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New roles of research data infrastructure in research paradigm evolution

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Journal of Data and information Science 2024年第2期9卷 104-119页

作者： Yizhan Li Lu Dong Xiaoxiao Fan Ren Wei Shijie Guo Wenzhen Ma Zexia Li National Library Science Chinese Academy of SciencesBeijing 100190China department of information Resources management School of Economics and ManagementUniversity of Chinese Academy of SciencesBeijing100190China Bureau of Facility Support and Budget Chinese Academy of SciencesBeijing 100864China

Research data infrastructures form the cornerstone in both cyber and physical spaces,driving the progression of the data-intensive scientific research *** opinion paper presents an overview of global research data infrastructure,drawing insights from national roadmaps and strategic documents related to research data *** emphasizes the pivotal role of research data infrastructures by delineating four new missions aimed at positioning them at the core of the current scientific research and communication *** four new missions of research data infrastructures are:(1)as a pioneer,to transcend the disciplinary border and address complex,cutting-edge scientific and social challenges with problem-and data-oriented insights;(2)as an architect,to establish a digital,intelligent,flexible research and knowledge services environment;(3)as a platform,to foster the high-end academic communication;(4)as a coordinator,to balance scientific openness with ethics needs.

关键词： Research data infrastructure Landscape Data-centric Problem-oriented

Market Equilibrium Based on Cloud-edge Collaboration

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CSEE Journal of Power and Energy systems 2024年第1期10卷 96-104页

作者： Tong Cheng Haiwang Zhong Qing Xia the State Key Laboratory of Power systems the Department of Electrical EngineeringTsinghua UniversityBeijing 100084China

Market participants can only bid with lagged information disclosure under the existing market mechanism,which can lead to information asymmetry and irrational market behavior,thus influencing market *** promote rational bidding behavior of market participants and improve market efficiency,a novel electricity market mechanism based on cloudedge collaboration is proposed in this *** market information,called residual demand curve,is published to market participants in real-time on the cloud side,while participants on the edge side are allowed to adjust their bids according to the information disclosure prior to closure *** proposed mechanism can encourage rational bids in an incentive-compatible way through the process of dynamic equilibrium while protecting participants’*** paper further formulates the mathematical model of market equilibrium to simulate the process of each market participant’s strategic bidding behavior towards equilibrium.A case study based on the IEEE 30-bus system shows the proposed market mechanism can effectively guide bidding behavior of market participants,while condensing exchanged information and protecting privacy of participants.

关键词： Cloud-edge collaboration market mechanism residual demand curve strategic bidding

Low-Brightness Object Recognition Based on Deep Learning

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Computers, Materials & Continua 2024年第5期79卷 1757-1773页

作者： Shu-Yin Chiang Ting-Yu Lin department of information and Telecommunications Engineering Ming Chuan UniversityTaoyuan City333Taiwan

This research focuses on addressing the challenges associated with image detection in low-light environments,particularly by applying artificial intelligence techniques to machine vision and object recognition *** primary goal is to tackle issues related to recognizing objects with low brightness *** this study,the Intel RealSense Lidar Camera L515 is used to simultaneously capture color information and 16-bit depth information *** detection scenarios are categorized into normal brightness and low brightness *** the system determines a normal brightness environment,normal brightness images are recognized using deep learning *** low-brightness situations,three methods are proposed for *** first method is the SegmentationwithDepth image(SD)methodwhich involves segmenting the depth image,creating amask from the segmented depth image,mapping the obtained mask onto the true color(RGB)image to obtain a backgroundreduced RGB image,and recognizing the segmented *** second method is theHDVmethod(hue,depth,value)which combines RGB images converted to HSV images(hue,saturation,value)with depth images D to form HDV images for *** third method is the HSD(hue,saturation,depth)method which similarly combines RGB images converted to HSV images with depth images D to form HSD images for *** experimental results,in normal brightness environments,the average recognition rate obtained using image recognition methods is 91%.For low-brightness environments,using the SD method with original images for training and segmented images for recognition achieves an average recognition rate of over 82%.TheHDVmethod achieves an average recognition rate of over 70%,while the HSD method achieves an average recognition rate of over 84%.The HSD method allows for a quick and convenient low-light object recognition *** research outcome can be applied to nighttime surveillance systems or nighttime road safety systems

关键词： Low-brightness depth image image segmentation image recognition HDV HSD

CapsNet-FR: Capsule Networks for Improved Recognition of Facial Features

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Computers, Materials & Continua 2024年第5期79卷 2169-2186页

