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A Blockchain-Based Framework for Secure Storage and Sharing of Resumes

computers, Materials & Continua 2022年第9期72卷 5395-5413页

作者： Huanrong Tang Changlin Hu Tianming Liu Jianquan Ouyang Key Laboratory of Intelligent Computing and Information Processing Ministry of EducationComputer Science College of Xiangtan UniversityXiangtanHunan ProvinceChina Department of Computer Science The University of GeorgiaAthensGeorgiaUSA

In response to problems in the centralized storage of personal resumes on third-party recruitment platforms,such as inadequate privacy protection,inability of individuals to accurately authorize downloads,and inability to determine who downloaded the resume and when,this study proposes a blockchain-based framework for secure storage and sharing of *** can employ an authorized access mechanism to protect their privacy *** proposed framework uses smart contracts,interplanetary file system,symmetric encryption,and digital signatures to protect,verify,and share *** keys are split and stored in multiple depositories through secret-sharing technology to improve the security of these *** key escrow incentives are implemented using smart contracts to automatically verify the correctness of keys and encourage the active participation of honest key escrow *** framework combines blockchain and searchable symmetric encryption technology to realize multikeyword search using inverted indexing and Bloom filters and verify search results on the *** search service fees are charged through *** after the search results are verified can the search service provider obtain the search fee,thus ensuring fair and efficient search for encrypted *** framework is decentralized,secure,and tamper-evident,and achieves controlled sharing while protecting personal privacy and information security.

关键词： Resume blockchain interplanetary file system secret sharing searchable encryption

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Operator Placement for IoT Data Streaming Applications in Edge Computing Environment 22nd

Operator Placement for IoT Data Streaming Applications in ...

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22nd International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2022

作者： Chen, Sixin Tang, Bing Yang, Qing Liu, Yuanyuan School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan411201 China Hunan Key Laboratory for Service Computing and Novel Software Technology Hunan University of Science and Technology Xiangtan411201 China School of Information and Communication Engineering Guangzhou Maritime University Guangzhou510725 China

ISBN: (纸本)9783031226762

With the rapid development of IoT applications, how to process large and continuous data streams in real time for IoT applications has become a challenge in recent years. This paper presents a model to predict the Maximum Sustainable Throughput (MST) of data streaming applications at the edge, and then proposes GACP, a constraint programming-base operator placement strategy to maximize MST using the genetic algorithm. We evaluated the proposed operator placement strategy in terms of MST, the number of edge servers in usage, and the percentage of communications within edge servers. Experimental results show that compared with the existing heuristic algorithms, the proposed GACP strategy can achieve better MST, which is 2–5 times higher than existing algorithms. © 2023, Springer Nature Switzerland AG.

关键词： Edge computing

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Boosting high initial coulombic efficiency of hard carbon by in-situ electrochemical presodiation

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Journal of Energy Chemistry 2023年第2期77卷 310-316,I0008页

作者： Nannan Qin Yanyan Sun Chao Hu Sainan Liu Zhigao Luo Xinxin Cao Shuquan Liang Guozhao Fang School of Materials Science and Engineering Central South UniversityChangsha 410083HunanChina School of Minerals Processing and Bioengineering Central South UniversityChangsha 410083HunanChina College of Chemistry Xiangtan UniversityXiangtan 411105HunanChina Key Laboratory of Electronic Packaging and Advanced Functional Materials of Hunan Province Central South UniversityChangsha 410083HunanChina

Hard carbon(HC)is a promising anode material for sodium ion batteries(SIBs),whereas inferior initial coulombic efficiency(ICE)severely limits its practical *** the present work,we propose an in situ electrochemical presodiation approach to improve ICE by mixing sodium biphenyl(Na-Bp)dimethoxyethane(DME)solution with DME-based ether electrolyte.A solid electrolyte interface(SEI)could be formed beforehand on the HC electrode and Na^(+)was absorbed to nanopores and graphene stacks,compensating for the sodium loss and preventing electrolyte decomposition during the initial charge and discharge *** this way,the ICE of half-cells was increased to nearly 100%and that of full-cells from 45%to 96%with energy density from 132.9 to 230.5 W h kg^(-1).Our work provides an efficient and facile method for improving ICE,which can potentially promote the practical application of HCbased materials.

关键词： Hard carbon In situ presodiation Initial coulombic efficiency Solid electrolyte interface Sodium-ion batteries

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A Reverse Auction-Based Incentive Mechanism for Cost-Effective Data Collection in Mobile Crowdsensing 29

A Reverse Auction-Based Incentive Mechanism for Cost-Effecti...

