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Annual Conference of Industrial Electronics Society

作者： Gholamreza Davarpanah Sajjad Mohammadi Department of Electrical Engineering Amirkabir University of Technology Tehran Iran Department of Electrical Engineering and Computer Science MIT Cambridge USA

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

A new three-phase hybrid-excited multi-tooth switched reluctance motor with embedded permanent magnets is proposed, capable of achieving higher torque density for transportation electrification applications. Operating principles and design considerations are discussed. A magnetic equivalent circuit is developed. Finite element method is employed in the field analysis. The advantages of the proposed topology over existing designs for switched reluctance motors and flux switching motors are presented. Finally, the optimized design is prototyped to experimentally confirm the design and simulation results.

关键词： Magnetic flux Torque Transportation Switches Switched reluctance motors Electrification Motors Permanent magnets Finite element analysis Saturation magnetization

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Topology Optimization in Three-Phase C-Core SRMs

Topology Optimization in Three-Phase C-Core SRMs

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Annual Conference of Industrial Electronics Society

作者： Gholamreza Davarpanah Sajjad Mohammadi James L. Kirtley Department of Electrical Engineering Amirkabir University of Technology Tehran Iran Department of Electrical Engineering and Computer Science MIT Cambridge USA

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

This paper investigates the optimized combination of rotor and stator teeth in a three-phase switched reluctance motor featuring a connected C-core topology to attain a larger winding area and, thus, a higher electrical loading capability, leading to a higher torque density. The general formulation is discussed. Additionally, the shorter flux path within the design leads to a reduced core loss. The finite element method is employed in the design and field analysis. A comparison with a conventional motor shows the superiority of the proposed configuration. The optimized design is prototyped and tested. Both static and dynamic torques are extracted. A good correlation between simulation and experimental results is observed.

关键词： Stator cores Torque Loading Windings Rotors Stator windings Switched reluctance motors Motors Topology Finite element analysis

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Nonparametric MLE for Gaussian Location Mixtures: Certified Computation and Generic Behavior

arXiv

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arXiv 2025年

作者： Polyanskiy, Yury Sellke, Mark Department of Electrical Engineering and Computer Science MIT. United States Department of Statistics Harvard University United States

We study the nonparametric maximum likelihood estimator πb for Gaussian location mixtures in one dimension. It has been known since [Lin83a] that given an n-point dataset, this estimator always returns a mixture with at most n components, and more recently [PW20] gave a sharp O(log n) bound for subgaussian data. In this work we study computational aspects of πb. We provide an algorithm which for small enough Ε > 0 computes an Ε-approximation of πb in Wasserstein distance in time K +Cnk2 log log(1/Ε). Here K is data-dependent but independent of Ε, while C is an absolute constant and k = |supp(πb)| ≤ n is the number of atoms in πb. We also certifiably compute the exact value of |supp(πb)| in finite time. These guarantees hold almost surely whenever the dataset (x1, . . ., xn) ∈ [−cn1/4, cn1/4] consists of independent points from a probability distribution with a density (relative to Lebesgue measure). We also show the distribution of πb conditioned to be k-atomic admits a density on the associated 2k − 1 dimensional parameter space for all k ≤ √n/3, and almost sure locally linear convergence of the EM algorithm. One key tool is a classical Fourier analytic estimate for non-degenerate curves. Copyright © 2025, The Authors. All rights reserved.

关键词： Maximum likelihood estimation

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ProHealth – Improvised E-Health Care System

ProHealth – Improvised E-Health Care System

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Contemporary Computing and Communications (InC4), IEEE International Conference on

作者： Rajani Sajjan Tushar Chaturvedi Dhanraj Bhanusghare Yash Bansal Department of Computer Science and Engineering MIT ADT University Pune India

The importance of health care is immense in society during the COVID-19 pandemic as well as the post-pandemic situation. The Indian health sector has also made a significant improvement in the healthcare system over the years. This paper presents the development of an application ‘ProHealth,’ for the citizens and doctors of India where they can store their medical data and access it anytime. In the ProHealth (Improvised E-Health Care System-IEHCS), users can register as patients to store their medical data in the database and registered doctors can give advice and prescription when requested for an appointment. The proposed application also provides a virtual E-Health card which has a unique user id and QR code for one-tab access. It concatenates sectors such as health, government, pharmacy, laboratory, and health insurance and makes it transparent between the user and respective sector. The application is going to be developed using Java and the platform will be Android. The database will be stored on google firebase and private cloud storage. It provides an efficient way of storing information electronically, a faster communication mechanism between patients, doctors, and other sectors, and ensures better security for the users.

