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Predicting extreme events from data using deep machine learning: When and where

Physical Review Research 2022年第2期4卷 023028-023028页

作者： Junjie Jiang Zi-Gang Huang Celso Grebogi Ying-Cheng Lai The Key Laboratory of Biomedical Information Engineering of Ministry of Education Institute of Health and Rehabilitation Science School of Life Science and Technology Research Center for Brain-inspired Intelligence Xi'an Jiaotong University The Key Laboratory of Neuro-informatics & Rehabilitation Engineering of Ministry of Civil Affairs Xi'an Shaanxi 710049 China School of Electrical Computer and Energy Engineering Arizona State University Tempe Arizona 85287 USA Institute for Complex Systems and Mathematical Biology School of Natural and Computing Sciences King's College University of Aberdeen Aberdeen AB24 3UE United Kingdom Department of Physics Arizona State University Tempe Arizona 85287 USA

We develop a framework based on the deep convolutional neural network (DCNN) for model-free prediction of the occurrence of extreme events both in time (“when”) and in space (“where”) in nonlinear physical systems of spatial dimension two. The measurements or data are a set of two-dimensional snapshots or images. For a desired time horizon of prediction, a proper labeling scheme can be designated to enable successful training of the DCNN and subsequent prediction of extreme events in time. Given that an extreme event has been predicted to occur within the time horizon, a space-based labeling scheme can be applied to predict, within certain resolution, the location at which the event will occur. We use synthetic data from the two-dimensional complex Ginzburg-Landau equation and empirical wind speed data from the North Atlantic Ocean to demonstrate and validate our machine-learning-based prediction framework. The trade-offs among the prediction horizon, spatial resolution, and accuracy are illustrated, and the detrimental effect of spatially biased occurrence of extreme events on prediction accuracy is discussed. The deep learning framework is viable for predicting extreme events in the real world.

关键词： Machine learning Spatiotemporal chaos Artificial neural networks Extreme event statistics

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Broadband miniaturized spectrometers with a van der Waals tunnel diode

arXiv

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arXiv 2024年

作者： Uddin, Gius Das, Susobhan Shafi, Abde Mayeen Wang, Lei Cui, Xiaoqi Nigmatulin, Fedor Ahmed, Faisal Liapis, Andreas C. Cai, Weiwei Yang, Zongyin Lipsanen, Harri Hasan, Tawfique Yoon, Hoon Hahn Sun, Zhipei Department of Electronics and Nanoengineering Aalto University Espoo02150 Finland QTF Centre of Excellence Aalto University Aalto00076 Finland Key Lab of Education Ministry for Power Machinery and Engineering School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China College of Information Science and Electronic Engineering State Key Laboratory of Modern Optical Instrumentation Zhejiang University Hangzhou310027 China Cambridge Graphene Centre University of Cambridge CambridgeCB3 0FA United Kingdom Department of Semiconductor Engineering School of Electrical Engineering and Computer Science Gwangju Institute of Science and Technology 123 Cheomdangwagi-ro Buk-gu Gwangju61005 Korea Republic of

Miniaturized spectrometers are of immense interest for various on-chip and implantable photonic and optoelectronic applications. state-of-the-art conventional spectrometer designs rely heavily on bulky dispersive components (such as gratings, photodetector arrays, and interferometric optics) to capture different input spectral components that increase their integration complexity. Here, we report a high-performance broadband spectrometer based on a simple and compact van der Waals heterostructure diode, leveraging a careful selection of active van der Waals materials-molybdenum disulfide and black phosphorus, their electrically tunable photoresponse, and advanced computational algorithms for spectral reconstruction. We achieve remarkably high peak wavelength accuracy of ~2 nanometers, and broad operation bandwidth spanning from ~500 to 1600 nanometers in a device with a ~30×20 μm2 footprint. This diode-based spectrometer scheme with broadband operation offers an attractive pathway for various applications, such as sensing, surveillance and spectral imaging. © 2024, CC BY.

关键词： Spectrometers

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Fine-grained image analysis with deep learning: A survey

arXiv

引用

arXiv 2021年

作者： Wei, Xiu-Shen Song, Yi-Zhe Aodha, Oisin Mac Wu, Jianxin Peng, Yuxin Tang, Jinhui Yang, Jian Belongie, Serge PCA Lab Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Jiangsu Key Lab of Image Video Understanding for Social Security School of Computer Science and Engineering Nanjing University of Science and Technology China University of Surrey United Kingdom The University of Edinburgh United Kingdom The State Key Laboratory for Novel Software Technology Nanjing University China Peking University China Nanjing University of Science and Technology China The University of Copenhagen The Pioneer Centre for AI Denmark

