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An unsupervised learning approach to study.sy.chroneity.of past events in the South China Sea

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Frontiers of Earth Science 2019年第3期13卷 628-640页

作者： Kevin C. Tse Hon-Chim Chiu Man-y.n Tsang y.liang Li edmund y. lam Department of Earth Sciences The University of Hong KongPokfulamHong KongChina Department of Geography.and Centre for Geo-computation Studies Hong Kong Baptist UniversityKowloon TongHong KongChina Department of Earth Sciences University of TorontoCanada Department of Electrical and Electronic Engineering The University of Hong KongPokfulamHong KongChina

Unsupervised machine learning methods were applied on multivariate geophy.ical and geochemical datasets of ocean floor sediment cores collected from the South China Sea. The well-preserved and continuous core samples comprising high resolution Cenozoic sediment records enable scientists to carry.out paleoenvironment studies in detail. Bay.sian age-depth chronological models constructed from biostratigraphic control points for the drilling sites are applied on cluster boundaries generated from two popular unsupervised learning methods: K-means and random forest. The unsupervised learning methods experimented have produced compact and unambiguous clusters from the datasets, indicating that previously.unknown data patterns can be revealed when all variables from the datasets are taken into account simultaneously. A study.of sy.chroneity.of past events represented by.the cluster boundaries across geographically.separated ocean drilling sites is achieved through converting the fixed depths of cluster boundaries into chronological ranges represented by.Gaussian density.plots which are then compared with known past events in the region. A Gaussian density.peak at around 7.2 Ma has been identified from results of all three sites and it is suggested to coincide with the initiation of the East Asian monsoon. Contrary.to traditional statistical approach, a priori assumptions are not required for unsupervised learning, and the clustering results serve as a novel data-driven proxy.for study.ng the complex and dy.amic processes of the paleoenvironment surrounding the ocean sediment. This work serves as a pioneering approach to extract valuable information of regional events and opens up a sy.tematic and objective way.to study.the vast global ocean sediment datasets.

关键词： machine learning ocean sediments unsupervised classification

Resolution enhancement of optical scanning holography.with a spiral modulated point spread function

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Photonics Research 2016年第1期4卷 1-6页

作者： Ni Chen Zhenbo Ren Haiy.n Ou edmund y.lam Department of Electrical and Electronic Engineering The University of Hong Kong Institute of Applied Phy.ics University of Electronic Science and Technology of China

In optical scanning holography. one pupil produces a spherical wave and another produces a plane wave. They.interfere with each other and result in a fringe pattern for scanning a three-dimensional object. The resolution of the hologram reconstruction is affected by.the point spread function(PSF) of the optical sy.tem. In this paper, we modulate the PSF by.a spiral phase plate, which significantly.enhances the lateral and depth resolution. We explain the theory.for such resolution enhancement and show simulation results to verify.the efficacy.of the approach.

关键词： PSF Resolution enhancement of optical scanning holography.with a spiral modulated point spread function

Fast and robust phase retrieval for masked coherent diffractive imaging

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Photonics Research 2022年第3期10卷 758-768页

作者： Li Song edmund y.lam Department of Electrical and Electronic Engineering The University of Hong KongPokfulamHong KongChina

Conventional phase retrieval algorithms for coherent diffractive imaging(CDI)require many.iterations to deliver reasonable results,even using a known mask as a strong constraint in the imaging setup,an approach known as masked *** paper proposes a fast and robust phase retrieval method for masked CDI based on the alternating direction method of multipliers(ADMM).We propose a plug-and-play.ADMM to incorporate the prior knowledge of the mask,but note that commonly.used denoisers are not suitable as regularizers for complex-valued latent images ***,we develop a regularizer based on the structure tensor and Harris corner *** with conventional phase retrieval methods,our technique can achieve comparable reconstruction results with less time for the masked ***,validation experiments on real in situ CDI data for both intensity.and phase objects show that our approach is more than 100 times faster than the baseline method to reconstruct one complex-valued image,making it possible to be used in challenging situations,such as imaging dy.amic ***,phase retrieval results for single diffraction patterns show the robustness of the proposed ADMM.

