and Microelectronics Germany The Siberian Federal University Krasnoyarsk Russia

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Thermal Stress and Reliability Analysis of TSV-Based 3-D ICs With a Novel Adaptive Strategy Finite Element Method

Thermal Stress and Reliability Analysis of TSV-Based 3-D ICs...

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作者： Zhou, Hao Zhu, Hengliang Cui, Tao Pan, David Z. Zhou, Dian Zeng, Xuan State Key Laboratory of ASIC and Systems Department of Microelectronics Fudan University Shanghai200433 China State Key Laboratory of Scientific and Engineering Computing National Center for Mathematics and Interdisciplinary Sciences Institute of Computational Mathematics Academy of Mathematics and System Sciences Chinese Academy of Sciences Beijing100190 China Department of Electrical and Computer Engineering University of Texas at Austin AustinTX78712 United States Department of Electrical Engineering University of Texas at Dallas RichardsonTX75080 United States

Thermomechanical stress is one of the most important issues in performance and reliability analysis of through silicon via-based 3-D integrated circuits (3-D ICs), where an accurate numerical approach is generally needed to produce stress models and identify weak points in the structure. In this paper, we propose a knowledge-oriented nonuniform (KONU) refinement strategy for 3-D IC stress simulation under the framework of a parallel adaptive finite element method (FEM), and apply it in 3-D IC stress and reliability analysis. Parallel adaptive FEM is promising for solving large-scale problems due to its high accuracy and parallel efficiency. It produces refined meshes based on the a posteriori error analysis, which has the quasi-optimal convergence rate for solving the problem. It has high parallel efficiency, which makes it suitable for handling large and complex structures in 3-D ICs. The KONU refinement strategy developed in this paper can efficiently reduce the number of refinement iterations in parallel adaptive FEM for 3-D IC thermomechanical stress simulation and improves the computational efficiency. It is demonstrated in this paper through several examples that parallel adaptive FEM for thermomechanical stress evaluation can be widely applied in 3-D IC reliability analysis, where accurate stress simulation and modeling is exceptionally important to produce accurate results. © 2018 IEEE.

关键词： Reliability analysis

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Technology Roadmap for Flexible Sensors

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ACS NANO 2023年第6期17卷 5211-5295页

