68 research outputs found
Power Management ICs for Internet of Things, Energy Harvesting and Biomedical Devices
This dissertation focuses on the power management unit (PMU) and integrated circuits (ICs) for the internet of things (IoT), energy harvesting and biomedical devices. Three monolithic power harvesting methods are studied for different challenges of smart nodes of IoT networks. Firstly, we propose that an impedance tuning approach is implemented with a capacitor value modulation to eliminate the quiescent power consumption. Secondly, we develop a hill-climbing MPPT mechanism that reuses and processes the information of the hysteresis controller in the time-domain and is free of power hungry analog circuits. Furthermore, the typical power-performance tradeoff of the hysteresis controller is solved by a self-triggered one-shot mechanism. Thus, the output regulation achieves high-performance and yet low-power operations as low as 12 µW. Thirdly, we introduce a reconfigurable charge pump to provide the hybrid conversion ratios (CRs) as 1⅓× up to 8× for minimizing the charge redistribution loss. The reconfigurable feature also dynamically tunes to maximum power point tracking (MPPT) with the frequency modulation, resulting in a two-dimensional MPPT. Therefore, the voltage conversion efficiency (VCE) and the power conversion efficiency (PCE) are enhanced and flattened across a wide harvesting range as 0.45 to 3 V. In a conclusion, we successfully develop an energy harvesting method for the IoT smart nodes with lower cost, smaller size, higher conversion efficiency, and better applicability.
For the biomedical devices, this dissertation presents a novel cost-effective automatic resonance tracking method with maximum power transfer (MPT) for piezoelectric transducers (PT). The proposed tracking method is based on a band-pass filter (BPF) oscillator, exploiting the PT’s intrinsic resonance point through a sensing bridge. It guarantees automatic resonance tracking and maximum electrical power converted into mechanical motion regardless of process variations and environmental interferences. Thus, the proposed BPF oscillator-based scheme was designed for an ultrasonic vessel sealing and dissecting (UVSD) system. The sealing and dissecting functions were verified experimentally in chicken tissue and glycerin. Furthermore, a combined sensing scheme circuit allows multiple surgical tissue debulking, vessel sealer and dissector (VSD) technologies to operate from the same sensing scheme board. Its advantage is that a single driver controller could be used for both systems simplifying the complexity and design cost. In a conclusion, we successfully develop an ultrasonic scalpel to replace the other electrosurgical counterparts and the conventional scalpels with lower cost and better functionality
Boosting Adversarial Transferability by Achieving Flat Local Maxima
Transfer-based attack adopts the adversarial examples generated on the
surrogate model to attack various models, making it applicable in the physical
world and attracting increasing interest. Recently, various adversarial attacks
have emerged to boost adversarial transferability from different perspectives.
In this work, inspired by the fact that flat local minima are correlated with
good generalization, we assume and empirically validate that adversarial
examples at a flat local region tend to have good transferability by
introducing a penalized gradient norm to the original loss function. Since
directly optimizing the gradient regularization norm is computationally
expensive and intractable for generating adversarial examples, we propose an
approximation optimization method to simplify the gradient update of the
objective function. Specifically, we randomly sample an example and adopt the
first-order gradient to approximate the second-order Hessian matrix, which
makes computing more efficient by interpolating two Jacobian matrices.
Meanwhile, in order to obtain a more stable gradient direction, we randomly
sample multiple examples and average the gradients of these examples to reduce
the variance due to random sampling during the iterative process. Extensive
experimental results on the ImageNet-compatible dataset show that the proposed
method can generate adversarial examples at flat local regions, and
significantly improve the adversarial transferability on either normally
trained models or adversarially trained models than the state-of-the-art
attacks.Comment: 17 pages, 5 figures, 6 table
Improving the Transferability of Adversarial Examples with Arbitrary Style Transfer
Deep neural networks are vulnerable to adversarial examples crafted by
applying human-imperceptible perturbations on clean inputs. Although many
attack methods can achieve high success rates in the white-box setting, they
also exhibit weak transferability in the black-box setting. Recently, various
methods have been proposed to improve adversarial transferability, in which the
input transformation is one of the most effective methods. In this work, we
notice that existing input transformation-based works mainly adopt the
transformed data in the same domain for augmentation. Inspired by domain
generalization, we aim to further improve the transferability using the data
augmented from different domains. Specifically, a style transfer network can
alter the distribution of low-level visual features in an image while
preserving semantic content for humans. Hence, we propose a novel attack method
named Style Transfer Method (STM) that utilizes a proposed arbitrary style
transfer network to transform the images into different domains. To avoid
inconsistent semantic information of stylized images for the classification
network, we fine-tune the style transfer network and mix up the generated
images added by random noise with the original images to maintain semantic
consistency and boost input diversity. Extensive experimental results on the
ImageNet-compatible dataset show that our proposed method can significantly
improve the adversarial transferability on either normally trained models or
adversarially trained models than state-of-the-art input transformation-based
attacks. Code is available at: https://github.com/Zhijin-Ge/STM.Comment: 10 pages, 2 figures, accepted by the 31st ACM International
Conference on Multimedia (MM '23
CFD Applications in Ground Source Heat Pump System
In ground source heat pump (GSHP) system, computational fluid dynamics (CFD) is commonly used to conduct simulation analysis of its operating characteristics. Particularly, ground heat exchanger (GHE) is the most core component of GSHP system, and the heat transfer characteristics of which with soil around will directly affect the efficiency of the entire system. Thus, CFD is always applied to predict the process of heat transfer around GHE and its influence on heat exchange process. In this chapter, a 3-D numerical model considering dynamic surface condition and initial soil temperature distribution is developed to investigate the thermal performance of helix ground heat exchanger (HGHE) on basis of CFD, and the main influencing factor (inlet water temperature) is studied with the established model. In addition, the experimental investigation is carried out to verify the accuracy of the model. The results are of great significance for exploring the application of CFD in GSHP system
Topological Superfluid in one-dimensional Ultracold Atomic System with Spin-Orbit Coupling
We propose a one-dimensional Hamiltonian which supports Majorana
fermions when -wave superfluid appears in the ultracold atomic
system and obtain the phase-separation diagrams both for the
time-reversal-invariant case and time-reversal-symmetry-breaking case. From the
phase-separation diagrams, we find that the single Majorana fermions exist in
the topological superfluid region, and we can reach this region by tuning the
chemical potential and spin-orbit coupling . Importantly, the
spin-orbit coupling has realized in ultracold atoms by the recent experimental
achievement of synthetic gauge field, therefore, our one-dimensional ultra-cold
atomic system described by is a promising platform to find the
mysterious Majorana fermions.Comment: 5 papers, 2 figure
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