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IEEE Conference on Aerospace

作者： Conor A. Nixon Zachary Yahn Ethan Duncan Ian Neidel Alyssa C. Mills Benoît Seignovert Andrew Larsen Kathryn Gansler Charles Liles Catherine C. Walker Douglas M. Trent John Santerre Planetary Systems Laboratory NASA Goddard Space Flight Center Greenbelt MD Computer Science Department University of Virginia Charlottesville VA School of Information University of California Berkeley Berkeley CA Yale University Timothy Dwight College New Haven CT Geosciences Department Baylor University Waco TX Nantes Université Laboratoire De Planétologie Et Géosciences Nantes France Business Intelligence Division Inntopia Stowe VT Department of Geology University of Maryland College Park MD NASA Langley Research Center Center Operations Directorate Virginia Department of Applied Ocean Physics and Engineering Woods Hole Oceanographic Institution Massachusetts OCIO Information Data & Analytics Services SAIC | East-2 NASA Langley Research Center Virginia

In this paper we present two examples of recent investigations that we have undertaken, applying Machine Learning (ML) neural networks (NN) to image datasets from outer planet missions to achieve feature recognition. Our first investigation was to recognize ice blocks (also known as rafts, plates, polygons) in the chaos regions of fractured ice on Europa. We used a transfer learning approach, adding and training new layers to an industry-standard Mask R-CNN (Region-based Convolutional Neural Network) to recognize labeled blocks in a training dataset. Subsequently, the updated model was tested against a new dataset, achieving 68% precision. In a different application, we applied the Mask R-CNN to recognize clouds on Titan, again through updated training followed by testing against new data, with a precision of 95% over 369 images. We evaluate the relative successes of our techniques and suggest how training and recognition could be further improved. The new approaches we have used for planetary datasets can further be applied to similar recognition tasks on other planets, including Earth. For imagery of outer planets in particular, the technique holds the possibility of greatly reducing the volume of returned data, via onboard identification of the most interesting image subsets, or by returning only differential data (images where changes have occurred) greatly enhancing the information content of the final data stream.

关键词： Training Earth Image recognition Transfer learning Streaming media Feature extraction Ice

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Emerging contaminants:A One Health perspective

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The Innovation 2024年第4期5卷 140-170,139页