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Robust Model Invalidation for Chemical Reaction Networks Using Generalized Moments

Robust Model Invalidation for Chemical Reaction Networks Usi...

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IEEE Conference on Decision and Control

作者： Theodore W. Grunberg Domitilla Del Vecchio Department of Electrical Engineering and Computer Science MIT Cambridge MA USA Department of Mechanical Engineering MIT Cambridge MA USA

Many biomolecular systems can be described by chemical reaction networks, however, there may be several candidate networks based on the known biology for a particular system. Determining which chemical reaction network models are inconsistent with observed data can be done via model invalidation. In this work, we formulate and solve a robust version of the model invalidation problem for the case where only measurements from the stationary distribution are available. This problem corresponds to determining if an observed distribution could have been generated by the given chemical reaction network for some value of the parameters, plus a perturbation of bounded size with respect to total variation distance. The main technical tool we introduce to solve the problem is a set of generalized moments that make the problem amenable to an algorithmic solution.

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A Universal Maximum Likelihood GRAND Decoder in 40nm CMOS 14

A Universal Maximum Likelihood GRAND Decoder in 40nm CMOS

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14th International Conference on COMmunication Systems and NETworkS, COMSNETS 2022

作者： Riaz, Arslan Medard, Muriel Duffy, Ken R. Yazicigil, Rabia Tugce Boston University Department of Electrical and Computer Engineering BostonMA United States MIT Department of Electrical Engineering and Computer Science CambridgeMA United States Maynooth University Hamilton Institute Ireland

ISBN: (纸本)9781665421041

As optimally accurate Maximum-likelihood (ML) decoding is NP-complete in code-length, all existing decoders are code-specific and so restricted in code-rate and code-length. Guessing Random Additive Noise Decoding (GRAND) is a recently introduced theoretically universal decoder suitable for all moderate redundancy codes, as required for ultra-reliable low-latency communication by the 5G New Radio Standard. Here we demonstrate the first-integrated universal GRAND chip in 40nm CMOS technology. It efficiently decodes all binary linear codes of any rate from 0.66 to 1 with code length up to 128 bits. For a bit-flip probability of 10-5, GRAND chip measurements show that it achieves 1 μs latency at 68 MHz. Dynamic clock gating leveraging noise statistics reduces the average power dissipation to 3.75 mW at 1.1 V consuming 30.6 pJ/decoded bit of energy with a throughput of 122.6 Mb/s. The chip allows seamless swapping between codebooks with no downtime, enabling use by multiple applications simultaneously. © 2022 IEEE.

关键词： Additive noise

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Proficient Detection of Flash Attacks Using a Predictive Strategy 6th

Proficient Detection of Flash Attacks Using a Predictive Str...

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6th International Conference on Emerging Research in Computing, Information, Communication and Applications, ERCICA 2020

作者： Om Kumar, C.U. Sathia Bhama, Ponsy R. K. Department of Computer Science & Engineering SRM Easwari Engineering College Chennai600 044 India Associate Professor Department of Computer Technology MIT Campus-Anna University Chennai600 044 India

ISBN: (纸本)9789811613371

The availability of service through cloud computing upon the emergence of IoT and wireless networking has exposed the security of information to an even greater risk of abuse. These security threats are caused by cyber criminals through Malware, Cracker, Insider and Zombie. Among the strategies attacking the network DoS or DDoS is disastrous as its objective is to paralyse the complete network system. The bursty or volatile nature of traffic is indicative of a surge in traffic flow. Such an event also implies the incidence of a DDoS attack. If left unchecked this attack will cause a disruption in service. The study focuses on deriving a statistical model for discriminating malign traffic by devising a predictive model using error optimization technique and Hurst Correlogram analysis for effectively detecting and controlling the spread of bot-induced DDoS attack in a cloud environment. This work proposes ARIMA model that detects DDoS with an accuracy of 92% which is further assessed through MLR with an accuracy of 84%. The Hurst estimation of the univariate lies very close to the Hurst of raw data needs mention and proves the maturity of the prediction strategy. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Malware

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A General Security Approach for Soft-information Decoding against Smart Bursty Jammers

A General Security Approach for Soft-information Decoding ag...

