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Lecture Notes in Networks and Systems 2023年 729 LNNS卷 v-vi页

作者： Vasant, Pandian Weber, Gerhard-Wilhelm Arefin, Mohammad Shamsul Rodriguez-Aguilar, Roman Panchenko, Vladimir Munapo, Elias Thomas, J. Joshua Faculty of Electrical and Electronics Engineering Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Ton Duc Thang University Ho Chi Minh City Viet Nam Department of Computer Science Chittagong University of Engineering and Technology Chittagong Bangladesh Laboratory of Non-traditional Energy Systems Department of Theoretical and Applied Mechanics Federal Scientific Agroengineering Center VIM Russian University of Transport Moscow Russia Department of Computer Science UOW Malaysia KDU Penang University College George Town Malaysia Faculty of Engineering Management Poznań University of Technology Poznan Poland School of Economics and Decision Sciences North West University Mmabatho South Africa Facultad de Ciencias Económicas y Empresariales School of Economic and Business Sciences Universidad Panamericana Mexico City Mexico

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Chinese Journal of Physics 2025年 93卷 649-649页

作者： Javaid Ali Muhammad Rafiq Nauman Ahmed Sultan Alqahtani Ilyas Khan Abha Singh Department of Mathematics GGCT Punjab Higher Education Department Lahore Pakistan Department of Mathematics Faculty of Sciences University of Central Punjab Lahore Pakistan Department of Computer Science and Mathematics Lebanese American University Beirut Lebanon Department of Mathematics and Statistics The University of Lahore Lahore Pakistan College of Engineering Mechanical Engineering Department King Khalid University Abha Saudi Arabia Department of Mathematics Saveetha School of Engineering SIMATS Chennai Tamil Nadu India Department of Mathematics College of Science Al-Zulfi Majmaah University Al-Majmaah 11952 Saudi Arabia Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman Jordan Al-Ayen research center Al-Ayen University Iraq Department of Basic Sciences College of Sciences and Theoretical Studies Dammam-branch Saudi Electronic University Riyadh Saudi Arabia

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Eagle+: A fast incremental approach to automaton and table online updates for cloud services

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Future Generation computer Systems 2018年 80卷 275-285页

作者： Li, Jianxin Peng, Hao Yang, Erica Hu, Chunming Zhong, Shenghai Wang, Lihong School of Computer Science & Engineering Beihang University Beijing China Scientific Computing Department STFC Rutherford Appleton Laboratory Oxfordshire United Kingdom National Computer Network Emergency Response Technical Team/Coordination Center of China Beijing China

Automaton or table-based multi-pattern matching methods have been widely used in cloud services, i.e., virtual Firewall service, virtual IDS service, etc. In cloud, a large scale of patterns in such services are frequently updated causing by users’ joining or quitting and adjustment of security and management policies. Therefore, how to quickly and accurately update the Automaton and Table becomes an important issue. In this paper, we propose Eagle+, an incremental approach for updating the matching Automaton and Table whilst avoiding recalculating the whole patterns after each change. In Eagle+, we attain efficiency by computing only the latest update set of patterns when updating the Automaton and Table. Moreover, Eagle+ achieves accurately local updating based on three atomic operations, adding, updating and deleting, each of which modifies values on classical Aho–Corasick (AC) automaton, Set Backward Oracle Matching (SBOM) automaton and Wu–Manber (WM) table. Compared with existing pattern updating methods, Eagle+ reduces the computation complexity from O(n2) to O(n). The experimental results show that Eagle+ can save nearly 72%–92% of the time consumption in updating automatons and perform 100X faster in WM table. © 2017 Elsevier B.V.

关键词： Web services

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Master equations and quantum trajectories for squeezed wave packets

arXiv

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arXiv 2021年

作者： Gross, Jonathan A. Baragiola, Ben Stace, T.M. Combes, Joshua Center for Quantum Information and Control University of New Mexico AlbuquerqueNM87131-0001 United States Institut Quantique Université de Sherbrooke SherbrookeQCJ1K 2R1 Canada Centre for Quantum Computation & Communication Technology School of Science RMIT University MelbourneVIC3000 Australia ARC Centre for Engineered Quantum System Department of Physics University of Queensland BrisbaneQLD4072 Australia Department of Electrical Computer and Energy Engineering University of Colorado Boulder BoulderCO80309 United States

The interaction between matter and squeezed light has mostly been treated within the approximation that the field correlation time is small. Methods for treating squeezed light with more general correlations currently involve explicitly modeling the systems producing the light. We develop a general purpose input-output theory for a particular form of narrowband squeezed light-a squeezed wave-packet mode-that only cares about the statistics of the squeezed field and the shape of the wave packet. This formalism allows us to derive the input-output relations and the master equation. We also consider detecting the scattered field using photon counting and homodyne measurements which necessitates the derivation of the stochastic master equation. The non Markovian nature of the field manifests itself in the master equation as a coupled hierarchy of equations. We illustrate these with consequences for the decay and resonance fluorescence of two-level atoms in the presence of such fields. Copyright © 2021, The Authors. All rights reserved.

