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A Numerical Investigation of the Effect of Boundary Conditions on Acoustic Pressure Distribution in a Sonochemical Reactor Chamber

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Fluid Dynamics & Materials Processing 2024年第6期20卷 1425-1439页

作者： Ivan Sboev Tatyana Lyubimova Konstantin Rybkin Michael Kuchinskiy UEC-Aviadvigatel 93 Komsomolsky ProspectPerm614990Russia laboratory of computing Hydrodynamic Institute of Continuous Media Mechanics UB RASPerm614013Russia laboratory of Interfacial Hydrodynamic Perm State UniversityPerm614068Russia

The intensification of physicochemical processes in the sonochemical reactor chamber is widely used in problems of synthesis,extraction and *** of the most important mechanisms at play in such processes is the acoustic cavitation due to the non-uniform distribution of acoustic pressure in the *** has a strong impact on the surface degradation *** this work,a numerical calculation of the acoustic pressure distribution inside the reactor chamber was performed using COMSOL *** numerical results have revealed the dependence of the structure of the acoustic pressure field on the boundary conditions for various thicknesses of the piezoelectric *** particular,the amplitude of the acoustic pressure is minimal in the case of absorbing boundaries,and the attenuation becomes more significant as the thickness of the piezoelectric transducer *** addition,reflective boundaries play a significant role in the formation and distribution of zones of maximum cavitation activity.

关键词： Ultrasound numerical simulation acoustic pressure field cavitation erosion foil test

Integrating Neighborhood Geographic Distribution and Social Structure Influence for Social media User Geolocation

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Computer Modeling in Engineering & Sciences 2024年第9期140卷 2513-2532页

作者： Meng Zhang Xiangyang Luo Ningbo Huang Key laboratory of Cyberspace Situation Awareness of Henan Province Zhengzhou450001China State Key laboratory of Mathematical Engineering and Advanced computing Zhengzhou450001China

Geolocating social media users aims to discover the real geographical locations of users from their publicly available data,which can support online location-based applications such as disaster alerts and local content *** relationship-based methods represent a classical approach for geolocating social ***,geographically proximate relationships are sparse and challenging to discern within social networks,thereby affecting the accuracy of user *** address this challenge,we propose user geolocation methods that integrate neighborhood geographical distribution and social structure influence(NGSI)to improve geolocation ***,we propose a method for evaluating the homophily of locations based on the k-order neighbor-hood geographic distribution(k-NGD)similarity among *** are notable differences in the distribution of k-NGD similarity between location-proximate and non-location-proximate *** this distinction,we filter out non-location-proximate social relationships to enhance location homophily in the social *** better utilize the location-proximate relationships in social networks,we propose a graph neural network algorithm based on the social structure *** algorithm enables us to perform a weighted aggregation of the information of users’multi-hop neighborhood,thereby mitigating the over-smoothing problem of user features and improving user geolocation *** results on real social media dataset demonstrate that the neighborhood geographical distribution similarity metric can effectively filter out non-location-proximate social ***,compared with 7 existing social relationship-based user positioning methods,our proposed method can achieve multi-granularity user geolocation and improve the accuracy by 4.84%to 13.28%.

关键词： User geolocation social media neighborhood geographic distribution structure influence

Aircraft parameter estimation using a stacked long short-term memory network and Levenberg-Marquardt method

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Chinese Journal of Aeronautics 2024年第2期37卷 123-136页

作者： Zhe HUI Yinan KONG Weigang YAO Gang CHEN School of Aerospace Science and Technology Xidian UniversityXi’an 710071China Computation Aerodynamics Institution China Aerodynamics Research and Development CenterMianyang 621000China Faculty of computing Engineering and MediaDe Montfort UniversityLeicester LE19BHUnited Kingdom School of Aerospace Engineering Xi’an Jiaotong UniversityXi’an 710049China

To effectively estimate the unknown aerodynamic parameters from the aircraft’s flight data,this paper proposes a novel aerodynamic parameter estimation method incorporating a stacked Long Short-Term Memory(LSTM)network model and the Levenberg-Marquardt(LM)*** stacked LSTM network model was designed to realize the aircraft dynamics modeling by utilizing a frame of nonlinear functional mapping based entirely on the measured input-output data of the aircraft system without requiring explicit postulation of the *** LM method combines the already-trained LSTM network model to optimize the unknown aerodynamic *** proposed method is applied by using the real flight data,generated by ATTAS aircraft and a bio-inspired morphing Unmanned Aerial Vehicle(UAV).The investigation reveals that for the two different flight data,the designed stacked LSTM network structure can maintain the efficacy of the network prediction capability only by appropriately adjusting the dropout rates of its hidden layers without changing other network parameters(i.e.,the initial weights,initial biases,number of hidden cells,time-steps,learning rate,and number of training iterations).Besides,the proposed method’s effectiveness and potential are demonstrated by comparing the estimated results of the ATTAS aircraft or the bio-inspired morphing UAV with the corresponding reference values or wind-tunnel results.