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29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Zhang, MingHe Wang, BoTao Liu, Gang Huang, Jing Guilin University of Electronic Technology School of Computer Science and Information Security Guilin China Shanghai University School of Computer Engineering and Science Shanghai China Hunan University of Science and Technology School of Computer Science and Engineering Xiangtan China

ISBN: (纸本)9798350330717

Incentive mechanisms play a crucial role in mobile crowdsensing between mobile users, third-party platforms, and clients. However, existing mechanisms often do not sufficiently consider users' future potential and past contributions to data sharing when recruiting or retaining them. Moreover, few people consider that the client in this mechanism requires high-quality data collection for training artificial intelligence models. To solve these problems, this paper proposes an innovative mobile crowdsensing incentive mechanism based on reverse auctions. This mechanism not only attracts users who provide high-quality data but also helps the client collect an appropriate amount of cost-effective data for model training. This is achieved by setting prerequisites for the release of tasks by the platform, that is, only after the client's model training effect reaches a certain level of improvement, the platform can release new tasks for data collection. Additionally, when recruiting users to participate in auctions, the platform will selectively recruit based on their potential value to ensure high-quality data collection. In cases where users might consider leaving the platform, measures for retention will be implemented. This will involve offering rewards adjusted proportionally according to their potential and contribution value to encourage them to stay. The comprehensive simulation results demonstrate the effectiveness of this new mechanism, highlighting its superior performance over existing mechanisms. © 2023 IEEE.

关键词： data collection incentive mechanism Mobile crowdsensing reverse auction

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Deep Learning Emotion Recognition Method 10

Deep Learning Emotion Recognition Method

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10th IEEE International Conference on Cyber Security and Cloud Computing and 9th IEEE International Conference on Edge Computing and Scalable Cloud, CSCloud-EdgeCom 2023

作者： Xiao, Weidong Tan, Wenjin Xiong, Naixue Yang, Ce Chen, Lin Xie, Rui University of Technology Schoole of Software Engineering Xiamen Xiamen361024 China Hunan University of Science and Technology School of Computer Science and Engineering Xiangtan411201 China

ISBN: (纸本)9798350312461

Emotion recognition refers to the process of actively analyzing human emotions through computer technology, and it has become an important part of modern society. Traditional emotion recognition is mainly based on a single information source, such as text, speech, video, etc., from which emotional features are extracted for classification or regression to recognize human emotions. With the development of artificial intelligence technology, multimodal emotion recognition is gradually becoming widely used. It combines two or more types of information, such as text, speech, and visual information, in different ways to analyze emotions. Multimodal emotion recognition is far superior to a single modality in understanding emotions. This article mainly analyzes the technology of emotion analysis. Firstly, we introduce the basic concepts and research status of emotion recognition. Then, we introduce the main types of emotion recognition and describe various methods used in the process in detail. Finally, we discuss the challenges and future developments of emotion recognition. © 2023 IEEE.

关键词： Emotion Recognition

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A Real-time Execution System of Multimodal Transformer through PIM-GPU Collaboration 24

A Real-time Execution System of Multimodal Transformer throu...

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61st ACM/IEEE Design Automation Conference, DAC 2024

作者： Ji, Shengyi Liu, Chubo Ding, Yan Liao, Qing Tang, Zhuo College of Information Science and Engineering Hunan University Changsha China Department of Computer Science and Technology Harbin Institute of Technology Shenzhen China

ISBN: (纸本)9798400706011

Multimodal transformer excels in various applications, but faces great challenges such as high memory consumption and limited data reuse that hinder real-time performance. To address these issues, we propose a processing-in-memory (PIM)-GPU collaboration oriented compiler to accelerate the multimodal transformers. The PIM-GPU collaboration adapts well to multimodal transformers and significantly accelerates model inference. In addition, we introduce a tailored PIM allocation algorithm for variable-length inputs to further improve computation efficiency. Experimental results show that our scheme can achieve an average 15x end-to-end speedup. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Graphics processing unit

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In-situ self-templating synthesis of 3D hierarchical porous carbonsfrom oxygen-bridged porous organic polymers for highperformance supercapacitors

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Nano Research 2022年第9期15卷 7759-7768页

作者： Qi Xiong Bei Liu Yijiang Liu Pu Wang Hua Cheng Huaming Li Zhouguang Lu Mei Yang College of Chemistry Xiangtan UniversityXiangtan 411105China Key Laboratory of Polymeric Materials&Application Technology of Hunan Province Key Laboratory of Advanced Functional Polymeric Materialsof College of Hunan Provinceand Key Lab of Environment-Friendly Chemistry and Application in Ministry of EducationXiangtan UniversityXiangtan 411105China Department of Materials Science&Engineering Shenzhen Key Laboratory of Interfacial Science and Engineering of MaterialsSouthern Universityof Science and TechnologyShenzhen 518055China

It is a big challenge to well control the porous structure of carbon materials for supercapacitor ***,a simple in-situ self-templating strategy is developed to prepare three-dimensional(3D)hierarchical porous carbons with good combination of micro and meso-porous architecture derived from a new oxygen-bridged porous organic polymer(OPOP).The OPOP is produced by the condensation polymerization of cyanuric chloride and hydroquinone in NaOH ethanol solution and NaCl is in-situ formed as by-product that will serve as template to construct an interconnected 3D hierarchical porous architecture upon *** large interface pore architecture,and rich doping of N and O heteroatoms effectively promote the electrolyte accessibility and electronic conductivity,and provide abundant active sites for energy ***,the supercapacitors based on the optimized OPOP-800 sample display an energy density of 8.44 and 27.28 Wh·kg^(−1)in 6.0 M KOH and 1.0 M Na2SO4 electrolytes,*** capacitance retention is more than 94%after 10,000 ***,density functional theory(DFT)calculations have been employed to unveil the charge storage mechanism in the *** results presented in this job are inspiring in finely tuning the porous structure to optimize the supercapacitive performance of carbon materials.