关键词： Wave packets

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FAIR for AI: An interdisciplinary and international community building perspective

arXiv

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arXiv 2022年

作者： Huerta, E.A. Blaiszik, Ben Brinson, L. Catherine Bouchard, Kristofer E. Diaz, Daniel Doglioni, Caterina Duarte, Javier M. Emani, Murali Foster, Ian Fox, Geoffrey Harris, Philip Heinrich, Lukas Jha, Shantenu Katz, Daniel S. Kindratenko, Volodymyr Kirkpatrick, Christine R. Lassila-Perini, Kati Madduri, Ravi K. Neubauer, Mark S. Psomopoulos, Fotis E. Roy, Avik Rübel, Oliver Zhao, Zhizhen Zhu, Ruike Data Science and Learning Division Argonne National Laboratory LemontIL60439 United States Department of Computer Science University of Chicago ChicagoIL60637 United States Globus University of Chicago ChicagoIL60637 United States Department of Mechanical Engineering and Materials Science Duke University DurhamNC27708 United States Scientific Data Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Biological Systems & Engineering Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Helen Wills Neuroscience Institute University of California Berkeley BerkeleyCA94720 United States Department of Physics University of California La Jolla San DiegoCA92093 United States Lund University Department of Physics Box 118 Lund221 00 Sweden School of Physics & Astronomy The University of Manchester ManchesterM13 9PL United Kingdom Leadership Computing Facility Argonne National Laboratory LemontIL60439 United States Biocomplexity Institute Department of Computer Science University of Virginia CharlottesvilleVA22904 United States Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States Technical University Munich Arcisstraße 21 München80333 Germany Computational Science Initiative Brookhaven National Laboratory UptonNY11973 United States Electrical and Computer Engineering Rutgers The State University of New Jersey PiscatawayNJ08854 United States National Center for Supercomputing Applications University of Illinois Urbana-Champaign UrbanaIL61801 United States Department of Computer Science University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Electrical & Computer Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States School of Information Sciences University of Illinois at Urbana-Champaign UrbanaIL61801 United States San Diego Supercomputer Center University of California La Jolla San DiegoCA

A foundational set of findable, accessible, interoperable, and reusable (FAIR) principles were proposed in 2016 as prerequisites for proper data management and stewardship, with the goal of enabling the reusability of scholarly data. The principles were also meant to apply to other digital assets, at a high level, and over time, the FAIR guiding principles have been reinterpreted or extended to include the software, tools, algorithms, and workflows that produce data. FAIR principles are now being adapted in the context of AI models and datasets. Here, we present the perspectives, vision, and experiences of researchers from different countries, disciplines, and backgrounds who are leading the definition and adoption of FAIR principles in their communities of practice, and discuss outcomes that may result from pursuing and incentivizing FAIR AI research. The material for this report builds on the FAIR for AI Workshop held at Argonne National Laboratory on June 7, 2022. Copyright © 2022, The Authors. All rights reserved.

关键词： Information management

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IMPROVING the LAND SURFACE GENERAL DROUGHT INDEX MODEL 21

IMPROVING the LAND SURFACE GENERAL DROUGHT INDEX MODEL

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Joint Meeting of the 21st William T. Pecora Memorial Remote Sensing Symposium, Pecora 2019 and the 38th International Symposium on Remote Sensing of Environment, ISRSE 2019

作者： Ngandam Mfondoum, A.H. Gbetkom, P.G. Cooper, R. Hakdaoui, S. Mansour Badamassi, M.B. StatsN'Maps Private Consulting Firm DallasTX75287 United States Department of Geography University of Yaoundé i Yaoundé Cameroon Department of Geography University of Aix-Marseille Marseille France Erik Jonsson School of Engineering and Computer Science University of Texas in Dallas DallasTX75080 United States Earth Observation Department Geo-Biodiversity and Natural Patrimony Laboratory Geophysics Natural Patrimony and Green Chemistry Research Center Scientific Institute Mohamed v University Rabat Morocco Laboratory of Botanic Mycology and Environment Mohammed v University Rabat Morocco