作者： Luo, Yifei Abidian, Mohammad Reza Ahn, Jong-Hyun Akinwande, Deji Andrews, Anne M. Antonietti, Markus Bao, Zhenan Berggren, Magnus Berkey, Christopher A. Bettinger, Christopher John Chen, Jun Chen, Peng Cheng, Wenlong Cheng, Xu Choi, Seon-Jin Chortos, Alex Dagdeviren, Canan Dauskardt, Reinhold H. Di, Chong-an Dickey, Michael D. Duan, Xiangfeng Facchetti, Antonio Fan, Zhiyong Fang, Yin Feng, Jianyou Feng, Xue Gao, Huajian Gao, Wei Gong, Xiwen Guo, Chuan Fei Guo, Xiaojun Hartel, Martin C. He, Zihan Ho, John S. Hu, Youfan Huang, Qiyao Huang, Yu Huo, Fengwei Hussain, Muhammad M. Javey, Ali Jeong, Unyong Jiang, Chen Jiang, Xingyu Kang, Jiheong Karnaushenko, Daniil Khademhosseini, Ali Kim, Dae-Hyeong Kim, Il-Doo Kireev, Dmitry Kong, Lingxuan Lee, Chengkuo Lee, Nae-Eung Lee, Pooi See Lee, Tae-Woo Li, Fengyu Li, Jinxing Liang, Cuiyuan Lim, Chwee Teck Lin, Yuanjing Lipomi, Darren J. Liu, Jia Liu, Kai Liu, Nan Liu, Ren Liu, Yuxin Liu, Yuxuan Liu, Zhiyuan Liu, Zhuangjian Loh, Xian Jun Lu, Nanshu Lv, Zhisheng Magdassi, Shlomo Malliaras, George G. Matsuhisa, Naoji Nathan, Arokia Niu, Simiao Pan, Jieming Pang, Changhyun Pei, Qibing Peng, Huisheng Qi, Dianpeng Ren, Huaying Rogers, John A. Rowe, Aaron Schmidt, Oliver G. Sekitani, Tsuyoshi Seo, Dae-Gyo Shen, Guozhen Sheng, Xing Shi, Qiongfeng Someya, Takao Song, Yanlin Stavrinidou, Eleni Su, Meng Sun, Xuemei Takei, Kuniharu Tao, Xiao-Ming Tee, Benjamin C. K. Thean, Aaron Voon-Yew Trung, Tran Quang Wan, Changjin Wang, Huiliang Wang, Joseph Wang, Ming Wang, Sihong Wang, Ting Wang, Zhong Lin Weiss, Paul S. Wen, Hanqi Xu, Sheng Xu, Tailin Yan, Hongping Yan, Xuzhou Yang, Hui Yang, Le Yang, Shuaijian Yin, Lan Yu, Cunjiang Yu, Guihua Yu, Jing Yu, Shu-Hong Yu, Xinge Zamburg, Evgeny Zhang, Haixia Zhang, Xiangyu Zhang, Xiaosheng Zhang, Xueji Zhang, Yihui Zhang, Yu Zhao, Siyuan Zhao, Xuanhe Zheng, Yuanjin Zheng, Yu-Qing Zheng, Zijian Zhou, Tao Zhu, Bowen Zhu, Ming Zhu, Rong Zhu, Yangzhi Zhu, Yong Zou, Guijin Chen, Xiaodong 08-03 Innovis Singapore 138634 Republic of Singapore Innovative Centre for Flexible Devices (iFLEX) School of Materials Science and Engineering Nanyang Technological University Singapore 639798 Singapore Department of Biomedical Engineering University of Houston Houston Texas 77024 United States School of Electrical and Electronic Engineering Yonsei University Seoul 03722 Republic of Korea Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 United States Microelectronics Research Center The University of Texas at Austin Austin Texas 78758 United States Department of Chemistry and Biochemistry California NanoSystems Institute and Department of Psychiatry and Biobehavioral Sciences Semel Institute for Neuroscience and Human Behavior and Hatos Center for Neuropharmacology University of California Los Angeles Los Angeles California 90095 United States Colloid Chemistry Department Max Planck Institute of Colloids and Interfaces 14476 Potsdam Germany Department of Chemical Engineering Stanford University Stanford California 94305 United States Laboratory of Organic Electronics Department of Science and Technology Campus Norrköping Linköping University 83 Linköping Sweden Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg Wood Science Center (WWSC) SE-100 44 Stockholm Sweden Department of Materials Science and Engineering Stanford University Stanford California 94301 United States Department of Biomedical Engineering and Department of Materials Science and Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States Department of Bioengineering University of California Los Angeles Los Angeles California 90095 United States School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore 637457 Singapore Nanobionics Group Department of Chemical and Biological Engineering Monash University Clayton Australia 3800 Monash

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative

关键词： soft materials mechanics engineering flexible electronics conformable sensors bioelectronics human-machine interfaces body area sensor networks technology translation sustainable electronics

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Room-temperature continuous-wave operation of organometal halide perovskite lasers

arXiv

引用

arXiv 2018年

作者： Li, Zhitong Moon, Jiyoung Gharajeh, Abouzar Haroldson, Ross Hawkins, Roberta Hu, Walter Zakhidov, Anvar Gu, Qing Department of Electrical and Computer Engineering Department of Material Science and Engineering Department of Physics University of Texas at Dallas RichardsonTX75080 United States ASIC and System State-key Lab Institute of Microelectronics Fudan University Shanghai200433 China Department of Nanophotonics and Metamaterials ITMO University St. Petersburg Moscow Russia

Solution-processed organic-inorganic lead halide perovskites have recently emerged as promising gain media for tunable semiconductor lasers. However, optically pumped continuous-wave lasing at room temperature - a prerequisite for a laser diode - has not been realized so far. Here, we report lasing action in a surface emitting distributed feedback methylammonium lead iodide (MAPbI3) perovskite laser on silicon substrate, at room temperature under continuous-wave optical pumping. This outstanding performance is achieved because of the ultra-low lasing threshold of 13 W/cm2, which is enabled by thermal nanoimprint lithography that directly patterns perovskite into a high Q cavity with large mode confinement, while at the same time improves perovskite's emission characteristics. Our results represent a major step toward electrically pumped lasing in organic and thin-film materials, as well as the insertion of perovskite lasers into photonic integrated circuits for applications in optical computing, sensing and on-chip quantum information. Copyright © 2018, The Authors. All rights reserved.