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2022 IEEE GLOBECOM Workshops, GC Wkshps 2022

作者： Ercan, Furkan Galligan, Kevin Duffy, Ken R. Medard, Muriel Starobinski, David Yazicigil, Rabia Tugce Boston University Department of Electrical and Computer Engineering BostonMA United States Hamilton Institute Maynooth University Ireland MIT Department of Electrical Engineering and Computer Science CambridgeMA United States

ISBN: (纸本)9781665459754

Malicious attacks such as jamming can cause significant disruption or complete denial of service (DoS) to wireless communication protocols. Moreover, jamming devices are getting smarter, making them difficult to detect. Forward error correction, which adds redundancy to data, is commonly deployed to protect communications against the deleterious effects of channel noise. Soft-information error correction decoders obtain reliability information from the receiver to inform their decoding, but in the presence of a jammer such information is misleading and results in degraded error correction performance. As decoders assume noise occurs independently to each bit, a bursty jammer will lead to greater degradation in performance than a non-bursty one. Here we establish, however, that such temporal dependencies can aid inferences on which bits have been subjected to jamming, thus enabling counter-measures. In particular, we introduce a pre-decoding processing step that updates likelihood ratio (LLR) reliability information to reflect inferences in the presence of a jammer, enabling improved decoding performance for any soft detection decoder. The proposed method requires no alteration to the decoding algorithm. Simulation results show that the method correctly infers a significant proportion of jamming in any received frame. Results with one particular decoding algorithm, the recently introduced ORBGRAND, show that the proposed method reduces the block-error rate (BLER) by an order of magnitude for a selection of codes, and prevents complete DoS at the receiver. © 2022 IEEE.

关键词： Decoding

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Fast sampling from constrained spaces using the Metropolis-adjusted Mirror Langevin algorithm

arXiv

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arXiv 2023年

作者： Srinivasan, Vishwak Wibisono, Andre Wilson, Ashia Department of Electrical Engineering and Computer Science MIT United States Department of Computer Science Yale University United States

We propose a new method called the Metropolis-adjusted Mirror Langevin algorithm for approximate sampling from distributions whose support is a compact and convex set. This algorithm adds an accept-reject filter to the Markov chain induced by a single step of the Mirror Langevin algorithm (Zhang et al., 2020), which is a basic discretisation of the Mirror Langevin dynamics. Due to the inclusion of this filter, our method is unbiased relative to the target, while known discretisations of the Mirror Langevin dynamics including the Mirror Langevin algorithm have an asymptotic bias. For this algorithm, we also give upper bounds for the number of iterations taken to mix to a constrained distribution whose potential is relatively smooth, convex, and Lipschitz continuous with respect to a self-concordant mirror function. As a consequence of the reversibility of the Markov chain induced by the inclusion of the Metropolis-Hastings filter, we obtain an exponentially better dependence on the error tolerance for approximate constrained sampling. We also present numerical experiments that corroborate our theoretical findings. © 2023, CC BY.

关键词： Mirrors

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Challenges and Opportunities of Machine Learning on Neutron and X-ray Scattering

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Synchrotron Radiation News 2022年第4期35卷 16-20页

作者： Drucker, Nathan C. Liu, Tongtong Chen, Zhantao Okabe, Ryotaro Chotrattanapituk, Abhijatmedhi Nguyen, Thanh Wang, Yao Li, Mingda Quantum Measurement Group MIT Cambridge MA United States School of Engineering and Applied Sciences Harvard University Cambridge MA United States Department of Physics MIT Cambridge MA United States Department of Mechanical Engineering MIT Cambridge MA United States Department of Chemistry MIT Cambridge MA United States Department of Electrical Engineering and Computer Science MIT Cambridge MA United States Department of Nuclear Science and Engineering MIT Cambridge MA United States Department of Physics and Astronomy Clemson University Clemson SC United States

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