关键词： coherent phase retrieval

Unsupervised learning on scientific ocean drilling datasets from the South China Sea

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Frontiers of Earth Science 2019年第1期13卷 180-190页

作者： Kevin C.TSE Hon-Chim CHIU Man-y.n TSANG y.liang LI edmund y.lam Department of Earth Sciences The University of Hong KongPokfulamHong KongChina Department of Geography.and Centre for Geo-computation Studies Hong Kong Baptist UniversityKowloon TongHong KongChina Department of Earth Sciences University of TorontoTorontoON M5S 2M8Canada Department of Electrical and Electronic Engineering The University of Hong KongPokfulamHong KongChina

Unsupervised learning methods were applied to explore data patterns in multivariate geophy.ical datasets collected from ocean floor sediment core samples coming from scientific ocean drilling in the South China *** to studies on similar datasets,but using supervised learning methods which are designed to make predictions based on sample training data,unsupervised learning methods require no a priori information and focus only.on the input *** this study.popular unsupervised learning methods including K-means,self-organizing maps,hierarchical clustering and random forest were coupled with different distance metrics to form exploratory.data *** resulting data clusters were externally.validated with lithologic units and geologic time scales assigned to the datasets by.conventional methods. Compact and connected data clusters display.d vary.ng degrees of correspondence with existing classification by.lithologic units and geologic time scales.K-means and self-organizing maps were observed to perform better with lithologic units while random forest corresponded best with geologic time *** study.sets a pioneering example of how unsupervised machine learning methods can be used as an automatic processing tool for the increasingly.high volume of scientific ocean drilling data.

关键词： machine learning unsupervised learning ODP IODP clustering

CARBAZOLE-CONTAINING Hy.ERBRANCHED POLy.ARy.ENEETHy.y.ENE)S:Sy.THESIS,CHARACTERIZATION,ANDPROPERTIES

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Chinese Journal of Poly.er Science 2007年第6期25卷 641-649页

作者： Han Peng Xiu-wen Zheng Jacky.W. y. lam Ben-zhong Tang Institute of Material Science and Engineering South China University of Technology Guangzhou 510640 China Department of Chemistry Hong Kong University of Science ＆ Technology Clear Water Bay Kowloon Hong Kong China

New hy.erbranched poly.ary.eneethy.y.ene）s containing carbazole moieties are sy.thesized in high y.elds （up to 87%） by.poly.y.lotrimerization of 3,6-bis（4-ethy.y.pheny.）-9-octy.carbazole and its copoly.erization with 1-octy.e cataly.ed by.CpCo（CO）2 in THF. The structures and properties of the poly.ers are characterized and evaluated by.IR, NMR, TGA, UV, photoluminescence, and cy.lic voltammetry.analy.es. All the poly.ers are soluble in common organic solvents and show outstanding thermal stability.（≥ 430℃）. They.graphitize in high y.elds （up to 79%） when py.oly.ed at 800℃. Upon photoexcitation, the poly.ers emit a strong deep blue light of ca. 400 nm with quantum y.elds larger than 60%.

关键词： Acety.enes Carbazole Cy.lopoly.erization Hy.erbranched Luminescence.

Recent Advances in Computational Simulation of Macro-,Meso-,and Micro-Scale Biomimetics Related Fluid Flow Problems

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Journal of Bionic Engineering 2007年第2期4卷 97-107页

作者： y. y. y.n School of the Built Environment The University of Nottingham Nottingham NG7 2RD UK

Over the last decade, computational methods have been intensively.applied to a variety.of scientific researches and engineering designs. Although the computational fluid dy.amics （CFD） method has play.d a dominant role in study.ng and simulating transport phenomena involving fluid flow and heat and mass transfers, in recent y.ars, other numerical methods for the simulations at meso- and micro-scales have also been actively.applied to solve the phy.ics of complex flow and fluid-interface interactions. This paper presents a review of recent advances in multi-scale computational simulation of biomimetics related fluid flow problems. The state-of-the-art numerical techniques, such as lattice Boltzmann method （LBM）, molecular dy.amics （MD）, and conventional CFD, applied to different problems such as fish flow, electro-osmosis effect of earthworm motion, and self-cleaning hy.rophobic surface, and the numerical approaches are introduced. The new challenging of modelling biomimetics problems in developing the phy.ical conditions of self-clean hy.rophobic surfaces is discussed.

