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Ensemble learning of diffractive optical networks

Light(Science & Applications) 2021年第1期10卷 123-135页

作者： md sadman sakib rahman Jingxi Li Deniz Mengu Yair Rivenson Aydogan Ozcan Electrical and Computer Engineering Department University of CaliforniaLos AngelesCA 90095USA Bioengineering Department University of CaliforniaLos AngelesCA 90095USA California NanoSystems Institute(CNSI) University of CaliforniaLos AngelesCA 90095USA

A plethora of research advances have emerged in the fields of optics and photonics that benefit from harnessing the power of machine ***,there has been a revival of interest in optical computing hardware due to its potential advantages for machine learning tasks in terms of parallelization,power efficiency and computation *** deep neural networks(D^(2)NNs)form such an optical computing framework that benefits from deep learning-based design of successive diffractive layers to all-optically process information as the input light diffracts through these passive layers.D^(2)NNs have demonstrated success in various tasks,including object classification,the spectral encoding of information,optical pulse shaping and ***,we substantially improve the inference performance of diffractive optical networks using feature engineering and ensemble *** independently training 1252 D^(2)NNs that were diversely engineered with a variety of passive input filters,we applied a pruning algorithm to select an optimized ensemble of D^(2)NNs that collectively improved the image classification *** this pruning,we numerically demonstrated that ensembles of N=14 and N=30 D^(2)NNs achieve blind testing accuracies of 61.14±0.23%and 62.13±0.05%,respectively,on the classification of GFAR-10 test images,providing an inference improvennent of>16%compared to the average performance of the individual D^(2)NNs within each *** results constitute the highest inference accuracies achieved to date by any diffractive optical neural network design on the same dataset and might provide a significant leap to extend the application space of diffractive optical image classification and machine vision systems.

关键词： networks collective successive

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Universal linear intensity transformations using spatially incoherent diffractive processors

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Light(Science & Applications) 2023年第9期12卷 1830-1856页

作者： md sadman sakib rahman Xilin Yang Jingxi Li Bijie Bai Aydogan Ozcan Electrical and Computer Engineering Department University of CaliforniaLos AngelesCA 90095USA Bioengineering Department University of CaliforniaLos AngelesCA 90095USA California NanoSystems Institute(CNSI) University of CaliforniaLos AngelesCA 90095USA

Under spatially coherent light,a diffractive optical network composed of structured surfaces can be designed to perform any arbitrary complex-valued linear transformation between its input and output fields-of-view(FOVs)if the total number(N)of optimizable phase-only diffractive features is≥~2N_(i)N_(o),where Ni and No refer to the number of useful pixels at the input and the output FOVs,*** we report the design of a spatially incoherent diffractive optical processor that can approximate any arbitrary linear transformation in time-averaged intensity between its input and output *** spatially incoherent monochromatic light,the spatially varying intensity point spread function(H)of a diffractive network,corresponding to a given,arbitrarily-selected linear intensity transformation,can be written as H(m,n;m′,n′)=|h(m,n;m′,n′)|^(2),where h is the spatially coherent point spread function of the same diffractive network,and(m,n)and(m′,n′)define the coordinates of the output and input FOVs,*** numerical simulations and deep learning,supervised through examples of input-output profiles,we demonstrate that a spatially incoherent diffractive network can be trained to all-optically perform any arbitrary linear intensity transformation between its input and output if N≥~2N_(i)N_(o).We also report the design of spatially incoherent diffractive networks for linear processing of intensity information at multiple illumination wavelengths,operating ***,we numerically demonstrate a diffractive network design that performs all-optical classification of handwritten digits under spatially incoherent illumination,achieving a test accuracy of>95%.Spatially incoherent diffractive networks will be broadly useful for designing all-optical visual processors that can work under natural light.

