检索结果-内蒙古大学图书馆

Experimental Characterization of the Reliability of 3-Terminal Dual-Damascene Copper Interconnect Trees

学校读者我要写书评

暂无评论

MRS Online Proceedings Library 2011年第1期716卷 8131-8136页

作者： Gan, C. L. Thompson, C. V. Pey, K. L. Choi, W. K. Wei, F. Yu, B. Hau-Riege, S. P. Advanced Materials for Micro- and Nano- Systems Programme Singapore-MIT Alliance Singapore Department of Materials Science and Engineering Massachusetts Institute of Technology Cambridge USA National University of Singapore now with School of Electrical & Electronics Engineering Nanyang Technological University Nanyang Avenue Singapore Department of Electrical & Computer Engineering National University of Singapore Singapore Institute of Microelectronics San Jose USA Intel Corp. Hillsborough OR 97124 now with Lawrence Livermore National Laboratory Livermore USA

Electromigration experiments have been carried out on simple Cu dual-damascene interconnect tree structures consisting of straight via-to-via (or contact-to-contact) lines with an extra via in the middle of the line. As with Al-based interconnects, the reliability of a segment in this tree strongly depends on the stress conditions of the connected segment. Beyond this, there are important differences in the results obtained under similar test conditions for Al-based and Cu-based interconnect trees. These differences are thought to be associated with variations in the architectural schemes of the two metallizations. The absence of a conducting electromigrationresistant overlayer in Cu technology, and the possibility of liner rupture at stressed vias lead to significant differences in tree reliabilities in Cu compared to Al.

关键词：

Radiality constraints for resilient reconfiguration of distribution systems: Formulation and application to microgrid formation

学校读者我要写书评

暂无评论

arXiv 2019年

作者： Lei, Shunbo Chen, Chen Song, Yue Hou, Yunhe Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI48109 United States Energy Systems Division Argonne National Laboratory ArgonneIL60439 United States Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong University of Hong Kong Shenzhen Institute of Research and Innovation Shenzhen518027 China

Network reconfiguration is an effective strategy for different purposes of distribution systems (DSs), e.g., resilience enhancement. In particular, DS automation, distributed generation integration and microgrid (MG) technology development, etc., are empowering much more flexible reconfiguration and operation of the system, e.g., DSs or MGs with flexible boundaries. However, the formulation of DS reconfiguration-related optimization problems to include those new flexibilities is non-trivial, especially for the issue of topology, which has to be radial. That is, the existing methods of formulating the radiality constraints can cause under-utilization of DS flexibilities. Thus, in this work, we propose a new method for radiality constraints formulation that fully enables the topological and some other related flexibilities of DSs, so that the reconfiguration-related optimization problems can have extended feasibility and enhanced optimality. Graph-theoretic supports are provided to certify its theoretical validity. As integer variables are involved, we also analyze the issues of tightness and compactness. The proposed radiality constraints are specifically applied to post-disaster MG formation, which is involved in many DS resilience-oriented service restoration and/or infrastructure recovery problems. The resulting new MG formation model, which allows more flexible merge and/or separation of the sub-grids, etc., establishes superiority over the models in the literature. Demonstrative case studies are conducted on two test systems. Copyright © 2019, The Authors. All rights reserved.

关键词： Optimization

Real-Time Simulation for Active and Reactive Power Control of Doubly Fed Induction Generator

学校读者我要写书评

暂无评论

Real-Time Simulation for Active and Reactive Power Control o...

North American Power Symposium

作者： Rabindra Maharjan Sukumar Kamalasadan Power Energy and Intelligent Systems Laboratory (PEISL) Department of Electrical and Computer Engineering University of North Carolina at Charlotte

ISBN: (纸本)9781479912537

In this paper real-time modeling and simulation of complete closed loop control of doubly fed induction generator (DFIG) for wind generation system is presented. Decoupled active power and reactive power control of DFIG is realized using the flux oriented vector control. Inner and outer loop controller at rotor side and the grid side converter is presented for the closed loop control of the DFIG using real-time digital simulator. The simulation is carried on OPAL-RT digital simulator which is based on RT-LAB platform with the models build in Simulink. Further full closed loop models are evaluated in an experimental test bed for the step response of active and reactive power (P and Q) change. The real-time modeling and evaluation shows the capability of fully closed loop control and has greater impact on real-world applications.