Fine-grained image analysis (FGIA) is a longstanding and fundamental problem in computer vision and pattern recognition, and underpins a diverse set of real-world applications. The task of FGIA targets analyzing visual objects from subordinate categories, e.g., species of birds or models of cars. The small inter-class and large intra-class variation inherent to fine-grained image analysis makes it a challenging problem. Capitalizing on advances in deep learning, in recent years we have witnessed remarkable progress in deep learning powered FGIA. In this paper we present a systematic survey of these advances, where we attempt to re-define and broaden the field of FGIA by consolidating two fundamental fine-grained research areas – fine-grained image recognition and fine-grained image retrieval. In addition, we also review other key issues of FGIA, such as publicly available benchmark datasets and related domain-specific applications. We conclude by highlighting several research directions and open problems which need further exploration from the community. © 2021, CC BY.

关键词： Image recognition

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Automatic Context Pattern Generation for Entity Set Expansion

arXiv

引用

arXiv 2022年

作者： Li, Yinghui Huang, Shulin Zhang, Xinwei Zhou, Qingyu Li, Yangning Liu, Ruiyang Cao, Yunbo Zheng, Hai-Tao Shen, Ying Shenzhen International Graduate School Tsinghua University Guangdong Shenzhen518055 China Peng Cheng Laboratory Guangdong Shenzhen518066 China The School of Intelligent Systems Engineering Sun Yat-Sen University Guangdong Guangzhou510275 China The Tencent Cloud Xiaowei Beijing100190 China The Department of Computer Science and Technology Tsinghua University Beijing100190 China

Entity Set Expansion (ESE) is a valuable task that aims to find entities of the target semantic class described by given seed entities. Various Natural Language Processing (NLP) and Information Retrieval (IR) downstream applications have benefited from ESE due to its ability to discover knowledge. Although existing corpus-based ESE methods have achieved great progress, they still rely on corpora with high-quality entity information annotated, because most of them need to obtain the context patterns through the position of the entity in a sentence. Therefore, the quality of the given corpora and their entity annotation has become the bottleneck that limits the performance of such methods. To overcome this dilemma and make the ESE models free from the dependence on entity annotation, our work aims to explore a new ESE paradigm, namely corpus-independent ESE. Specifically, we devise a context pattern generation module that utilizes autoregressive language models (e.g., GPT-2) to automatically generate high-quality context patterns for entities. In addition, we propose the GAPA, a novel ESE framework that leverages the aforementioned GenerAted PAtterns to expand target entities. Extensive experiments and detailed analyses on three widely used datasets demonstrate the effectiveness of our method. All the codes of our experiments are available at https://***/geekjuruo/GAPA. Copyright © 2022, The Authors. All rights reserved.

关键词： Information retrieval

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Training, testing and benchmarking medical AI models using Clinical AIBench

引用

BenchCouncil Transactions on Benchmarks, Standards and Evaluations 2022年第1期2卷 100037-100037页

作者： Huang, Yunyou Miao, Xiuxia Zhang, Ruchang Ma, Li Liu, Wenjing Zhang, Fan Guan, Xianglong Liang, Xiaoshuang Lu, Xiangjiang Tang, Suqing Zhang, Zhifei Guangxi Key Lab of Multi-Source Information Mining & Security School of Computer Science and Engineering & School of Software Guangxi Normal University Guilin China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China Guilin Medical University Guilin China Department of Physiology and Pathophysiology Capital Medical University Beijing China Faculty of Education Guangxi Normal University Guilin China International Open Benchmark Council Beijing China

AI technology has been used in many clinical research fields, but most AI technologies are difficult to land in real-world clinical settings. In most current clinical AI research settings, the diagnosis task is to identify different types of diseases among the given ones. However, the diagnosis in real-world settings needs dynamically developing inspection strategies based on the existing resources of medical institutions and identifying different kinds of diseases out of many possibilities. To promote the development of different clinical AI technologies and the implementation of clinical applications, we propose a benchmark named Clinical AIBench for developing, verifying, and evaluating clinical AI technologies in real-world clinical settings. Specifically, Clinical AIBench can be used for: (1) Model training and testing: Researchers can use the data to train and test their models. (2)Model evaluation: Researchers can use Clinical AIBench to objectively, fairly, and comparably evaluate various models of different researchers. (3) Clinical value evaluation: Researchers can use the clinical indicators provided by Clinical AIBench to evaluate the clinical value of models, which will be applied in real-world clinical settings. For convenience, Clinical AIBench provides three different levels of clinical settings: restricted clinical setting, which is named closed clinical setting, data island clinical setting, and real-world clinical setting, which is called open clinical setting. In addition, Clinical AIBench covers three diseases: Alzheimer's disease, COVID-19, and dental. Clinical AIBench provides python APIs to researchers. The data and source code are publicly available from the project website https://***/clinical_aibench/. © 2022 The Authors