关键词： spatially intensity arbitrary

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Physics and artificial intelligence: illuminating the future of optics and photonics

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Advanced Photonics 2024年第5期6卷 7-12页

作者： md sadman sakib rahman Aydogan Ozcan University of California Electrical and Computer Engineering Department University of California Bioengineering Department University of California California Nano Systems Institute

1 Introduction The artificial intelligence （AI） revolution is upon us,transforming not just our daily lives with smart assistants,personalized recommendations,and autonomous systems but also profoundly altering the landscape of scientific research and knowledge *** revolution is characterized by the integration of AI into every domain of human activity,from healthcare and finance to education and *** transformative effects are also being felt in the world of scientific research,e.g.,in the physical sciences,where AI is not just assisting in data analysis1but is also driving new discoveries2and pushing the boundaries of knowledge and applied *** interplay between AI and physics has reached a point where advancements in one field are catalyzing progress in the other,creating feedback loops of innovations that are reshaping our understanding of the universe and the tools we use to explore it.

关键词： Artificial intelligence Physics Design Evolutionary algorithms Systems modeling Artificial neural networks Quantum photonics Neural networks Algorithm development Education and training

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OAM-based diffractive all-optical classification

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Advanced Photonics 2024年第1期6卷 6-7页

作者： md sadman sakib rahman Aydogan Ozcan University of California Electrical and Computer Engineering DepartmentLos AngelesCaliforniaUnited States University of California Bioengineering DepartmentLos AngelesCaliforniaUnited States University of California California NanoSystems Institute(CNSI)Los AngelesCaliforniaUnited States

Object classification is an important aspect of machine *** practices in object classification entail the digitization of object information followed by the application of digital algorithms such as deep neural *** execution of digital neural networks is power-consuming,and the throughput is *** existing von Neumann digital computing paradigm is also less suited for the implementation of highly parallel neural network architectures.^(1)

关键词： consuming digit neural

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Complex-valued universal linear transformations and image encryption using spatially incoherent diffractive networks

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Advanced Photonics Nexus 2024年第1期3卷 76-85页

作者： Xilin Yang md sadman sakib rahman Bijie Bai Jingxi Li Aydogan Ozcan University of California Los AngelesElectrical and Computer Engineering DepartmentLos AngelesCaliforniaUnited States University of California Los AngelesBioengineering DepartmentLos AngelesCaliforniaUnited States University of California Los AngelesCalifornia NanoSystems Institute(CNSI)Los AngelesCaliforniaUnited States

As an optical processor,a diffractive deep neural network(D2NN)utilizes engineered diffractive surfaces designed through machine learning to perform all-optical information processing,completing its tasks at the speed of light propagation through thin optical *** sufficient degrees of freedom,D2NNs can perform arbitrary complex-valued linear transformations using spatially coherent ***,D2NNs can also perform arbitrary linear intensity transformations with spatially incoherent illumination;however,under spatially incoherent light,these transformations are nonnegative,acting on diffraction-limited optical intensity patterns at the input field of ***,we expand the use of spatially incoherent D2NNs to complex-valued information processing for executing arbitrary complex-valued linear transformations using spatially incoherent *** simulations,we show that as the number of optimized diffractive features increases beyond a threshold dictated by the multiplication of the input and output space-bandwidth products,a spatially incoherent diffractive visual processor can approximate any complex-valued linear transformation and be used for all-optical image encryption using incoherent *** findings are important for the all-optical processing of information under natural light using various forms of diffractive surface-based optical processors.

关键词： optical computing optical networks machine learning diffractive optical networks diffractive neural networks image encryption

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Low Altitude Satellite Constellation for Futuristic Aerial-Ground Communications

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Computer Modeling in Engineering & Sciences 2023年第8期136卷 1053-1089页

作者： Saifur rahman Sabuj Mohammad Saadman Alam Majumder Haider md Akbar Hossain Al-sakib Khan Pathan Department of Electronic Engineering Hanbat National UniversityDaejeon34158South Korea Department of Electrical and Electronic Engineering Brac UniversityDhaka1212Bangladesh School of Business and Digital Technologies Manukau Institute of TechnologyManukau2241New Zealand Department of Computer Science and Engineering United International UniversityDhaka1212Bangladesh

This paper discusses the significance and prospects of low altitude small satellite aerial vehicles to ensure smooth aerial-ground communications for next-generation broadband *** achieve the generic goals of fifthgeneration and beyondwireless networks,the existing aerial network architecture needs to be *** detailed architecture of low altitude aerial networks and the challenges in resource management have been illustrated in this ***,we have studied the coordination between promising communication technologies and low altitude aerial networks to provide robust network *** talk about the techniques that can ensure userfriendly control and monitoring of the low altitude aerial networks to bring forth wireless broadband connectivity to a new *** the end,we highlight the future research directions of aerial-ground communications in terms of access technologies,machine learning,compressed sensing,and quantum communications.