作者： Mahmood Ul Haq Muhammad Athar Javed Sethi Najib Ben Aoun Ala Saleh Alluhaidan Sadique Ahmad Zahid farid department of Computer System Engineering University of Engineering&TechnologyPeshawar25000Pakistan College of Computer Science and information Technology Al-Baha UniversityAlaqiq65779-7738Saudi Arabia REGIM-Lab:Research Groups in Intelligent Machines National School of Engineers of Sfax(ENIS)University of SfaxSfax3038Tunisia department of information systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia EIAS:Data Science and Blockchain Laboratory College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia department of Computer Sciences Bahria University Karachi CampusKarachi541004Pakistan department of Electrical Engineering Abasyn UniversityPeshawar25000Pakistan

Face recognition (FR) technology has numerous applications in artificial intelligence including biometrics, security,authentication, law enforcement, and surveillance. Deep learning (DL) models, notably convolutional neuralnetworks (CNNs), have shown promising results in the field of FR. However CNNs are easily fooled since theydo not encode position and orientation correlations between features. Hinton et al. envisioned Capsule Networksas a more robust design capable of retaining pose information and spatial correlations to recognize objects morelike the brain does. Lower-level capsules hold 8-dimensional vectors of attributes like position, hue, texture, andso on, which are routed to higher-level capsules via a new routing by agreement algorithm. This provides capsulenetworks with viewpoint invariance, which has previously evaded CNNs. This research presents a FR model basedon capsule networks that was tested using the LFW dataset, COMSATS face dataset, and own acquired photos usingcameras measuring 128 × 128 pixels, 40 × 40 pixels, and 30 × 30 pixels. The trained model outperforms state-ofthe-art algorithms, achieving 95.82% test accuracy and performing well on unseen faces that have been blurred orrotated. Additionally, the suggested model outperformed the recently released approaches on the COMSATS facedataset, achieving a high accuracy of 92.47%. Based on the results of this research as well as previous results, capsulenetworks perform better than deeper CNNs on unobserved altered data because of their special equivarianceproperties.

关键词： CapsNet face recognition artificial intelligence

A statistical analysis of the Kappa-type energy spectrum distribution of radiation belt electrons observed by Van Allen Probes

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Earth and Planetary Physics 2024年第2期8卷 368-374页

作者： LuHuai Jiao Xin Ma YuanNong Zhang TaiFeng Jin Song Fu BinBin Ni department of Space Physics School of Electronic InformationWuhan UniversityWuhan 430072China

The energy spectrum of energetic electrons is a key factor representing the dynamic variations of Earth’s Van Allen radiation *** measurements have indicated that the commonly used Maxwellian and Kappa distributions are inadequate for capturing the realistic spectral distributions of radiation belt *** we adopt the Kappa-type(KT)distribution as the fitting function and perform a statistical analysis to investigate the radiation belt electron flux spectra observed by the Van Allen *** calculating the optimal values of the key KT distribution parameters(i.e.,κandθ2)from the observed spectral shapes,we fit the radiation belt electron fluxes at different L-shells under different geomagnetic *** this manner,we obtain typical values of the KT distribution parameters,which are statistically feasible for modeling the radiation belt electron flux profiles during either geomagnetically quiet or active periods.A comparison of the KT distribution model results with those using the Maxwellian or Kappa distribution reveals the advantage of the KT distribution for studying the overall properties of the radiation belt electron spectral distribution,which has important implications for deepening the current understanding of the radiation belt electron dynamics under evolving geomagnetic conditions.

关键词： radiation belt electron Kappa-type distribution fitting geomagnetic storm

Models to Simulate Effective Coverage of Fire Station Based on Real-Time Travel Times

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 483-513页

作者： Sicheng Zhu Dingli Liu Weijun Liu Ying Li Tian Zhou department of Engineering management Changsha University of Science and TechnologyChangsha410114China

In recent years,frequent fire disasters have led to enormous damage in *** firefighting rescues can minimize the losses caused by *** the rescue processes,the travel time of fire trucks can be severely affected by traffic conditions,changing the effective coverage of fire ***,it is still challenging to determine the effective coverage of fire stations considering dynamic traffic *** paper addresses this issue by combining the traveling time calculationmodelwith the effective coverage *** addition,it proposes a new index of total effective coverage area(TECA)based on the time-weighted average of the effective coverage area(ECA)to evaluate the urban fire *** also selects China as the case study to validate the feasibility of the models,a fire station(FS-JX)in ***-JX station and its surrounding 9,117 fire risk points are selected as the fire service supply and demand points,respectively.A total of 196 simulation scenarios throughout a consecutiveweek are ***,1,933,815 sets of valid sample data are *** results showed that the TECA of FS-JX is 3.27 km^(2),which is far below the standard requirement of 7.00 km^(2) due to the traffic *** visualization results showed that three rivers around FS-JX interrupt the continuity of its effective *** proposed method can provide data support to optimize the locations of fire stations by accurately and dynamically determining the effective coverage of fire stations.