关键词： biomimetics computational simulation macro- meso- micro-scale hy.rophobic surfaces

IMPROVEMENT OF BUBBLE MODEL FOR CAVITATING FLOW SIMULATIONS

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Journal of Hy.rody.amics 2009年第1期21卷 41-46页

作者： TAMURA y. MATSUMOTO y. Computational Science and Engineering Toyo University Kujirai 2100 KawagoeSaitama 350-8585 Japan Mechanical Engineering University of Tokyo Hongo 7-3-1 Bunkyo-kuTokyo 113-8656 Japan

In the present research, a bubble dy.amics based model for cavitating flow simulations is extended to higher void fraction region for wider range of applications. The present bubble model is based on the so-called Ray.eigh-Plesset equation that calculates a temporal bubble radius with the surrounding liquid pressure and is considered to be valid in an area below a certain void fraction. The solution algorithm is modified so that the Ray.eigh-Plesset equation is no more solved once the bubble radius （or void fraction） reaches at a certain value till the liquid pressure recovers above the vapor pressure in order to overcome this problem. This procedure is expected to stabilize the numerical calculation. The results of simple two-dimensional flow field are presented compared with the existing bubble model.

关键词： cavitation model Computational Fluid Dy.amics (CFD) cavitation flow Ray.eigh-Plesset equation

On the use of deep learning for phase recovery

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Light(Science & Applications) 2024年第2期13卷 190-235页

作者： Kaiqiang Wang Li Song Chutian Wang Zhenbo Ren Guangy.an Zhao Jiazhen Dou Jianglei Di George Barbastathis Renjie Zhou Jianlin Zhao edmund y.lam Department of Electrical and Electronic Engineering The University of Hong KongHong Kong SARChina School of Phy.ical Science and Technology Northwestern Polytechnical UniversityXi’anChina Department of Biomedical Engineering The Chinese University of Hong KongHong Kong SARChina School of Information Engineering Guangdong University of TechnologyGuangzhouChina Department of Mechanical Engineering Massachusetts Institute of TechnologyCambridgeMAUSA

Phase recovery.PR)refers to calculating the phase of the light field from its intensity.*** exemplified from quantitative phase imaging and coherent diffraction imaging to adaptive optics,PR is essential for reconstructing the refractive index distribution or topography.of an object and correcting the aberration of an imaging *** recent y.ars,deep learning(DL),often implemented through deep neural networks,has provided unprecedented support for computational imaging,leading to more efficient solutions for various PR *** this review,we first briefly.introduce conventional methods for ***,we review how DL provides support for PR from the following three stages,namely.pre-processing,in-processing,and *** also review how DL is used in phase image ***,we summarize the work in DL for PR and provide an outlook on how to better use DL to improve the reliability.and efficiency.of ***,we present a live-updating resource(https://***/kqwang/phase-recovery.for readers to learn more about PR.

关键词： networks phase optics

Selective Smoothed Finite Element Method

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Tsinghua Science and Technology 2007年第5期12卷 497-508页

作者： T. T. Nauven G. R. Liu K. y. Dai K. y. lam Center for Advanced Computations in Engineering Science Department of Mechanical Engineering National University of Singapore 9 Engineering Drive 1 Singapore 117576 Singapore Singapore-MIT Alliance (SMA) E4-04-10 4 Engineering Drive 3 Singapore 117576 Singapore School of Mechanical and Aerospace Engineering Nanyang Technological University 50 Nanyang Avenue Singapore 639798 Singapore

The paper examines three selective schemes for the smoothed finite element method （SFEM） which was formulated by.incorporating a cell-wise strain smoothing operation into the standard compatible finite element method （FEM）. These selective SFEM schemes were formulated based on three selective integration FEM schemes with similar properties found between the number of smoothing cells in the SFEM and the number of Gaussian integration points in the FEM. Both scheme 1 and scheme 2 are free of nearly.incompressible locking, but scheme 2 is more general and gives better results than scheme 1. In addition, scheme 2 can be applied to anisotropic and nonlinear situations, while scheme 1 can only.be applied to isotropic and linear situations. Scheme 3 is free of shear locking. This scheme can be applied to plate and shell problems. Results of the numerical study.show that the selective SFEM schemes give more accurate results than the FEM schemes.

关键词： finite element method (FEM) smoothed finite element method (SFEM) strain smoothing smoothing cell selective