检索结果-内蒙古大学图书馆

24th IEEE International Conference on Communication technology, ICCT 2024

作者： Li, Dong Yan, Zhigang Hao, Yuyu Niyato, Dusit Quek, Tony Q. S. Macau University of Science and Technology School of Computer Science and Engineering Macau China Nanyang Technological University School of Computer Science and Engineering Singapore Singapore University of Technology and Design Information Systems Technology and Design Pillar Singapore

ISBN: (纸本)9798350363760

In Federated Learning (FL) for the low Earth orbit (LEO) satellite networks with parameters aggregated by a ground station, the communication overhead is a substantial concern. To circumvent this limitation and alleviate the latency within the FL for the satellite-ground communication, Decentralized Federated Learning (DFL) has appeared as an effective solution. However, considering the heterogeneity of satellites, the problem on how to efficiently leverage the limited resources available to enhance the model performance of DFL has drawn little attention, which motivates this work. Specifically, the proposed solution involves optimizing the number of local training rounds across diverse satellites with varying resource budgets to enhance the DFL performance by utilizing the resource more efficiently. Simulation results show that, the proposed scheme achieves a much better performance than the conventional schemes with fixed rounds of local training. © 2024 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Ozone-based advanced oxidation processes in water treatment: recent advances, challenges, and perspective

引用

Environmental science and Pollution Research 2025年第7期32卷 3531-3570页

作者： Mahmoodi, Mohammadreza Pishbin, Esmail Department of Civil Architectural and Environmental Engineering The University of Texas at Austin 2515 Speedway AustinTX78712 United States Bio-Microfluidics Lab Department of Electrical Engineering and Information Technology Iranian Research Organization for Science and Technology Tehran Iran

Water pollution, driven by a variety of enduring contaminants, poses considerable threats to ecosystems, human health, and biodiversity, highlighting the urgent need for innovative and sustainable treatment approaches. Ozone-based advanced oxidation processes (AOPs) have demonstrated significant efficacy in breaking down stubborn pollutants, such as organic micropollutants and pathogens, that are not easily addressed by traditional treatment techniques. This review offers an in-depth analysis of ozonation mechanisms, covering both the direct oxidation by ozone and the indirect reactions facilitated by hydroxyl radicals, emphasizing their effectiveness and adaptability across various wastewater matrices. Significant progress in the combination of ozonation with additional technologies, including UV irradiation, hydrogen peroxide (H₂O₂), catalytic systems, and biological treatments, is examined, highlighting their effectiveness in enhancing pollutant breakdown, increasing biodegradability, and reducing secondary pollution. Hybrid methods, including catalytic ozonation and ozone-biological treatment, show significant enhancements in process efficiency and cost-effectiveness, while effectively tackling challenges associated with energy use and byproduct generation. Despite the promising possibilities, obstacles remain, such as scalability issues, high operational costs, and the risk of generating potentially harmful transformation products. Cutting-edge approaches, including the creation of sophisticated catalysts, integration of processes, and refinement of reactor designs, are suggested to address these challenges and improve the real-world implementation of ozone-based advanced oxidation processes. This review highlights the significant potential of ozone-based advanced oxidation processes as sustainable approaches for wastewater treatment, providing an essential route to environmental conservation and safeguarding public health. © The Author(s), under exclusive lice

关键词： Ozonization

来源：评论

学校读者我要写书评

暂无评论

Privacy-Preserving Pseudonym Schemes for Personalized 3D Avatars in Mobile Social Metaverses 6

Privacy-Preserving Pseudonym Schemes for Personalized 3D Ava...

引用

6th International Conference on Electronics and Communication, Network and Computer technology, ECNCT 2024

作者： Su, Cheng Luo, Xiaofeng Liu, Zhenmou Kang, Jiawen Hao, Min Xiong, Zehui Yang, Zhaohui Huang, Chongwen School of Automation Guangdong University of Technology Guangzhou China School of Systems Science and Engineering Sun Yat-sen University Guangzhou510275 China Singapore University of Technology and Design Information Systems Technology and Design Pillar Singapore College of Information Science and Electronic Engineering Zhejiang University Hangzhou China

