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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Xiang, Ju Chen, Shengkai Wang, Lin-Cong-Hua Meng, Xiangmao Li, Min Changsha University of Science and Technology School of Computer and Communication Engineering Changsha China Central South University School of Computer Science and Engineering Changsha China Xiangtan University School of Computer Science Xiangtan China

ISBN: (纸本)9798350386226

Identifying disease-associated genes (DAGs) is important for the research of complex diseases, and network-based methods have been a powerful and elegant strategy for this topic. Genes and their products perform biological functions through synergy in biological networks, but mining useful information from the networks remains an open issue. Therefore, we propose a novel heterogeneous network impulsive dynamics model to identify DAGs more effectively. It inspires a heterogeneous network impulsive dynamical process by imposing impulsive signals at specific nodes, in an enhanced dual-layer heterogeneous network. Then, it extracts the impulsive dynamical signatures of responses of nodes to the impulsive signals so as to infer DAGs. A series of experiments confirm that this model has good performance of inferring DAGs under different conditions, and case studies further demonstrate its effectiveness. Furthermore, a user-friendly web platform is provided to facilitate prioritization and analysis of DAGs. It may become a useful tool for studying complex diseases and relevant genes. © 2024 IEEE.

关键词： Genome

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Automotive Lightweight Design Modeling And Intelligent Optimization Learn Key Technologies 10

Automotive Lightweight Design Modeling And Intelligent Optim...

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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： Xu, Gejing Liang, Wei Cai, Jiahong Xiao, Jiahong Chen, Xingyu Gong, Yinyan QuanZhou University Information Engineering Software College QuanZhou362000 China Hunan University of Science and Technology School of Computer Science and Engineering Xiangtan411201 China

ISBN: (纸本)9798350312461

The automotive industry has always been seeking innovative solutions to improve car performance, safety, and cost savings. Lightweight design technology has become one of the solutions. This article summarizes the modeling and optimization methods of automotive lightweight design, as well as key technologies based on intelligent optimization learning. First, this article outlines the basic concepts of automotive lightweight design, as well as the needs and challenges of the industry for lightweight design. Then, the modeling methods of lightweight design are introduced in detail, including geometric modeling, topology optimization, structural optimization, and multidisciplinary optimization. At the same time, commonly used materials, manufacturing processes, and testing methods in lightweight design are introduced, as well as relevant design guidelines and standards. This article also introduces some algorithms and their applicable scenarios. Additionally, this article summarizes the application prospects and future development directions of key technologies for automotive lightweight design modeling and intelligent optimization learning. We emphasize the opportunities and challenges in this field and propose how to continue promoting the development of lightweight design technology and responding to increasingly complex market demands. This article provides a systematic review of key technologies for automotive lightweight design modeling and intelligent optimization learning, which helps researchers and practitioners to deepen their understanding of the technical development and application trends in this field. © 2023 IEEE.

关键词： Automotive industry

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重金属污染与生态风险评价——基于自组织地图和正矩阵分解的临澧县土壤研究

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Journal of Central South university 2024年第4期31卷 1371-1382页

作者：邹昊李武清任伯帜谢青蔡昭奇陈禄源王瑾 School of Civil Engineering Hunan University of Science and TechnologyXiangtan 411201China Institute of Geological Survey of Hunan Province Changsha 410083China School of Resource Security Hunan University of Science and TechnologyXiangtan 411201China School of Earth Science and Spatial Information Hunan University of Science and TechnologyXiangtan 411201China College of Foreign Languages Hunan UniversityChangsha 410082China

土壤重金属污染一直是环境科学中备受关注的问题。本文对中国临澧县土壤中六种重金属(As、Cd、Cr、Cu、Zn和Pb)的污染水平、分布、来源及其对生态环境的影响进行了分析。样本浓度分析结果显示Cd的浓度均超过背景值,超标率达到100%,其余... 详细信息