关键词： Perovskite

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A novel integrated ultraviolet photodetector based on standard CMOS process

引用

Chinese Physics B 2015年第3期24卷 418-422页

作者：汪涵金湘亮陈长平田满芳朱柯翰 Faculty of Materials Optoelectronics and PhysicsXiangtan University Hunan Engineering Laboratory for Microelectronics Optoelectronics and System on a Chip Electrical and Computer Engineering Department Boise State University

A novel integrated ultraviolet（UV） photodetector has been proposed, which realizes a high UV selectivity by combining a conventional UV-selective photodiode with an extra infrared（IR） photodiode. The IR photodiode is designed for compensating the photocurrent response of the UV photodiode in the infrared band and is 15 times smaller than the UV one. The integrated photodetector has been fabricated in a 0.35 μm standard CMOS technology. Some critical performance indices of this new structure photodetector, such as spectral responsivity, breakdown voltage, quenching waveform, and transient response, are measured and analyzed. Test results show that the complementary UV–IR photodetector has a maximum spectral responsivity of 0.27 A·W-1 at the wavelength of 400 nm. The device has a high UV selectivity of 3000,which is much higher than that of the single UV photodiode.

关键词： ultraviolet photodetector compensating parasitic photocurrent UV selectivity CMOS process

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Design of high reliability RF-LDMOS by suppressing the parasitic bipolar effect using enhanced p-well and double epitaxy

引用

Journal of Semiconductors 2015年第6期36卷 93-98页

作者：徐向明黄景丰遇寒钱文生周正良韩波王勇王鹏飞张卫 State Key Laboratory of ASIC and System School of Microelectronics Fudan University HuaHong Grace Semiconductor Manufacturing Corporation School of Computer and Information Engineering Fuyang Teachers College

A laterally diffused metal-oxide-semiconductor （LDMOS） device design with an enhanced p-well and double p-epitaxial structure is investigated for device ruggedness improvement while keeping its high device per- formance under high frequency. Based upon the device design, radio-frequency （RF） LDMOS transistors for GSM （global system for mobile communication） application have been fabricated by using 0.35/zm CMOS technolo- gies. Experimental data show that the proposed device achieves a breakdown voltage of 70 V, output power of 180 W. The RF linear gain is over 20 dB and the power added efficiency （PAE） is over 70% with the frequency of 920 MHz. In particular, it can pass the 20 ： 1 voltage standing wave ratio （VSWR） load mismatch biased at drain DC supply voltage of 32 V and output power at 10-dB gain compression point （P10dB）. The device ruggedness has been remarkably improved by using the proposed device structure.

关键词： RF power LDMOS semiconductor device ruggedness reliability

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Point-of-care medical devices and systems interoperability: A mapping of ICE and FHIR

Point-of-care medical devices and systems interoperability: ...

引用

IEEE Conference on Standards for Communications and Networking (CSCN)

作者： Björn Andersen Martin Kasparick Hannes Ulrich Stefan Schlichting Frank Golatowski Dirk Timmermann Josef Ingenerf Institute of Medical Informatics University of Lubeck Lubeck Germany Institute of Applied Microelectronics and Computer Engineering University of Rostock Rostock Germany Universitat zu Lubeck Lubeck Schleswig-Holstein DE Center of Competence System Solutions System Architecture of Dragerwerk AG & Co. KGaA Lubeck Germany

Medical devices at the point-of-care can be interconnected through standardised communication protocols to build an Integrated Clinical Environment (ICE), but in order to interoperate with clinical information systems, different data exchange standards need to be conformed to. The emerging HL7 Fast Healthcare Interoperability Resources (FHIR) framework appeals to developers and clinicians alike and is a promising candidate to modernise this domain. Novel IEEE 11073 standard proposals that specify a service-oriented architecture of networked medical devices are one example for an ICE architecture. They are based on expressing a device's capabilities and state in a machine-readable way in order to be safely accessed and manipulated by other participants in the networked device system. In this work, the domain information and service model of this ICE architecture was mapped to FHIR resources that were constrained and extended to support the modelling of this device architecture. Through the definition of a FHIR profile, the data structures were aligned, effectively allowing for the transformation of medical device observation data from ICE to FHIR representation without the need for any proprietary interface. The implementation of this transformation, e. g. as a gateway, bridges the structural interoperability gap between two contemporary communication architectures for medical devices and clinical information systems and thus lays the foundation for semantic interoperability that can be achieved through the combined use with controlled vocabularies. The consequent availability of device data enables secondary usage such as large-scale data analytics. Future sub-profiles for specific device types further simplify the transformation.

关键词： Standards Interoperability Measurement Ice Service-oriented architecture Data models Biomedical imaging

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