关键词： Parameter estimation LSTM network model LM method Aerodynamic parameters Flight data Aircraft dynamics modeling Network prediction capability Network parameters

A prompt-based approach to adversarial example generation and robustness enhancement

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Frontiers of Computer Science 2024年第4期18卷 85-96页

作者： Yuting YANG Pei HUANG Juan CAO Jintao LI Yun LIN Feifei MA Key Lab of Intelligent Information Processing of Chinese Academy of Sciences(CAS) Institute of Computing TechnologyCASBeijing 100190China School of Computer Science and Technology University of Chinese Academy of SciencesBeijing 100049China Department of Computer Science Stanford UniversityCA 94305USA School of computing National University of SingaporeSingapore 119077Singapore laboratory of Parallel Software and Computational Science Institute of SoftwareChinese Academy of SciencesBeijing 100190China

Recent years have seen the wide application of natural language processing(NLP)models in crucial areas such as finance,medical treatment,and news media,raising concerns about the model robustness and *** find that prompt paradigm can probe special robust defects of pre-trained language *** prompt texts are first constructed for inputs and a pre-trained language model can generate adversarial examples for victim models via *** results show that prompt paradigm can efficiently generate more diverse adversarial examples besides synonym ***,we propose a novel robust training approach based on prompt paradigm which incorporates prompt texts as the alternatives to adversarial examples and enhances robustness under a lightweight minimax-style optimization *** on three real-world tasks and two deep neural models show that our approach can significantly improve the robustness of models to resist adversarial attacks.

关键词： robustness adversarial example prompt learning pre-trained language model

A hybrid memory architecture supporting fine-grained data migration

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Frontiers of Computer Science 2024年第2期18卷 31-41页

作者： Ye CHI Jianhui YUE Xiaofei LIAO Haikun LIU Hai JIN National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Department of Computer Science Michigan Technological UniversityMichigan 49931USA

Hybrid memory systems composed of dynamic random access memory(DRAM)and Non-volatile memory(NVM)often exploit page migration technologies to fully take the advantages of different memory *** previous proposals usually migrate data at a granularity of 4 KB pages,and thus waste memory bandwidth and DRAM *** this paper,we propose Mocha,a non-hierarchical architecture that organizes DRAM and NVM in a flat address space physically,but manages them in a cache/memory *** the commercial NVM device-Intel Optane DC Persistent Memory Modules(DCPMM)actually access the physical media at a granularity of 256 bytes(an Optane block),we manage the DRAM cache at the 256-byte size to adapt to this feature of *** design not only enables fine-grained data migration and management for the DRAM cache,but also avoids write amplification for Intel Optane *** also create an Indirect Address Cache(IAC)in Hybrid Memory Controller(HMC)and propose a reverse address mapping table in the DRAM to speed up address translation and cache ***,we exploit a utility-based caching mechanism to filter cold blocks in the NVM,and further improve the efficiency of the DRAM *** implement Mocha in an architectural *** results show that Mocha can improve application performance by 8.2%on average(up to 24.6%),reduce 6.9%energy consumption and 25.9%data migration traffic on average,compared with a typical hybrid memory architecture-HSCC.

关键词： non-volatile memory hybrid memory system data migration fine-grained caching

Spatial-temporal Patterns of Urban Parks' Effects on the Sentiments and Their Associated Factors Based on Social media Data——a Case Study in Beijing

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Journal of Geodesy and Geoinformation Science 2024年第2期 95-110页

作者： YUAN Yuting WANG Juan WEI Yali ZHU Yanrong SHI Changsheng MENG Bin College of Applied Arts and Science Beijing Union University laboratory of Urban Cultural Sensing & computing Beijing Union University Beijing Guohuan Environmental Technology Co. Ltd.