关键词： Fire services fire station effective coverage real-time traffic simulation

Quantum self-attention neural networks for text classification

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Science China(information Sciences) 2024年第4期67卷 301-313页

作者： Guangxi LI Xuanqiang ZHAO Xin WANG Institute for Quantum Computing Baidu Research Centre for Quantum Software and information University of Technology Sydney QICI Quantum information and Computation Initiative Department of Computer ScienceThe University of Hong Kong Thrust of Artificial Intelligence Information HubHong Kong University of Science and Technology(Guangzhou)

An emerging direction of quantum computing is to establish meaningful quantum applications in various fields of artificial intelligence, including natural language processing(NLP). Although some efforts based on syntactic analysis have opened the door to research in quantum NLP(QNLP), limitations such as heavy syntactic preprocessing and syntax-dependent network architecture make them impracticable on larger and real-world data sets. In this paper, we propose a new simple network architecture, called the quantum selfattention neural network(QSANN), which can compensate for these limitations. Specifically, we introduce the self-attention mechanism into quantum neural networks and then utilize a Gaussian projected quantum self-attention serving as a sensible quantum version of self-attention. As a result, QSANN is effective and scalable on larger data sets and has the desirable property of being implementable on near-term quantum devices. In particular, our QSANN outperforms the best existing QNLP model based on syntactic analysis as well as a simple classical self-attention neural network in numerical experiments of text classification tasks on public data sets. We further show that our method exhibits robustness to low-level quantum noises and showcases resilience to quantum neural network architectures.

关键词： quantum neural networks self-attention natural language processing text classification parameterized quantum circuits

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Overshoot phenomena:Observation and simulation

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Earth and Planetary Physics 2024年第2期8卷 391-399页

作者： Ting Feng MoRan Liu ShiMin He Xiang Wang Chen Zhou department of Space Physics School of Electronic InformationWuhan UniversityWuhan 430072China

High-power O-mode radio waves can excite artificial instabilities in the F region,according to experiments conducted at the European Incoherent Scatter Science Association(EISCAT)heating *** main instabilities include the parametric decay instability(PDI),oscillating two-stream instability(OTSI),and thermal parametric instability(TPI).The PDI and OTSI not only compete with each other,but also compete with the TPI,leading to a two-stage overshoot phenomenon:a miniovershoot occurs on a millisecond time scale after pump-on,followed by the main *** gain insight into the miniovershoot via a generalized Zakharov model,whereas the main overshoot can be observed as an enhanced plasma line overshoot phenomenon in incoherent scatter radar *** can also observe that the zero-frequency ion line exists only in the initial heating period after a cold start and that the upshifted and downshifted ion lines behave irregularly in the *** simulation results show that competition between the PDI and OTSI leads to an initial peak,which we named the *** following processes,namely ion density caviton generation,and collapse and cascade in the development of the PDI,contribute to the miniovershoot phenomenon.

关键词： overshoot parametric decay instability oscillating two-stream instability competition

Effect of interplanetary magnetic field B_(x)on the polar electrojets as observed by CHAMP and Swarm satellites

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Earth and Planetary Physics 2024年第2期8卷 382-390页

作者： Hui Wang ChengZhi Wang YunFang Zhong department of Space Physics School of Electronic InformationWuhan UniversityWuhan 430072China

Based on 16 years of magnetic field observations from CHAMP and Swarm satellites,this study investigates the influence of the Interplanetary Magnetic Field(IMF)Bx component on the location and peak current density of the polar electrojets(PEJs).We find that the IMF Bx displays obvious local time,seasonal,and hemispherical effects on the PEJs,as follows:(1)Compared to other local times,its influence is weakest at dawn and dusk.(2)In the midnight sectors of both hemispheres,the IMF Bx tends to amplify the westward PEJ when it is0 in the Southern Hemisphere;this effect is relatively stronger in the local winter hemisphere.(3)At noontime,the IMF Bx intensifies the eastward current when it is0,it reduces the westward current;this effect is notably more prominent in the local summer hemisphere.(4)Moreover,the noontime eastward current shifts towards higher latitudes,while the midnight westward current migrates towards lower latitudes when IMF Bx is0 in the Southern Hemisphere.

关键词： polar electrojet interplanetary magnetic field Bx local time asymmetry hemispheric difference