关键词： Doubly Fed Induction Generator (DFIG) Vector control Real time simulation

Zeroth-order algorithms for stochastic distributed nonconvex optimization

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Yi, Xinlei Zhang, Shengjun Yang, Tao Johansson, Karl H. Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden Department of Electrical Engineering University of North Texas DentonTX76203 United States State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China

In this paper, we consider a stochastic distributed nonconvex optimization problem with the cost function being distributed over n agents having access only to zeroth-order (ZO) information of the cost. This problem has various machine learning applications. As a solution, we propose two distributed ZO algorithms, in which at each iteration each agent samples the local stochastic ZO oracle at two points with a time-varying smoothing parameter. We show that the proposed algorithms achieve the linear speedup convergence rate O(√p=(nT)) for smooth cost functions under the state-dependent variance assumptions which are more general than the commonly used bounded variance and Lipschitz assumptions, and O(p=(nT)) convergence rate when the global cost function additionally satisfies the Polyak-Lojasiewicz (P-L) condition in addition, where p and T are the dimension of the decision variable and the total number of iterations, respectively. To the best of our knowledge, this is the first linear speedup result for distributed ZO algorithms, which enables systematic processing performance improvements by adding more agents. We also show that the proposed algorithms converge linearly under the relative bounded second moment assumptions and the P-L condition. We demonstrate through numerical experiments the efficiency of our algorithms on generating adversarial examples from deep neural networks in comparison with baseline and recently proposed centralized and distributed ZO algorithms. Copyright © 2021, The Authors. All rights reserved.

关键词： Cost functions

Compressive phase retrieval via reweighted amplitude flow

学校读者我要写书评

暂无评论

arXiv 2017年

作者： Zhang, Liang Wang, Gang Giannakis, Georgios B. Chen, Jie Digital Technology Center Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China School of Automation State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

The problem of reconstructing a sparse signal vector from magnitude-only measurements (a.k.a., compressive phase retrieval), emerges naturally in diverse applications, but it is NP-hard in general. Building on recent advances in nonconvex optimization, this paper puts forth a new algorithm that is termed compressive reweighted amplitude flow and abbreviated as CRAF, for compressive phase retrieval. Specifically, CRAF operates in two stages. The first stage seeks a sparse initial guess via a new spectral procedure. In the second stage, CRAF implements a few hard thresholding based iterations using reweighted gradients. When there are sufficient measurements, CRAF provably recovers the underlying signal vector exactly with high probability under suitable conditions. Moreover, its sample complexity coincides with that of the state-of-the-art procedures. Finally, substantial simulated tests showcase remarkable performance of the new spectral initialization, as well as improved exact recovery relative to competing alternatives. Copyright © 2017, The Authors. All rights reserved.

关键词： Iterative methods

Automated Leukemia Screening and Sub-types Classification Using Deep Learning

学校读者我要写书评

暂无评论

computer systems Science & engineering 2023年第9期46卷 3541-3558页

作者： Chaudhary Hassan Abbas Gondal Muhammad Irfan Sarmad Shafique Muhammad Salman Bashir Mansoor Ahmed Osama M.Alshehri Hassan H.Almasoudi Samar M.Alqhtani Mohammed M.Jalal Malik A.Altayar Khalaf F.Alsharif Department of Computer Science COMSATS University Islamabad44000Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Control Automotive and Robotics LabNational Center of Robotics and Automation(NCRA HEC)MirpurPakistan Mirpur University of Science and Technology(MUST)MirpurPakistan Department of Computer Science Virtual University of PakistanLahore54000Pakistan Department of Clinical Laboratory Sciences College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Medical Laboratory Technology Faculty of Applied Medical SciencesUniversity of TabukTabukSaudi Arabia Department of Clinical Laboratory Sciences College of Applied Medical SciencesTaif UniversityP.O.Box 11099Taif21944Saudi Arabia