关键词： COVID-19

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The Combination of Two Control Strategies for Series Hybrid Electric Vehicles

引用

IEEE/CAA Journal of Automatica Sinica 2019年第2期6卷 596-608页

作者： Can Luo Zhen Shen Simos Evangelou Gang Xiong Fei-Yue Wang State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Cloud Computing Center Chinese Academy of Sciences IEEE Department of Electrical and Electronic Engineering Imperial College London Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Qingdao Academy of Intelligent Industries

With most countries paying attention to the environment protection, hybrid electric vehicles have become a focus of automobile research and development due to the characteristics of energy saving and low emission. Power follower control strategy(PFCS) and DC-link voltage control strategy are two sorts of control strategies for series hybrid electric vehicles(HEVs). Combining those two control strategies is a new idea for control strategy of series hybrid electric vehicles. By tuning essential parameters which are the defined constants under DClink voltage control and under PFCS, the points of minimum mass of equivalent fuel consumption(EFC) corresponding to a series of variables are marked for worldwide harmonized light vehicles test procedure(WLTP). The fuel economy of series HEVs with the combination control schemes performs better compared with individual control scheme. The results show the effects of the combination control schemes for series HEVs driving in an urban environment.

关键词： DC-Link voltage control power follower control strategy series hybrid electric vehicles tuning

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Communication-Sensing Region for Cell-Free Massive MIMO ISAC systems

arXiv

引用

arXiv 2023年

作者： Mao, Weihao Lu, Yang Chi, Chong-Yung Ai, Bo Zhong, Zhangdui Ding, Zhiguo The School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China The Institute of Communications Engineering Department of Electrical Engineering National Tsing Hua University Hsinchu30013 Taiwan The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The School of Electronics and Information Engineering Beijing Jiaotong University Beijing100044 China Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi United Arab Emirates Department of Electrical and Electronic Engineering University of Manchester Manchester United Kingdom

This paper investigates the system model and the transmit beamforming design for the Cell-Free massive multi-input multi-output (MIMO) integrated sensing and communication (ISAC) system. The impact of the uncertainty of the target locations on the propagation of wireless signals is considered during both uplink and downlink phases, and especially, the main statistics of the MIMO channel estimation error are theoretically derived in the closed-form fashion. A fundamental performance metric, termed communication-sensing (C-S) region, is defined for the considered system via three cases, i.e., the sensing-only case, the communication-only case and the ISAC case. The transmit beamforming design problems for the three cases are respectively carried out through different reformulations, e.g., the Lagrangian dual transform and the quadratic fractional transform, and some combinations of the block coordinate descent method and the successive convex approximation method. Numerical results present a 3-dimensional C-S region with a dynamic number of access points to illustrate the trade-off between communication and radar sensing. The advantage for radar sensing of the Cell-Free massive MIMO system is also studied via a comparison with the traditional cellular system. Finally, the efficacy of the proposed beamforming scheme is validated in comparison with zero-forcing and maximum ratio transmission schemes. Copyright © 2023, The Authors. All rights reserved.

关键词： Beamforming

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Interpretation-Enabled Software Reuse Detection Based on a Multi-level Birthmark Model

Interpretation-Enabled Software Reuse Detection Based on a M...

引用

International Conference on Software Engineering (ICSE)

作者： Xi Xu Qinghua Zheng Zheng Yan Ming Fan Ang Jia Ting Liu Key Laboratory of Intelligent Networks and Network Security Ministry of Education China School of Computer Science and Technology Xi’an Jiaotong University China State Key Lab on Integrated Services Networks School of Cyber Engineering Xidian University China Department of Communications and Networking Aalto University Finland School of Cyber Science and Engineering Xi’an Jiaotong University China

ISBN: (纸本)9781665402965;9781665448314

Software reuse, especially partial reuse, poses legal and security threats to software development. Since its source codes are usually unavailable, software reuse is hard to be detected with interpretation. On the other hand, current approaches suffer from poor detection accuracy and efficiency, far from satisfying practical demands. To tackle these problems, in this paper, we propose ISRD, an interpretation-enabled software reuse detection approach based on a multi-level birthmark model that contains function level, basic block level, and instruction level. To overcome obfuscation caused by cross-compilation, we represent function semantics with Minimum Branch Path (MBP) and perform normalization to extract core semantics of instructions. For efficiently detecting reused functions, a process for "intent search based on anchor recognition" is designed to speed up reuse detection. It uses strict instruction match and identical library call invocation check to find anchor functions (in short anchors) and then traverses neighbors of the anchors to explore potentially matched function pairs. Extensive experiments based on two real-world binary datasets reveal that ISRD is interpretable, effective, and efficient, which achieves 97.2% precision and 94.8% recall. Moreover, it is resilient to cross-compilation, outperforming state-of-the-art approaches.