土壤重金属污染一直是环境科学中备受关注的问题。本文对中国临澧县土壤中六种重金属(As、Cd、Cr、Cu、Zn和Pb)的污染水平、分布、来源及其对生态环境的影响进行了分析。样本浓度分析结果显示Cd的浓度均超过背景值,超标率达到100%,其余元素的平均浓度与背景值相近,超标率均在13.5%以下。地累计指数和富集因子指数均显示Cd是污染最严重的元素,其他元素则处于轻度污染级别以下。自组织地图(SOM)和正矩阵分解(PMF)的分析结果显示农业活动是土壤中重金属元素主要来源之一,而自然风化和工业污染也会导致土壤污染。Cd是临澧县土壤中污染最显著的元素,对生态环境造成的影响最大,达到较高风险等级。本研究为降低土壤重金属污染和生态环境风险提供了重要参考,同时也为相关部门制定有效的污染防治、生态环境保护政策提供了理论指导。

关键词：生态风险正矩阵分解重金属污染土壤自组织地图

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BFT Consensus Algorithms 10

BFT Consensus Algorithms

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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： Zhang, Xiaojun Zhong, Weiyu Yang, Ce Chen, Lin Liao, Jing Xiong, Naixue QuanZhou University of Information Engineering Software College QuanZhou362000 China Hunan University of Science and Technology School of Computer Science and Engineering Xiangtan411201 China

ISBN: (纸本)9798350312461

With the advent of Bitcoin, the blockchain as the underlying technology of Bitcoin has entered people's field of vision. In recent years, the blockchain and its related technologies have developed rapidly. The consensus algorithm is the key to the realization of blockchain technology. There will be Byzantine nodes in the process of reaching consensus among the nodes in the blockchain. Byzantine nodes are tolerated in the blockchain to achieve consensus. Consensus is an essential performance of consensus algorithms. This paper first introduces blockchain technology and the application of consensus algorithms in it;secondly, introduces the classic PBFT algorithm;then, introduces some existing consensus algorithms;finally summarizes the research status and challenges of consensus algorithms, and analyzes its Prospects. © 2023 IEEE.

关键词： Blockchain

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A Blockchain-empowered Federated Learning Framework Supprting GDPR-compliance 10

A Blockchain-empowered Federated Learning Framework Supprtin...

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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, Lijun Han, Dezhi Zhou, Sisi Xu, Nengxiang Chen, Lin Xie, Siqi College of Information Engineering Shanghai Maritime University Shanghai200135 China School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan411201 China

ISBN: (纸本)9798350312461

In recent years, data privacy security has been widely and highly valued by countries around the world. In the context of European Union's General Data Protection Regulation (GDPR), the regulatory requirements of laws and regulations are becoming increasingly strict, bringing huge impacts and challenges to enterprises with user's personal data such as internet services and financial technology. Up to a point, federal learning ensures data privacy by storing and processing personal data locally. However, due to malicious clients or central servers being able to launch attacks on global models or user privacy data, the security of federated learning is questioned, introducing blockchain into the federated learning framework is a feasible solution to address these data security issues. In this work, the concept of Blockchain (BC), Federated Learning (FL), GDPR and other similar data protection laws are presented, where a Blockchain-empowered Federated Learning (BC-empowered FL) framework is introduced. The challenges on complying with the GDPR are described, and the solutions or principles for improving the GDPR-compliance of BC-empowered FL systems are analyzed, sorting out the differences and connections among the GDPR-compliance methods yet laying a foundation to design legal and compliant applications for different domains and scenarios which need touch upon the user's personal data. © 2023 IEEE.

关键词： Data privacy

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3D Reconstruction From Traditional Methods to Deep Learning 10

3D Reconstruction From Traditional Methods to Deep Learning

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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： Yang, Lan Yang, Chaoyi Xie, Rui Liu, Jingnian Zhang, Huan Tan, Wenjin QuanZhou University of Information Engineering Software College QuanZhou362000 China School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan411201 China

ISBN: (纸本)9798350312461

Vision is one of the important pathways for human perception of external information, with over 80% of perception being acquired through vision. How to enable computers to possess efficient and flexible visual systems similar to humans has always been a hot topic in the field of computer science. One of the main goals of computer vision research is to reconstruct the geometric structure of 3D objects visible on the visible surfaces from 2D photos. Recently, this technology has become mature enough and its applications range from autonomous driving, virtual reality, cultural heritage preservation and restoration, among others, with significant research value. In this paper, we summarize the key technical issues in 3D reconstruction from existing technologies, first by summarizing traditional methods of 3D reconstruction, then analyzing commonly used deep learning methods for 3D reconstruction and their application scenarios in different fields. Finally, we conclude and provide an outlook on future development directions. © 2023 IEEE.