作者： Fang Wang Leilei Xiang Kelvin Sze-Yin Leung Martin Elsner Ying Zhang Yuming Guo Bo Pan Hongwen Sun Taicheng An Guangguo Ying Bryan WBrooks Deyi Hou Damian EHelbling Jianqiang Sun Hao Qiu Timothy MVogel Wei Zhang Yanzheng Gao Myrna JSimpson Yi Luo Scott XChang Guanyong Su Bryan MWong Tzung-May Fu Dong Zhu Karl JJobst Chengjun Ge Frederic Coulon Jean Damascene Harindintwali Xiankui Zeng Haijun Wang Yuhao Fu Zhong Wei Rainer Lohmann Changer Chen Yang Song Concepcion Sanchez-Cid Yu Wang Ali El-Naggar Yiming Yao Yanran Huang Japhet Cheuk-Fung Law Chenggang Gu Huizhong Shen Yanpeng Gao Chao Qin Hao Li Tong Zhang Natàlia Corcoll Min Liu Daniel SAlessi Hui Li Kristian KBrandt Yolanda Pico Cheng Gu Jianhua Guo Jianqiang Su Philippe Corvini Mao Ye Teresa Rocha-Santos Huan He Yi Yang Meiping Tong Weina Zhang Fidèle Suanon Ferdi Brahushi Zhenyu Wang Syed AHashsham Marko Virta Qingbin Yuan Gaofei Jiang Louis A.Tremblay Qingwei Bu Jichun Wu Willie Peijnenburg Edward Topp Xinde Cao Xin Jiang Minghui Zheng Taolin Zhang Yongming Luo Lizhong Zhu Xiangdong Li DamiàBarceló Jianmin Chen Baoshan Xing Wulf Amelung Zongwei Cai Ravi Naidu Qirong Shen Janusz Pawliszyn Yong-guan Zhu Andreas Schaeffer Matthias C.Rillig Fengchang Wu Gang Yu James M.Tiedje State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008China University of Chinese Academy of Sciences Beijing 100049China Department of Chemistry Hong Kong Baptist UniversityHong KongChina HKBU Institute of Research and Continuing Education Shenzhen Virtual University ParkShenzhenChina Technical University of Munich TUM School of Natural SciencesInstitute of Hydrochemistry85748 GarchingGermany School of Resources&Environment Northeast Agricultural UniversityHarbin 150030China Climate Air Quality Research UnitSchool of Public Health and Preventive MedicineMonash UniversityMelbourneVICAustralia Faculty of Environmental Science&Engineering Kunming University of Science&TechnologyKunming 650500China Ministry of Education Key Laboratory of Pollution Processes and Environmental Criteria College of Environmental Science and EngineeringNankai UniversityTianjin 300350China Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control School of Environmental Science and EngineeringInstitute of Environmental Health and Pollution ControlGuangdong University of TechnologyGuangzhou 510006China Ministry of Education Key Laboratory of Environmental Theoretical Chemistry South China Normal UniversityGuangzhouGuangdong 510006China Department of Environmental Science Baylor UniversityWacoTXUSA Center for Reservoir and Aquatic Systems Research(CRASR) Baylor UniversityWacoTXUSA School of Environment Tsinghua UniversityBeijing 100084China School of Civil and Environmental Engineering Cornell UniversityIthacaNY 14853USA Key Laboratory of Microbial Technology for Industrial Pollution Control of Zhejiang Province Zhejiang University of TechnologyHangzhou 310014China School of Environmental Science and Engineering Shanghai Jiao Tong UniversityShanghai 200240China Laboratoire d’Ecologie Microbienne Universite Claude Bernard Lyon 1UMR CNRS 5557UMR INRAE 1418VetAgro Sup69622 VilleurbanneFrance Department of Pla

Environmental pollution is escalating due to rapid global development that often prioritizes human needs over planetary *** global efforts to mitigate legacy pollutants,the continuous introduction of new substances remains a major threat to both people and the *** response,global initiatives are focusing on risk assessment and regulation of emerging contaminants,as demonstrated by the ongoing efforts to establish the UN’s Intergovernmental science-Policy Panel on Chemicals,Waste,and Pollution *** review identifies the sources and impacts of emerging contaminants on planetary health,emphasizing the importance of adopting a One Health *** for monitoring and addressing these pollutants are discussed,underscoring the need for robust and socially equitable environmental policies at both regional and international *** actions are needed to transition toward sustainable pollution management practices to safeguard our planet for future generations.

关键词： pollution planet contaminants

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Multimodal Whole Slide Foundation Model for Pathology

arXiv

引用

arXiv 2024年

作者： Ding, Tong Wagner, Sophia J. Song, Andrew H. Chen, Richard J. Lu, Ming Y. Zhang, Andrew Vaidya, Anurag J. Jaume, Guillaume Shaban, Muhammad Kim, Ahrong Williamson, Drew F.K. Chen, Bowen Almagro-Perez, Cristina Doucet, Paul Sahai, Sharifa Chen, Chengkuan Komura, Daisuke Kawabe, Akihiro Ishikawa, Shumpei Gerber, Georg Peng, Tingying Le, Long Phi Mahmood, Faisal Department of Pathology Mass General Brigham Harvard Medical School BostonMA United States Data Science Program Dana-Farber Cancer Institute BostonMA United States Cancer Program Broad Institute of Harvard and MIT CambridgeMA United States John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA United States Helmholtz Munich German Research Center for Environment and Health Munich Germany School of Computation Information and Technology Technical University of Munich Munich Germany Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States Harvard-MIT Division of Health Sciences and Technology Massachusetts Institute of Technology CambridgeMA United States Department of Pathology Pusan National University Busan Korea Republic of Department of Pathology and Laboratory Medicine Emory University School of Medicine AtlantaGA United States Harvard Data Science Initiative Harvard University CambridgeMA United States Department of Systems Biology Harvard Medical School BostonMA United States Department of Preventive Medicine Graduate School of Medicine The University of Tokyo Tokyo Japan Division of Pathology National Cancer Center Exploratory Oncology Research & Clinical Trial Center Chiba Japan