ISBN: (纸本)9798350366143

The emergence of mobile social metaverses, a novel paradigm bridging physical and virtual realms, has led to the widespread adoption of avatars as digital representations for Social Metaverse Users (SMUs) within virtual spaces. Equipped with immersive devices, SMUs leverage Edge Servers (ESs) to deploy their avatars and engage with other SMUs in virtual spaces. To enhance immersion, SMUs incline to opt for 3D avatars for social interactions. However, existing 3D avatars are typically generated through scanning the real faces of SMUs, which can raise concerns regarding information privacy and security, such as profile identity leakages. To tackle this, we introduce a new framework for personalized 3D avatar construction, leveraging a two-layer network model that provides SMUs with the option to customize their personal avatars for privacy preservation. Specifically, our approach introduces avatar pseudonyms to jointly safeguard the profile and digital identity privacy of the generated avatars. Then, we design a novel metric named Privacy of Personalized Avatars (PoPA), to evaluate effectiveness of the avatar pseudonyms. To optimize pseudonym resource, we model the pseudonym distribution process as a Stackelberg game and employ Deep Reinforcement Learning (DRL) to learn equilibrium strategies under incomplete information. Simulation results validate the efficacy and feasibility of our proposed schemes for mobile social metaverses. © 2024 IEEE.

关键词： Differential privacy

来源：评论

学校读者我要写书评

暂无评论

A Q-Learning Based Hybrid Meta-Heuristic for Integrated Scheduling of Disassembly and Reprocessing Processes Considering Product Structures and Stochasticity

引用

Complex System Modeling and Simulation 2024年第2期4卷 184-209页

作者： Fuquan Wang Yaping Fu Kaizhou Gao Yaoxin Wu Song Gao the School of Business Qingdao UniversityQingdao 266071China the Macao Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China the Department of Industrial Engineering&Innovation Sciences Eindhoven University of TechnologyEindhoven5600 MBthe Netherlands the College of Information Science and Engineering Northeastern UniversityShenyang 110819China

Remanufacturing is regarded as a sustainable manufacturing paradigm of energy conservation and environment *** improve the efficiency of the remanufacturing process,this work investigates an integrated scheduling problem for disassembly and reprocessing in a remanufacturing process,where product structures and uncertainty are taken into ***,a stochastic programming model is developed to minimize the maximum completion time(makespan).Second,a Q-learning based hybrid meta-heuristic(Q-HMH)is specially *** each iteration,a Q-learning method is employed to adaptively choose a premium algorithm from four candidate ones,including genetic algorithm(GA),artificial bee colony(ABC),shuffled frog-leaping algorithm(SFLA),and simulated annealing(SA)*** last,simulation experiments are carried out by using sixteen instances with different scales,and three state-of-the-art algorithms in literature and an exact solver CPLEX are chosen for *** analyzing the results with the average relative percentage deviation(RPD)metric,we find that Q-HMH outperforms its rivals by 9.79%-26.76%.The results and comparisons verify the excellent competitiveness of Q-HMH for solving the concerned problems.

关键词： remanufacturing scheduling disassembly reprocessing meta-heuristic Q-learning

来源：评论

学校读者我要写书评

暂无评论

Leveraging EfficientNetB3 in a Deep Learning Framework for High-Accuracy MRI Tumor Classification

引用

Computers, Materials & Continua 2024年第10期81卷 867-883页

作者： Mahesh Thyluru Ramakrishna Kuppusamy Pothanaicker Padma Selvaraj Surbhi Bhatia Khan Vinoth Kumar Venkatesan Saeed Alzahrani Mohammad Alojail Department of Computer Science&Engineering Faculty of Engineering and TechnologyJAIN(Deemed-to-be University)Bengaluru562112India School of Computer Science and Engineering VIT-AP UniversityAmaravati522241India Department of Computer Science&Technology Madanapalle Institute of Technology&ScienceMadanapalle517325India School of Science Engineering and EnvironmentUniversity of SalfordManchesterM54WTUK School of Computer Science Engineering&Information Systems(SCORE) Vellore Institute of Technology(VIT)Vellore632014India Management Information System Department College of Business AdministrationKing Saud UniversityRiyadh11531Saudi Arabia Adjunct Research Faculty Centre for Research Impact&OutcomeChitkara UniversityRajpuraPunjab140401India

Brain tumor is a global issue due to which several people suffer,and its early diagnosis can help in the treatment in a more efficient *** different types of brain tumors,including gliomas,meningiomas,pituitary tumors,as well as confirming the absence of tumors,poses a significant challenge using MRI *** approaches predominantly rely on traditional machine learning and basic deep learning methods for image *** methods often rely on manual feature extraction and basic convolutional neural networks(CNNs).The limitations include inadequate accuracy,poor generalization of new data,and limited ability to manage the high variability in MRI *** the EfficientNetB3 architecture,this study presents a groundbreaking approach in the computational engineering domain,enhancing MRI-based brain tumor *** approach highlights a major advancement in employing sophisticated machine learning techniques within Computer science and engineering,showcasing a highly accurate framework with significant potential for healthcare *** model achieves an outstanding 99%accuracy,exhibiting balanced precision,recall,and F1-scores across all tumor types,as detailed in the classification *** successful implementation demonstrates the model’s potential as an essential tool for diagnosing and classifying brain tumors,marking a notable improvement over current *** integration of such advanced computational techniques in medical diagnostics can significantly enhance accuracy and efficiency,paving the way for wider *** research highlights the revolutionary impact of deep learning technologies in improving diagnostic processes and patient outcomes in neuro-oncology.