关键词： Aerial-terrestrial network cognitive radio network cooperative communication high altitude platform low altitude platform low earth orbit satellite constellation unmanned aerial vehicle

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Capturing transition and non-transition flows with a new shear stress transport model

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Chinese Journal of Aeronautics 2023年第3期36卷 121-136页

作者： md Mizanur rahman School of Mechanical Engineering Hangzhou Dianzi UniversityHangzhou 310018China

A new Shear Stress Transport(SST)k-ω model is devised to integrate salient features of both the non-transitional SST k-ω model and correlation-based γ-Re_(θ) transition *** exceptionally simplified approach is applied to extend the New SST(NSST)model capabilities toward transition/non-transition ***’s stress-intensity factor R_(b)=|-uv|/k can be parameterized with the wall-distance dependent Reynolds number Re_(y)=√ky/v;however,as the Re_(y)is replaced by a“flow-structure-adaptive”parameter R_(μ)=v_(T)/v,the resulting R_(b)is capable of capturing various transition phenomena *** prospective stress-intensity parameter R_(b)=R_(b)(Re_(y),R_(μ))is incorporated in the constitutive relations for eddy-viscosity v_(T) and production term P_(k).The proposed formulation is intrinsically plausible,having a dramatic impact on the prediction of bypass,separation-induced and natural transitions together with non-transitional *** extra viscous-production term P_(k)^(lim) is added with the k-equation to ensure proper generation of k at the viscous sublayer when computing separation-induced transition over a Low-Reynolds Number(LRN)*** demonstrate that the NSST k-ω model maintains an excellent consistency with both SST k-ω and γ-Re_(θ) models.

关键词： γ-Re_(θ)model Non-transition Stress-intensity parameter SST model Transition

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Sensitivity analysis of the DehumReq model to evaluate the impact of predominant factors on dehumidification requirement of greenhouses in cold regions

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Information Processing in Agriculture 2023年第2期10卷 216-228页

作者： md Sazan rahman Huiqing Guo Department of Mechanical Engineering University of Saskatchewan57 Campus driveSaskatoonSK S7N 5A9Canada Department of Bioresource Engineering McGill UniversityMacdonald Stewart Building21111 Lakeshore RoadSainte-Anne-de-BellevueQC H9X 3V9Canada

In this study,the sensitivity of a novel dehumidification requirement model(DehumReq)is analyzed to evaluate the effect of the predominant factors on the dehumidification needs of the *** hourly dehumidification demand and sensitivity coefficient(SC)are estimated for three different seasons:warm(July),mild(May),and cold(November),by using the local sensitivity analysis *** on SC values,the solar radiation,air exchange,leaf area index(LAI),and indoor setpoints(temperature,relative humidity(RH),and water vapor partial pressure(WVPP))have significant impact on the dehumidifi-cation needs,and the impact varies from season to *** parameters have a higher SC in summer,whereas solar radiation and LAI have a higher SC in mild *** dehumidification load increases 4 times of its base value with increasing solar radiation by 200 W/m^(2),and the highest LAI(10)caused 5 times increment of the *** changing of WVPP from its base value(1.5 kPa)to maximum(2.9 kPa)reduces the load 70%in *** exchange was found to be the most crucial parameter because it is the main dehumidification approach that has a large range and is easily adjustable for any *** air exchange by ventilation or infiltration will reduce the dehumidification load to zero in May and November and minimizes it to only nighttime load in *** the other parameters,higher ambient air RH and indoor air speed will result in higher the dehumidification load;whereas higher inner surface condensation will result in lower dehumidifi-cation *** result of this study will assist in the selection of the most efficient moisture control strategies and techniques for greenhouse humidity control.