The field of computational pathology has been transformed with recent advances in foundation models that encode histopathology region-of-interests (ROIs) into versatile and transferable feature representations via self-supervised learning (SSL). However, translating these advancements to address complex clinical challenges at the patient and slide level remains constrained by limited clinical data in disease-specific cohorts, especially for rare clinical conditions. We propose TITAN, a multimodal whole slide foundation model pretrained using 335,645 WSIs via visual self-supervised learning and vision-language alignment with corresponding pathology reports and 423,122 synthetic captions generated from a multimodal generative AI copilot for pathology. Without any finetuning or requiring clinical labels, TITAN can extract general-purpose slide representations and generate pathology reports that generalize to resource-limited clinical scenarios such as rare disease retrieval and cancer prognosis. We evaluate TITAN on diverse clinical tasks and find that TITAN outperforms both ROI and slide foundation models across machine learning settings such as linear probing, few-shot and zero-shot classification, rare cancer retrieval and cross-modal retrieval, and pathology report generation. The model is publicly accessible at https://***/mahmoodlab/TITAN © 2024, CC BY-NC-ND.

关键词： Self-supervised learning

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Toggling near-field directionality via polarization control of surface waves

arXiv

引用

arXiv 2021年

作者： Zhong, Yuhan Lin, Xiao Jiang, Jing Yang, Yi Liu, Gui-Geng Xue, Haoran Low, Tony Chen, Hongsheng Zhang, Baile Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation ZJU-Hangzhou Global Science and Technology Innovation Center College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China International Joint Innovation Center ZJU-UIUC Institute Zhejiang University Haining314400 China School of Applied Science Beijing Information Science and Technology University Beijing100192 China Research Laboratory of Electronics Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University Singapore637371 Singapore Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States Centre for Disruptive Photonic Technologies Nanyang Technological University Singapore637371 Singapore

Directional excitation of guidance modes is central to many applications ranging from light harvesting, optical information processing to quantum optical technology. Of paramount interest, especially, the active control of near-field directionality provides a new paradigm for the real-time on-chip manipulation of light. Here we find that for a given dipolar source, its near-field directionality can be toggled efficiently via tailoring the polarization of surface waves that are excited, for example, via tuning the chemical potential of graphene in a graphene-metasurface waveguide. This finding enables a feasible scheme for the active near-field directionality. Counterintuitively, we reveal that this scheme can transform a circular electric/magnetic dipole into a Huygens dipole in the near-field coupling. Moreover, for Janus dipoles, this scheme enables us to actively flip their near-field coupling and non-coupling faces. © 2021, CC BY.

关键词： Surface waves

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A map-matching algorithm dealing with sparse cellular fingerprint observations

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Geo-Spatial information science 2019年第2期22卷 89-106,I0002页

作者： Andrea Dalla Torre Paolo Gallo Donatella Gubiani Chris Marshall Angelo Montanari Federico Pittino Andrea Viel Cellular Product Center u-blox Italia SpATriesteItaly Department of Mathematics Computer Science and PhysicsUniversity of UdineUdineItaly Center for Information Technologies and Applied Mathematics University of Nova GoricaNova GoricaSlovenia Cellular Technology u-blox UK LtdReigateUK

The widespread availability of mobile communication makes mobile devices a resource for the collection of data about mobile infrastructures and user *** these contexts,the problem of reconstructing the most likely trajectory of a device on the road network on the basis of the sequence of observed locations(map-matching problem)turns out to be particularly *** contributions have demonstrated that the reconstruction of the trajectory of a device with good accuracy is technically feasible even when only a sparse set of GNSS positions is *** this paper,we face the problem of coping with sparse sequences of cellular *** to GNSS positions,cellular fingerprints provide coarser spatial information,but they work even when a device is missing GNSS positions or is operating in an energy saving *** devise a new map-matching algorithm,that exploits the well-known Hidden Markov Model and Random Forests to successfully deal with noisy and sparse cellular *** performance of the proposed solution has been tested over a medium-sized Italian city urban environment by varying both the sampling of the observations and the density of the fingerprint map as well as by including some GPS positions into the sequence of fingerprint observations.