Leukemia is a kind of blood cancer that damages the cells in the blood and bone marrow of the human *** produces cancerous blood cells that disturb the human’s immune system and significantly affect bone marrow’s production ability to effectively create different types of blood cells like red blood cells(RBCs)and white blood cells(WBC),and *** can be diagnosed manually by taking a complete blood count test of the patient’s blood,from which medical professionals can investigate the signs of leukemia ***,two other methods,microscopic inspection of blood smears and bone marrow aspiration,are also utilized while examining the patient for ***,all these methods are labor-intensive,slow,inaccurate,and require a lot of human experience and *** authors have proposed automated detection systems for leukemia diagnosis to overcome these *** have deployed digital image processing and machine learning algorithms to classify the cells into normal and blast ***,these systems are more efficient,reliable,and fast than previous manual diagnosing ***,more work is required to classify leukemia-affected cells due to the complex characteristics of blood images and leukemia cells having much intra-class variability and inter-class *** this paper,we have proposed a robust automated system to diagnose leukemia and its *** have classified ALL into its sub-types based on FAB classification,i.e.,L1,L2,and L3 types with better *** have achieved 96.06%accuracy for subtypes classification,which is better when compared with the state-of-the-art methodologies.

关键词： Healthcare cancer detection deep learning convolutional neural network

Extraordinary Quality Factors in Dual-Band Polarization-Insensitive QuasiBound States in the Continuum

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Ghahremani, Maryam Zapata-Rodríguez, Carlos J. Photonics Research Laboratory Center of Excellence on Applied Electromagnetic Systems School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Department of Optics and Optometry and Vision Sciences Faculty of Physics University of Valencia Dr. Moliner 50 Burjassot46100 Spain

In this study, we investigate a novel "dimerized" dielectric metasurface featuring dual-mode resonances governed by symmetry-protected bound states in the continuum (BICs). The metasurface design offers advantages such as insensitivity to incident light polarization and exceptionally high quality factors exceeding 105 for low and moderate structural deviations from the monoatomic array. By introducing mastered perturbations in the metasurface via the Brillouin zone folding method, without reducing symmetry, we explore the behavior of symmetry-protected BIC states and their polarization-independent responses. Through numerical simulations and analysis, we demonstrate the superiority of Q factors for specific BIC-based resonances, leading to precise control over interaction behaviors and light engineering in both near and far fields. Our findings contribute to the understanding of BIC resonance interactions and offer insights into the design of high-performance sensing applications and meta-devices with enhanced functionalities. © 2024, CC BY-NC-ND.

关键词： Incident light

Quantized frank-wolfe: Faster optimization, lower communication, and projection free

学校读者我要写书评

暂无评论

arXiv 2019年

作者： Zhang, Mingrui Chen, Lin Mokhtari, Aryan Hassani, Hamed Karbasi, Amin Department of Statistics and Data Science Yale University New HavenCT06511 United States Yale Institute for Network Science Department of Electrical Engineering Yale University New HavenCT06511 United States Laboratory for Information and Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical and Systems Engineering University of Pennsylvania PhiladelphiaPA19104 United States Department of Electrical Engineering and Computer Science Yale University New HavenCT06511 United States

How can we efficiently mitigate the overhead of gradient communications in distributed optimization? This problem is at the heart of training scalable machine learning models and has been mainly studied in the unconstrained setting. In this paper, we propose Quantized Frank-Wolfe (QFW), the first projection-free and communication-efficient algorithm for solving constrained optimization problems at scale. We consider both convex and non-convex objective functions, expressed as a finite-sum or more generally a stochastic optimization problem, and provide strong theoretical guarantees on the convergence rate of QFW. This is accomplished by proposing novel quantization schemes that efficiently compress gradients while controlling the noise variance introduced during this process. Finally, we empirically validate the efficiency of QFW in terms of communication and the quality of returned solution against natural baselines. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

Effective way to improve the response time of short term bursty TCP traffic

学校读者我要写书评

暂无评论

Effective way to improve the response time of short term bur...

IEEE Conference on Vehicular Technology (VTC)

作者： Yu-Chul Kim Jung-Sung Kwan Min-Kyo In Yong-Jin Kim Dong-Ho Cho Communication and Information Systems Laboratory Department of Electrical Engineering& Computer Science Korea Advanced Institute of Science and Technology Daejeon South Korea Next Generation Intemet Standards Team Electronics and Telecommunications Research Institute ETRI Protowl Engineering Center Daejeon South Korea

In this paper, we propose a new algorithm that aids the recovery of lost packets by generating additional duplicate ACK. It is shown that by adopting this algorithm the response time and throughput of short term burst... 详细信息

关键词： Delay Degradation Telecommunication traffic Information systems computer science Telecommunication standards Bit error rate Wire Filters TCPIP