关键词： Deep learning

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ISAC-Fi: Enabling Full-Fledged Monostatic Sensing over Wi-Fi Communication

IEEE Journal of Selected Areas in Sensors

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IEEE Journal of Selected Areas in Sensors 2024年 1卷 139-153页

作者： Chen, Zhe Hu, Chao Zheng, Tianyue Cao, Hangcheng Yang, Yanbing Chu, Yen Jiang, Hongbo Luo, Jun Fudan University Institute of Space Internet School of Computer Science Shanghai200437 China Sichuan University College of Computer Science Chengdu610017 China Nanyang Technological University School of Computer Science and Engineering Singapore639798 Singapore Hunan University College of Computer Science and Electronics Engineering Changsha410012 China University of Electronic Science and Technology of China Chengdu610054 China

Although Wi-Fi communications have been exploited for sensing purpose for over a decade, the bistatic or multistatic nature of Wi-Fi still poses multiple challenges, hampering real-life deployment of integrated sensing and communication (ISAC) within the Wi-Fi framework. In this article, we aim to redesign Wi-Fi so that monostatic sensing (mimicking radar) can be achieved over the multistatic communication infrastructure. Specifically, we propose, design, and implement ISAC-Fi as an ISAC-ready Wi-Fi prototype. We first present a novel self-interference cancellation scheme, in order to extract reflected (radio frequency) signals for sensing purpose in the face of transmissions. We then subtly revise the existing Wi-Fi framework so as to seamlessly operate monostatic sensing under the Wi-Fi communication standard. Finally, we offer two ISAC-Fi designs: 1) a Universal Software Radio Peripheral (USRP)-based design emulates a totally redesigned ISAC-Fi device and 2) another plug-and-play design allows for backward compatibility by attaching an extra module to an arbitrary Wi-Fi device. We perform extensive experiments to validate the efficacy of ISAC-Fi and also to demonstrate its superiority over existing Wi-Fi sensing proposals. © 2024 IEEE.

关键词： Wi-Fi

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Revealing alkali metal ions transport mechanism in the atomic channels of Au@a-MnO_(2)

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Journal of Energy Chemistry 2023年第7期82卷 350-358,I0008页

作者： Jingzhao Chen Yong Su Hongjun Ye Yushu Tang Jitong Yan Zhiying Gao Dingding Zhu Jingming Yao Xuedong Zhang Tingting Yang Baiyu Guo Hui Li Qiushi Dai Yali Liang Jun Ma Bo Wang Haiming Sun Qiunan Liu Jing Wang Congcong Du Liqiang Zhang Yongfu Tang Jianyu Huang Clean Nano Energy Center State Key Laboratory of Metastable Materials Science and TechnologyYanshan UniversityQinhuangdao 066004HebeiChina School of Materials Science and Engineering Xiangtan UniversityXiangtan 411105HunanChina Hebei Key Laboratory of Applied Chemistry College of Environmental and Chemical EngineeringYanshan UniversityQinhuangdao 066004HebeiChina

Understanding alkali metal ions’(e.g.,Li^(+)/Na^(+)/K^(+))transport mechanism is challenging but critical to improving the performance of alkali metal *** using a-MnO_(2)nanowires as cathodes,the transport kinetics of Li^(+)/Na^(+)/K^(+)in the 2×2 channels of a-MnO_(2)with a growth direction of[001]is *** show that ion radius plays a decisive role in determining the ion transport and *** of the ion radii,Li^(+)/Na^(+)/K^(+)can all go through the 2×2 channels of a-MnO_(2),generating large stress and causing channel merging or ***,smaller ions such as Li^(+)and Na^(+)cannot only transport along the[001]direction but also migrate along the<110>direction to the nanowire surface;for large ion such as K^(+),diffusion along the<110>direction is *** different ion transport behavior has grand consequences in the electrochemistry of metal oxygen batteries(MOBs).For Li-O_(2)battery,Li^(+)transports uniformly to the nanowire surface,forming a uniform layer of oxide;Na^(+)also transports to the nanowire surface but may be clogged locally due to its larger radius,therefore sporadic pearl-like oxides form on the nanowire surface;K^(+)cannot transport to the nanowire surface due to its large radius,instead,it breaks the nanowire locally,causing local deposition of potassium *** study provides atomic scale understanding of the alkali metal ion transport mechanism which may be harnessed to improve the performance of MOBs.