关键词： Map-matching algorithm trajectory cellular fingerprint Hidden Markov Model

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Evolution of Incommensurate Charge Density Waves Quantified with In Situ TEM

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Microscopy and Microanalysis 2024年第SUPPLEMENT_1期30卷

作者： Shen, Jeremy M Sung, Suk Hyun Agarwal, Nishkarsh Stangel, Alex Hovden, Robert Department of Electrical and Computer Engineering University of Michigan Ann Arbor MI USA Rowland Institute at Harvard Harvard University Cambridge MA USA Department of Material Science and Engineering University of Michigan Ann Arbor MI USA Applied Physics Program University of Michigan Ann Arbor MI USA

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Automation of the decision-making strategy in the water resources management system

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AIP Conference Proceedings 2024年第1期3021卷

作者： Inna I. Pivovarova Alexander L. Zolkin Adam S. Saparbiev Department of Applied Mathematics and Computer Science St. Petersburg University of the State Fire Service of the Ministry of Emergency Situations of Russia 149 Moskovsky Prosp. Saint Petersburg 196105 Russia Computer and Information Sciences Department Povolzhskiy State University of Telecommunications and Informatics Samara 443010 Russia Institute of mathematics physics and information technology Kadyrov Chechen State University Grozny 364024 Russia

The article discusses various approaches to the decision-making methodology to reduce hydrological and economic risks in the field of water resources management. The possibility of creating a fully automated integrated system is considered, the essence of which is the primary processing and analysis of the initial data, modeling possible scenarios, determining possible solutions for each of them, compiling primary clusters of a matrix of possible solutions, methodically combining clusters corresponding to the same decisions and the final assessment of the financial component. An example of GIS modeling for spatial analysis of heterogeneous incoming information is given. The effectiveness of GIS is shown in conditions of difficult decision-making with high uncertainty of hydrometeorological, climatic, socio-economic and other factors affecting the degree of risk of dangerous hydrological phenomena. The practical significance of an automatic system is substantiated, which solves both the direct problem of decision-making based on hydrometeorological forecasts and the reverse problem of optimizing forecasting systems based on an analysis of the potential economic efficiency of issued forecasts.

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Investigating the dirac operator evaluation with FPGAs

Supercomputing Frontiers and Innovations

引用

Supercomputing Frontiers and Innovations 2019年第2期6卷 56-63页

作者： Korcyl, Grzegorz Korcyl, Piotr Department of Information Technologies Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University Kraków Poland Institut für Theoretische Physik Universität Regensburg Regensburg Germany M. Smoluchowski Institute of Physics Jagiellonian University Kraków Poland

In recent years, computational capacity of single Field programmable Gate Array (FPGA) devices as well as their versatility have increased significantly. Adding to that fact, the High Level Synthesis frameworks allowing to program such processors in a high-level language like C++, makes modern FPGA devices a serious candidate as building blocks of a general-purpose High Performance Computing solution. In this contribution we describe benchmarks which we performed using a kernel from the Lattice QCD code, a highly compute-demanding HPC academic code for elementary particle simulations on the newest device from Xilinx, the U250 accelerator card. We describe the architecture of our solution and benchmark its performance on a single FPGA device running in two modes: using either external or embedded memory. We discuss both approaches in detail and provide assessment for the necessary memory throughput and the minimal amount of resources needed to deliver optimal performance depending on the available hardware. Our considerations can be used as guidelines for estimating the performance of some larger, manynode systems. © The Authors 2019.