关键词： in-situ self-templating porous organic polymer three-dimensional(3D)hierarchical porous carbons supercapacitors

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Speed limit effect during lane change in a two-lane lattice model under V2X environment

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Chinese Physics B 2024年第3期33卷 718-722页

作者：金灿彭光含聂方彦 College of Physical Science and Technology Guangxi Normal UniversityGuilin 541004China Guangxi Key Laboratory of Nuclear Physics and Technology Guangxi Normal UniversityGuilin 541004China Information and Modern Education Technology Center Hunan University of Arts and ScienceChangde 415000China Computer and Information Engineering College Guizhou University of CommerceGuiyang 550014China

Speed limit measures are ubiquitous due to the complexity of the road environment,which can be supplied with the help of vehicle to everything(V2X)communication ***,the influence of speed limit on traffic system will be investigated to construct a two-lane lattice model accounting for the speed limit effect during the lane change process under V2X ***,the stability condition and the mKdV equation are closely associated with the speed limit effect through theory ***,the evolution of density and hysteresis loop is simulated to demonstrate the positive role of the speed limit effect on traffic stability in the cases of strong reaction intensity and high limited speed.

关键词： traffic flow lattice model speed limit

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Dynamic mesophase transition induces anomalous suppressed and anisotropic phonon thermal transport

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npj Computational Materials 2024年第1期10卷 239-248页

作者： Linfeng Yu Kexin Dong Qi Yang Yi Zhang Zheyong Fan Xiong Zheng Huimin Wang Zhenzhen Qin Guangzhao Qin State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle College of Mechanical and Vehicle EngineeringHunan UniversityChangsha410082People’s Republic of China College of Physical Science and Technology Bohai UniversityJinzhou121013People’s Republic of China Hunan Key Laboratory for Micro-Nano Energy Materials&Device and School of Physics and Optoelectronics Xiangtan UniversityXiangtan411105 HunanChina School of Physics and Microelectronics Zhengzhou UniversityZhengzhou450001China Research Institute of Hunan University in Chongqing Chongqing401133China Greater Bay Area Institute for Innovation Hunan UniversityGuangzhou511300 Guangdong ProvinceChina

The physical/chemical properties undergo significant transformations in the different states arising from phase ***,due to the lack of a dynamic perspective,transitional mesophases are largely underexamined,constrained by the high resource burden of first ***,usingmolecular dynamics(MD)simulations empowered by the machine-learning potential,we proffer an innovative paradigm for phase transition:regulating the thermal transport properties via the transitional mesophase triggered by a uniaxial force *** investigate the mechanical,electrical,and thermal transport properties of the two-dimensional carbon allotrope of Janus-graphene with strain-engineered phase ***,we found that the transitional mesophase significantly suppresses the thermal conductivity and induces strong anisotropy near the phase transition *** machine-learning-driven MD simulations,we achieved highprecision atomic-level simulations of *** results show that thermal vibrationinduced intermediate amorphous or interfacial phases induce strong and anisotropic interfacial thermal *** investigation not only endows uswith a novel perspective onmesophases during phase transitions but also enhances our holistic comprehension of the evolution of material properties.

关键词： thermal transition transport

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Frequency Domain Feature Learning with Wavelet Transform for Image Translation 20th

Frequency Domain Feature Learning with Wavelet Transform fo...

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20th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2023

作者： Zhao, Huan Wang, Yujiang Li, Tingting Wang, Song Li, Lixuan Zha, Xupeng Zhang, Zixing College of Computer Science and Electronic Engineering Hunan University Changsha China

ISBN: (纸本)9789819970247

Image-to-image translation serves as an essential field of research in computer vision. Existing models frequently cause accidental distortion over non-target attributes, leading to overfitting of the generated image to the reference domain and poor visual quality. To address this problem, we propose Frequency Domain Feature Learning with Wavelet Transform, namely FDFL-WT, which with better non-target attributes retention and more precise image capture of style. This method utilizes the wavelet transform to capture the image’s approximation coefficients and diagonal coefficients, then we suggest wavelet reconstruction loss and wavelet translation loss. The former comprehensively records the context information of the source image to make the generated image realistic, whereas the latter improves the generator’s capacity to decouple attributes by assisting the model in efficiently retaining image content attributes. Experimental results on CelebA-HQ dataset indicate that FDFL-WT achieves about a 7.03 % performance improvement comparing with methods in the FID score of realism and disentanglement tests. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Wavelet transforms

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