关键词： Law Semantics Libraries Security Software reusability Software engineering Resilience

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The Important Role of Diatomite on Multifunctional Modified Separator of Li-S Battery

SSRN

引用

SSRN 2024年

作者： Yan, Chenyu Jiang, Zhiyi Yang, Caihong Dong, Xiongbo Zhang, Shilin Tu, Feiyue Li, Tianbao Li, Mitch Guijun Tang, Aidong Yang, Huaming Engineering Research Center of Nano-Geomaterials of Ministry of Education Laboratory of Advanced Mineral Materials Key Laboratory of Functional Geomaterials in China Nonmetallic Minerals Industry Faculty of Materials Science and Chemistry China University of Geosciences Wuhan430074 China College of Chemistry and Chemical Engineering Central South University Changsha410083 China Changsha Research Institute of Mining and Metallurgy Co. LTD Changsha410012 China Division of Integrative Systems and Design Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong School of Minerals Processing and Bioengineering Central South University Changsha410083 China

The commercial applications of Li-S batteries are limited by decreased cycling performance caused by the shuttle effect of polysulfides, slower kinetic reaction rates, and lithium anode dendrites. This study demonstrates the important role of diatomite (DT) in regulating cycle performance of modified separator for Li-S batteries. A multifunctional separator (Co/NC/DT) with DT as a carrier assembled high loading Co nanocluster (size 2-4 nm) is prepared. The N-doped carbon is immobilized via Si-N bond between DT and N-doped carbon. The depth profiles of XPS indicates that the ratio of pyrrolic N to pyridinic N of Co/NC/DT reaches 5.31 at the etching of 100 nm vs 0.83 for Co/NC at surface, which suggesting that mainly N species is pyrrolic N after the addition of DT. Theoretical calculations confirm that cobalt nanoclusters grown on pyrrolic N-doped carbon have a lower adsorption energy for a series of polysulfides species compared to that on pyridinic N-doped carbon and can reduce the energy barrier, especially only 0.09 eV for reduction from Li2S6 to Li2S4. In-situ X-ray diffraction analysis confirms Co/NC/DT can effectively promote formation of Li2S. Lithium anode in-situ optical microscopy observation shows the modified separator could reduce lithium dendrites effectively. Li-S battery assembled with the modified separator can reach an initial capacity of 1331.3 mAh g-1 at 0.2 C and cycle 1500 cycles at 1.0 C with a decay of only 0.039% per cycle. Through regulation of DT, Co/NC/DT accelerates the conversion from long-chain sulfur to short-chain sulfur and Li+ transfer rate, resulting in improving cycling performance. © 2024, The Authors. All rights reserved.

关键词： Separators

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Chance Constrained Economic Dispatch Considering the Capability of Network Flexibility Against Renewable Uncertainties

arXiv

引用

arXiv 2021年

作者： Song, Yue Liu, Tao Hill, David J. The Department of Control Science and Engineering Tongji University Shanghai201804 China The National Key Laboratory of Autonomous Intelligent Unmanned Systems Shanghai201210 China The Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai200120 China Hong Kong The HKU Shenzhen Institute of Research and Innovation Shenzhen China The Department of Electrical and Computer Systems Engineering Monash University MelbourneVIC3000 Australia The Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong

This paper incorporates a continuous-type network flexibility into chance constrained economic dispatch (CCED). In the proposed model, both power generations and line susceptances are continuous variables to minimize the expected generation cost and guarantee a low probability of constraint violation in terms of generations and line flows under renewable uncertainties. From the analytical form of CCED, we figure out the mechanism of network flexibility against uncertainties-while renewable uncertainties shrink the usable line capacities and aggravate transmission congestion, network flexibility mitigates congestion by re-routing the base-case line flows and reducing the line capacity shrinkage caused by uncertainties. Further, we propose an alternate iteration solver for this problem. By duality theory, we set up a master problem in the form of second-order cone programming to optimize generation dispatch scheme and a subproblem in the form of linear programming to optimize line susceptances. A satisfactory solution can be obtained efficiently by alternately solving these two problems. The proposed method applies to both Gaussian uncertainty and non-Gaussian uncertainty by means of Gaussian mixture model. The case studies on the IEEE 14-bus system and IEEE 118-bus system suggest that network flexibility can significantly improve operational economy while ensuring security under uncertainties. © 2021, CC BY.

关键词： Second-order cone programming

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