As the pivotal green space, urban parks play an important role in urban residents' daily activities. Thy can not only bring people physical health, but also can be more likely to elicit positive sentiment to those who visit ***, social media big data has provided new data sources for sentiment analysis. However, there was limited researches that explored the connection between urban parks and individual's sentiments. Therefore, this study firstly employed a pre-trained language model(BERT, Bidirectional Encoder Representations from Transformers)to calculate sentiment scores based on social media data. Secondly, this study analysed the relationship between urban parks and individual's sentiment from both spatial and temporal perspectives. Finally, by utilizing structural equation model(SEM), we identified 13 factors and analyzed its degree of the influence. The research findings are listed as below: 1 It confirmed that individuals generally experienced positive sentiment with high sentiment scores in the majority of urban parks; 2 The urban park type showed an influence on sentiment scores. In this study, higher sentiment scores observed in Eco-parks, comprehensive parks, and historical parks; 3 The urban parks level showed low impact on sentiment scores. With distinctions observed mainly at level-3 and level-4;4 Compared to internal factors in parks, the external infrastructure surround them exerted more significant impact on sentiment scores. For instance, number of bus and subway stations around urban parks led to higher sentiment scores, while scenic spots and restaurants had inverse result. This study provided a novel method to quantify the services of various urban parks, which can be served as inspiration for similar studies in other cities and countries, enhancing their park planning and management strategies.

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Two-dimensional magnetic materials for spintronic applications

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Nano Research 2024年第2期17卷 743-762页

作者： Shivam N.Kajale Jad Hanna Kyuho Jang Deblina Sarkar MIT media Lab Massachusetts Institute of TechnologyCambridgeMA 02139USA Department of Information Technology and Electrical Engineering ETH ZürichZürich8092Switzerland

Spintronic devices are driving new paradigms of bio-inspired,energy efficient computation like neuromorphic stochastic computing and in-memory *** have also emerged as key candidates for non-volatile memories for embedded systems as well as alternatives to persistent *** meet the growing demands from such diverse applications,there is need for innovation in materials and device designs which can be scaled and adapted according to the ***-dimensional(2D)magnetic materials address challenges facing bulk magnet systems by offering scalability while maintaining device integrity and allowing efficient control of *** this review,we highlight the progress made in experimental studies on 2D magnetic materials towards their integration into spintronic *** provide an account of the various relevant material discoveries,demonstrations of current and voltage-based control of magnetism and reported device systems,while also discussing the challenges and opportunities towards integration of 2D magnetic materials in commercial spintronic devices.

关键词： spintronics van der Waals magnetic tunnel junction(MTJ) spin-orbit torque magnetism

Generating diverse clothed 3D human animations via a generative model

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Computational Visual media 2024年第2期10卷 261-277页

作者： Min Shi Wenke Feng Lin Gao Dengming Zhu School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China Institute of computing Technology Chinese Academy of SciencesBeijing 100190China

Data-driven garment animation is a current topic of interest in the computer graphics *** approaches generally establish the mapping between a single human pose or a temporal pose sequence,and garment deformation,but it is difficult to quickly generate diverse clothed human *** address this problem with a method to automatically synthesize dressed human animations with temporal consistency from a specified human motion *** the heart of our method is a twostage ***,we first learn a latent space encoding the sequence-level distribution of human motions utilizing a transformer-based conditional variational autoencoder(Transformer-CVAE).Then a garment simulator synthesizes dynamic garment shapes using a transformer encoder-decoder *** the learned latent space comes from varied human motions,our method can generate a variety of styles of motions given a specific motion *** means of a novel beginning of sequence(BOS)learning strategy and a self-supervised refinement procedure,our garment simulator is capable of efficiently synthesizing garment deformation sequences corresponding to the generated human motions while maintaining temporal and spatial *** verify our ideas *** is the first generative model that directly dresses human animation.

关键词： Transformer garment animation conditional variational autoencoder(CVAE) computer graphics

media Power Measuring via Emotional Contagion

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Journal of Social computing 2024年第1期5卷 15-35页

作者： Xue Lin Hong Huang Zongya Li Hai Jin National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China School of Journalism Huazhong University of Science and TechnologyWuhan 430074China

media power,the impact that media have on public opinion and perspectives,plays a significant role in maintaining internal stability,exerting external influence,and shaping international dynamics for nations/***,prior research has primarily concentrated on news content and reporting time,resulting in limitations in evaluating media *** more accurately assess media power,we use news content,news reporting time,and news emotion simultaneously to explore the emotional contagion between *** use emotional contagion to measure the mutual influence between media and regard the media with greater impact as having stronger media *** propose a framework called Measuring media Power via Emotional Contagion(MMPEC)to capture emotional contagion among media,enabling a more accurate assessment of media power at the media and national/regional *** also interprets experimental results through correlation and causality analyses,ensuring *** analyses confirm the higher accuracy of MMPEC compared to other baseline models,as demonstrated in the context of COVID-19-related news,yielding compelling and interesting insights.

关键词： explainability media power emotional contagion