关键词： Greenhouse Dehumidification DehumReq model Sensitivity analysis Solar radiation Air exchange

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Test and performance optimization of nozzle inclination angle and swirl combustor in a low-tar biomass gasifier:a biomass power generation system perspective

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Carbon Resources Conversion 2022年第2期5卷 139-149页

作者： md Mashiur rahman Agricultural Engineering Division Regional Agricultural Research StationBangladesh Agricultural Research InstituteJamalpur2000Bangladesh DTU Chemical Engineering Technical University of Denmark(DTU)Frederiksborgvej 399DK 4000 RoskildeDenmark

A nozzle inclination angle and swirl combustor inside the low-tar biomass(LTB)gasifier reactor were tested and optimized to evaluate these effects on tar reduction to design tar-free producer *** tar reduction process is mainly based on the concept of a swirling flow created by the nozzle inclination angle,with the inclination angle of 55◦to the radial line,allowing good mixing between pyrolysis gases and gasifying agents.A separate swirl combustor has created large internal annular and reverses flow zones with the help of swirl flow,resulting in homogenized temperature inside the combustor and providing longer residence time;both have a positive effect on the combustion of mixed gasifying air-pyrolysis gases by the thermal cracking in the partial oxidation *** ratio(RR)and combustion degree of volatiles are the two optimization parameters for evaluating the performance of NIA and swirl *** result observed that outstanding tar reduction occurred in this novel *** 86.5 and 12.8%of tar compounds are broken down in the partial oxidation zone and pyrolysis zone using the novel swirl combustor and NIA,respectively;gas outlet has observed producer gas having tar concentration of less than 1%.The optimization results reveal that a lower recycling ratio(recycle gas/gasifying air)and a higher combustion degree of volatiles perform better in biomass ***,this system generated producer gas with the tar concentration at an extremely low level of 7.4 mg/Nm^(3)for a biomass moisture content of 9%and appeared the lower heating value of 4.6–5.1 MJ/Nm^(3).This lower tar concentration might be directly coupled with an internal combustion engine or a gas turbine for power generation.

关键词： Biomass gasification Downdraft moving bed gasifier Nozzle inclination angle Swirl combustor Swirl flow Tar Reduction

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Behaviour of self-centring shear walls——A state of the art review

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Frontiers of Structural and Civil Engineering 2023年第1期17卷 53-77页

作者： Mehdi JAVADI Reza HASSANLI md Mizanur rahman md Rajibul KARIM UniSA STEM University of South AustraliaAdelaide 5095Australia

The application of unbonded post-tensioning (PT) in structural walls has led to the development of advanced self-centring (rocking) shear wall systems that has significant advantages, including accelerated construction due to the incorporation of prefabricated elements and segmental construction for different materials (e.g., concrete, masonry, and timber), reduced residual drifts, and little damage upon extreme seismic and wind loads. Concrete, masonry, and timber are often used for the construction of unbonded PT structural wall systems. Despite extensive research since the 1980s, there are no well-established design guidelines available on the shear wall configuration with the required energy dissipation system, joint’s locations and acceptance criteria for shear sliding, confinement, seismic performance factors, PT loss, PT force range and residual drifts of shear walls subjected to lateral loads. In this research a comprehensive state-of-the-art literature review was performed on self-centring shear wall system. An extensive study was carried out to collect a database of 100 concrete, masonry, and self-centring shear wall tests from the literature. The established database was then used to review shear walls’ configurations, material, and components to benchmark requirements applicable for design purposes. The behaviour of concrete, masonry and timber shear walls were compared and critically analysed. The general behaviour, force-displacement performance of the walls, ductility, and seismic response factors, were critically reviewed and analysed for different self-centring wall systems to understand the effect of different parameters including configurations of the walls, material used for construction of the wall (concrete, masonry, timber) and axial stress ratio. The outcome of this research can be used to better understand the behaviour of self-centring wall system in order to develop design guidelines for such walls.

关键词： self-centring shear walls rocking walls energy dissipation seismic performance factors PT loss residual drift

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