Drought affects all human activities and ecosystems. Nearly 40 percent of the world's population inhabit Drylands, and they depend on agriculture for their food, security and livelihoods. Among the remote sensing indices developed, the Land Surface General Drought Index (LSGDI) was recently proposed. This paper proposes an improved model of LSGDI to face the issue of drought in semi-arid and arid regions. The experiment was conducted for the Maga's floodplain, in North-Cameroon. The method uses satellite images of Landsat in 1987, 2003 and 2018, for January and March or April, corresponding to the middle and the end of the dry season. A Vegetation Moisture Index (VMI) and a Normalized Difference Soil Drought Index (NDSoDI) are both developed. On an orthogonal plan, their projections give a drought line that expresses the improved LSGDI (LSGDI2) as the root sum square of the NDSoDI and the VMI. The LSGDI2 results are ranged in [0.09-0.14] interval, which is used to define the threshold and ease the qualifiers for drought classes. The visual patterns easily match the sandy areas of the original Landsat images with the highest values, while the vegetation and water areas match the lowest values. Compared with the LSGDI and Second Modified Perpendicular drought Index (MPDI1), the new index reflectance values are higher. Finally, although LSGDI2 curve's evolution follows the NDSoDI one at 94%, the new spectral index values depends on the both components, helping to map highest values of drought and moisture in Maga's floodplain, for a sustainable rice culture expansion. © 2020 Authors.

关键词： Landsat

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Extracting built-up features in complex biophysical environments by using a landsat bands ratio

Extracting built-up features in complex biophysical environm...

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American Society for Photogrammetry and Remote Sensing, ASPRS 2020 Annual Conference

作者： Mfondoum, Alfred Homère Ngandam Gbetkom, Paul Gérard Cooper, Ryan Hakdaoui, Sofia Badamassi, Mamane Barkawi Mansour StatsN'Maps Private Consulting Firm DallasTX United States Department of Geography University of Yaoundé I Yaoundé Cameroon Department of Geography University of Aix-Marseille Marseille France Erik Jonsson School of Engineering and Computer Science University of Texas in Dallas DallasTX75080 United States Earth Observation Department Geo-Biodiversity and Natural Patrimony Laboratory Geophysics Natural Patrimony and Green Chemistry Research Center Scientific Institute Mohamed V University Rabat Morocco Laboratory of Botanic Mycology and Environment Mohammed V University Rabat Morocco

This paper addresses the remote sensing challenging field of urban mixed pixels on a medium spatial resolution satellite data. The tentatively named Normalized Difference Built-up and Surroundings Unmixing Index (NDBSUI) is proposed by using Landsat-8 Operational Land Imager (OLI) bands. It uses the Shortwave Infrared 2 (SWIR2) as the main wavelength, the SWIR1 with the red wavelengths, for the built-up extraction. A ratio is computed based on the normalization process and the application is made on six cities with different urban and environmental characteristics. The built-up of the experimental site of Yaoundé is extracted with an overall accuracy of 95.51% and a kappa coefficient of 0.90. The NDBSUI is validated over five other sites, chosen according to Cameroon's bioclimatic zoning. The results are satisfactory for the cities of Yokadouma and Kumba in the bimodal and monomodal rainfall zones, where overall accuracies are up to 98.9% and 97.5%, with kappa coefficients of 0.88 and 0.94 respectively, although these values are close to those of three other indices. However, in the cities of Foumban, Ngaoundéré and Garoua, representing the western highlands, the high Guinea savannah and the Sudano-sahelian zones where built-up is more confused with soil features, overall accuracies of 97.06%, 95.29% and 74.86%, corresponding to 0.918, 0.89 and 0.42 kappa coefficients were recorded. Difference of accuracy with EBBI, NDBI and UI are up to 31.66%, confirming the NDBSUI efficiency to automate built-up extraction and unmixing from surrounding noises with less biases. © 2020 International Society for Photogrammetry and Remote Sensing. All rights reserved.

关键词： Landsat

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Single Image Super-Resolution with Application to Remote-Sensing Image

Single Image Super-Resolution with Application to Remote-Sen...

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Wireless and Optical Technologies (GCWOT), 2020 Global Conference on

作者： Farah Deeba Fayaz Ali Dharejo Yuanchun Zhou Abdul Ghaffar Mujahid Hussain Memon She Kun Institute of Computer Network Information Center Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China University of Chinese Academy of sciences Bejing China The Pakistan Council of Scientific and Industrial Research Laboratories Complex Karachi Pakistan School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9781665418607

ISBN: (纸本)9781665448116

To improve the resolution of satellite images, many researchers are committed to machine learning and neural network-based SR methods. SR has multiple residual network frameworks in deep learning that have improved performance and can extend thousands of layers in the system. However, each layer improves accuracy by doubling the number of layers, although training thousands of layers are too expensive, the process is slow, and there are functional recovery issues. To address these issues, we propose a super-resolution wide remote sensing residual network (WRSR), in which we increase the width and reduce the depth of the residual network, due to decreasing the depth of the network our model reduced memory costs. To enhance the resolution of the single image we showed that our method improves training loss performance by performing the weight normalization instead of augmentation technology. The results of the experiment show that the method performs well in terms of quantitative indicators (PSNR) and (SSIM).