关键词： High level synthesis

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Modelling smart energy consumption with hybrid demand management in off-grid electrical system considering techno-economic indices

Science and Technology for Energy Transition (STET)

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science and Technology for Energy Transition (STET) 2024年第1期79卷

作者： Rui-Ming, Fang Liao, Qiangqiang Askar, Shavan Pallathadka, Harikumar Sapaev, I.B. Baldaniya, Lalji Chahar, Mamata Saini, Suman Kapila, Ish Jewahery, Hassan Farhan, Mohsen Aued Mohmmedi, M. Information Systems Engineering Department Erbil Technical Engineering College Erbil Polytechnic University Erbil Iraq Manipur International University Manipur Imphal India Department Physics and Chemistry Tashkent Institute of Irrigation and Agricultural Mechanization Engineers Institute National Research University Tashkent Uzbekistan Scientific Researcher University of Tashkent for Applied Sciences Str. Gavhar 1 Tashkent100149 Uzbekistan Scientific Researcher Western Caspian University Baku Azerbaijan Marwadi University Research Centre Department of Pharmacy Faculty of Health Science Marwadi University Gujarat Rajkot360003 India Deparment of Chemistry NIMS Institute of Engineering & Technology NIMS University Rajasthan Jaipur India Department of Applied Sciences Chandigarh Engineering College Chandigarh Group of Colleges Mohali Punjab Jhanjeri140307 India Centre for Research Imapct & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India Department of Computer Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Computer Techniques Engineering College of Technical Engineering The Islamic University of Al Diwaniyah Al Diwaniyah Iraq Department of Computer Techniques Engineering College of Technical Engineering The Islamic University of Babylon Babylon Iraq Department of Management Al-Nisour University College Nisour Seq. Karkh Baghdad Iraq Department of Electrical Engineering Islamic Azad University Branch of Central Tehran Tehran Iran

This study proposes day-ahead power scheduling for electrical systems in off-grid mode, emphasizing consumer involvement. Bi-Demand Side Management (DSM) approaches like strategic conversion and demand shifting are proposed for consumer involvement. Multiple objectives are modelled to voltage profile improvement and reduce the operation energy cost. The non-dominated solutions of the voltage of buses and operation energy cost are generated by enhanced epsilon-constraint technique, simultaneously. The General Algebraic Modeling System (GAMS) software is proposed for solving optimization problems. A combination of decision-making methods like weight sum and fuzzy procedures are implemented for finding optimal solution non-dominated solutions. The proposed method's effectiveness is confirmed through numerical simulations carried out on several case studies that utilize the 33-bus electrical system. The findings illustrate the substantial effectiveness of demand-side participation in improving power dispatch and the optimal rate of multiple objectives. By using DSM, operation cost is reduced by 21.58% and the voltage index is improved by 13.36% than the lack of implementing DSM. © The Author(s), published by EDP sciences, 2024.

关键词： Demand response

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CubeSat single-photon detector module for investigating in-orbit laser annealing to heal radiation damage

arXiv

引用

arXiv 2024年

作者： Sultana, Nigar Krynski, Joanna Lim, Jin Gyu Floyd, John Lembeck, Michael Makarov, Vadim Kwiat, Paul Jennewein, Thomas Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Physics and Astronomy University of Waterloo WaterlooONN2L 3G1 Canada University of Illinois Urbana-Champaign ChampaignIL United States Vigo Quantum Communication Center University of Vigo Vigo Spain Quantum Information Science Program Canadian Institute for Advanced Research TorontoONM5G 1Z8 Canada

Single-photon avalanche photodiodes (SPADs) based on silicon are widely considered for quantum satellite communications but suffer from an increasing dark count rate (DCR) due to displacement damage in their active areas induced by proton radiation. When the DCR of SPADs exceeds a certain threshold, they become unusable for quantum communication protocols. Previous laboratory experiments have demonstrated that laser annealing of SPADs’ active area with about 1 W optical power can significantly reduce radiation-induced DCR of synthetically irradiated SPADs. To assess the feasibility of in-orbit laser annealing on constantly irradiated SPADs in low-Earth orbit, we developed a module with a CubeSat form factor capable of both laser and thermal annealing of four silicon SPADs. Here we report the design and ground testing of this module, investigating laser annealing in a simulated space environment. Our results pave the way for an in-orbit trial that may prove this technology useful for future satellite missions with quantum receivers on board. Copyright © 2024, The Authors. All rights reserved.

关键词： Radiation damage

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