关键词： Ion transport In-situ TEM STEM Metal oxygen batteries Metal ion batteries

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Speech Emotion Recognition based on Semi-Supervised Adversarial Variational Autoencoder 10

Speech Emotion Recognition based on Semi-Supervised Adversar...

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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, Yufeng Bo, Yuqin Zheng, Zhiling Hunan University of Science and Technology School of Computer Science and Engineering Xiangtan China Hunan Industry Polytechnic Information Center Changsha China

ISBN: (纸本)9798350312461

The application of semi-supervised learning in the field of speech emotion recognition can alleviate the problem of dependence on the amount of labeled data. Its core assumption is that the labeled and unlabeled data have the same feature representations, which determine the performance of the models. Therefore, this paper proposes a novel speech emotion recognition model based on semi-supervised adversarial variational autoencoding (SSAVAE), which reaps the advantages of generative adversarial network(GAN) and variational autoencoding(VAE) to learn the distribution of input data in the feature space. On the one hand, it can overcome the disturbance of the input data through learning the distribution of the input data in the feature space. On the other hand, it can approximate arbitrary feature distribution by introducing GAN. Concretely, SSAVAE considers the unlabeled data as the problem of the lack of emotional label attributes. The labeled data share the category information with the unlabeled data in the feature space. Several experiments are conducted on the FAU Aibo dataset to evaluate the effectiveness of the algorithm. The results show that the proposed method is superior to other benchmark algorithms and has strong feature learning capabilities. © 2023 IEEE.

关键词： Emotion Recognition

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CRT-Paillier Homomorphic Privacy Protection Scheme Based on BLS Signatures in Mobile Vehicular Networks 17

CRT-Paillier Homomorphic Privacy Protection Scheme Based on ...

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IEEE Congress on Cybermatics: 17th IEEE International Conference on Internet of Things, iThings 2024, 20th IEEE International Conference on Green Computing and Communications, GreenCom 2024, 17th IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2024, 10th IEEE International Conference on Smart Data, SmartData 2024

作者： Zhou, Yuquan Huang, Hejin Liao, Wenyu Liu, Jiyan Ying, Xiangdong Zhang, Chen Luo, Entao Hunan University of Science and Engineering Yongzhou China Xiangtan University Xiangtan China Hunan University of Technology and Business Changsha China Guangdong University of Technology Guangzhou China

ISBN: (纸本)9798350351637

Vehicular Ad-hoc Networks (VANETs) serve as an integral component within Intelligent Transportation Systems (ITS), designed to augment traffic fluidity and ensure a secure, comfortable driving environment for both drivers and passengers. In this system, real-time data exchange between vehicles, Road Side Units (RSUs), and other infrastructure is essential. However, this process can potentially lead to serious data privacy issues due to the large-scale data exchange. This paper proposes an edge-assisted homomorphic privacy protection scheme in VANETs, based on BLS signatures for homomorphic authentication and group signatures to address the conflicting requirements of participant identity verification and anonymity. By utilizing the Chinese Remainder Theorem (CRT)-optimized Paillier encryption algorithm, it allows for homomorphic addition operations on encrypted data, aiming to support secure data aggregation in ciphertext states while ensuring data transmission and aggregation security. The incorporation of CRT decomposes the modulo operation in the Paillier algorithm into operations with smaller moduli, further enhancing the efficiency of the Paillier algorithm in handling large-scale datasets, and reducing computational complexity and time costs. Experimental results demonstrate that with a global precision of 1024 bits in gmpy2, for a 2048-bit key length CRT-Paillier encryption algorithm, the encryption time is 91.30 ms, and the decryption time is 9.96 ms. The proposed scheme significantly enhances data security and operational efficiency within the VANET domain. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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