关键词： Training Optical losses Wireless communication Wireless sensor networks Superresolution Remote sensing Residual neural networks

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Correction to “The Open Catalyst 2020 (OC20) Dataset and Community Challenges”

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ACS Catalysis 2021年第21期11卷 13062-13065页

作者： Lowik Chanussot Abhishek Das Siddharth Goyal Thibaut Lavril Muhammed Shuaibi Morgane Riviere Kevin Tran Javier Heras-Domingo Caleb Ho Weihua Hu Aini Palizhati Anuroop Sriram Brandon Wood Junwoong Yoon Devi Parikh C. Lawrence Zitnick Zachary Ulissi Facebook AI Research (FAIR) 1 Hacker Way Menlo Park California 94025 United States Department of Chemical Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States Computer Science Department Stanford University Stanford California 94305 United States National Energy Research Scientific Computing Center (NERSC) Lawrence Berkeley National Laboratory Berkeley California 94720 United States School of Interactive Computing Georgia Tech Atlanta Georgia 30332 United States Scott Institute for Energy Innovation Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States

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AGE Challenge: Angle Closure Glaucoma Evaluation in Anterior Segment Optical Coherence Tomography

arXiv

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arXiv 2020年

作者： Fu, Huazhu Li, Fei Sun, Xu Cao, Xingxing Liao, Jingan Orlando, José Ignacio Tao, Xing Li, Yuexiang Zhang, Shihao Tan, Mingkui Yuan, Chenglang Bian, Cheng Xie, Ruitao Li, Jiongcheng Li, Xiaomeng Wang, Jing Geng, Le Li, Panming Hao, Huaying Liu, Jiang Kong, Yan Ren, Yongyong Bogunović, Hrvoje Zhang, Xiulan Xu, Yanwu State Key Laboratory Zhongshan Ophthalmic Center Sun Yat-sen University Guangzhou510060 China Inception Institute of Artificial Intelligence Abu Dhabi United Arab Emirates Intelligent Healthcare Unit Baidu Beijing China School of Computer Science and Engineering South China University of Technology GuangzhouGuangdong China National Scientific and Technical Research Council CONICET Argentina Tandil Argentina School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China Tencent Jarvis Lab Shenzhen China School of Software Engineering South China University of Technology Guangzhou China School of Biomedical Engineering Health Science Center Shenzhen University Shenzhen China School of Electronic and Information Engineering Shenzhen University Shenzhen China Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong School of Electronic and Information Engineering Soochow University Suzhou China Ningbo University Zhejiang China Ningbo Institute of Industrial Technology Chinese Academy of Sciences Zhejiang China Southern University of Science and Technology Shenzhen China Shanghai Jiaotong University Shanghai China Laboratory for Ophthalmic Image Analysis Department of Ophthalmology Medical University of Vienna Vienna Austria

Angle closure glaucoma (ACG) is a more aggressive disease than open-angle glaucoma, where the abnormal anatomical structures of the anterior chamber angle (ACA) may cause an elevated intraocular pressure and gradually leads to glaucomatous optic neuropathy and eventually to visual impairment and blindness. Anterior Segment Optical Coherence Tomography (AS-OCT) imaging provides a fast and contactless way to discriminate angle closure from open angle. Although many medical image analysis algorithms have been developed for glaucoma diagnosis, only a few studies have focused on AS-OCT imaging. In particular, there is no public AS-OCT dataset available for evaluating the existing methods in a uniform way, which limits the progress in the development of automated techniques for angle closure detection and assessment. To address this, we organized the Angle closure Glaucoma Evaluation challenge (AGE), held in conjunction with MICCAI 2019. The AGE challenge consisted of two tasks: scleral spur localization and angle closure classification. For this challenge, we released a large data of 4800 annotated AS-OCT images from 199 patients, and also proposed an evaluation framework to benchmark and compare different models. During the AGE challenge, over 200 teams registered online, and more than 1100 results were submitted for online evaluation. Finally, eight teams participated in the onsite challenge. In this paper, we summarize these eight onsite challenge methods and analyze their corresponding results in the two tasks. We further discuss limitations and future directions. In the AGE challenge, the top-performing approach had an average Euclidean Distance of 10 pixel (10µm) in scleral spur localization, while in the task of angle closure classification, all the algorithms achieved the satisfactory performances, especially, 100% accuracy rate for top-two performances. These artificial intelligence techniques were shown to have the potential to enable new developments in AS-OCT

关键词： Ophthalmology

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