关键词： Deep learning MRI brain tumor cassification EfficientNetB3 computational engineering healthcare technology artificial intelligence in medical imaging tumor segmentation neuro-oncology

来源：评论

学校读者我要写书评

暂无评论

Analysis of Network Resilience for Logical-Physical Dual-Layer Networks in Configuring Backup Paths 9

Analysis of Network Resilience for Logical-Physical Dual-Lay...

引用

9th International Conference on Big Data and information Analytics, BigDIA 2023

作者： Li, Zhe Long, Zhitao Yu, Zhuoting Diao, Boyang Liu, Jin National University of Defense Technology Science and Technology on Information Systems Engineering Laboratory Changsha China National University of Defense Technology College of Systems Engineering Changsha China

ISBN: (纸本)9798350330076

The logical-physical dual-layer network is standardized in this paper, and three attack modes-random attack, maximum betweenness attack, and minimum betweenness attack are used to simulate and analyze the network resilience of the logical-physical dual-layer network with backup path and without backup path. The variation curves of network load loss under various attack edges are derived through simulation analysis, and it is determined that setting up backup path can significantly increase network resilience. On the basis of this conclusion, the impact of different backup path stowage schemes on network resilience is further explored, and the network load configuration scheme is designed based on duplication degree and average path length. It is determined that the network resistance is inversely related to duplication degree and average path length under the simulation study of random attack technique. © 2023 IEEE.

关键词： Network layers

来源：评论

学校读者我要写书评

暂无评论

Adaptive Temporal Attention with Key-frame Loss for Speech Emotion Recognition 5

Adaptive Temporal Attention with Key-frame Loss for Speech E...

引用

5th International Seminar on Artificial Intelligence, Networking and information technology, AINIT 2024

作者： Chen, Jing Wang, Kejun Xu, Tao School of Information Engineering Jiaxing Nanhu University Jiaxing China School of Information Technology Beijing Institute of Technology Zhuhai Zhuhai China College of Intelligent Systems Science and Engineering Harbin Engineering University Harbin China

ISBN: (纸本)9798350385557

Speech emotion recognition has received growing attention to improving the user-friendly experience, but it is still a difficult challenge. That is mainly due to the problem of uneven distribution of emotional information in speech samples. The overall state label of a sample is not sufficient to fully describe each part of the sample. In other words, each part contributes differently to the overall recognition. In this paper, we build unidirectional and bidirectional temporal attention networks to enhance the ability to extract essential features, and build the key-frame loss function to make the attention weight closer to 0 and 1. The purpose of using the attention module and key-frame loss is to extract the information that is effective for classification and filter out the unimportant information. A large number of experiments were conducted on the IEMOCAP dataset to verify the effectiveness of the model and loss function. The experimental results show that under the combined effect of the attention model and the loss function, our method has achieved better performance than the existing methods, with a weighted accuracy of 59.15% and an unweighted accuracy of 60.87%. © 2024 IEEE.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

ATFS: A deep learning framework for angle transformation and face swapping of face de-identification

引用

Multimedia Tools and Applications 2024年第12期83卷 36797-36822页

作者： Tsai, Chwei-Shyong Wu, Hsien-Chu Chen, Wei-Ting Ying, Josh Jia-Ching Department of Management Information Systems National Chung Hsing University Taichung402 Taiwan Language Center National Chin-Yi University of Technology Taichung411 Taiwan Department of Computer Science and Information Engineering National Taichung University of Science and Technology Taichung404 Taiwan

This paper proposes an effective framework for improving angle transformation and face replacement. This ATFS framework aims to solve the image distortion caused by angled face swapping in face de-identification. In the ATFS framework, TransNet and SWGAN were proposed based on generative adversarial networks. When TransNet uses neural networks to reconstruct images, it combines the predicted facial points. As a result, Transnet can locate the target’s facial features and generate multi-angle transformed images to achieve angle transformation. The SWGAN applies a complicated neural network that combines residual operations and self-attention modules to extract the input image features and replace the face region of the input image with the target image to achieve face de-identification. Both TransNet and SWGAN adopt discriminators and various loss functions to train the neural network and accurately accelerate the training process. The experimental results show that the proposed method can maintain high-quality images and avoid image distortion during face swapping for image angle transformation compared to previously proposed methods. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2023.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Efficient 3D Hilbert Curve Encoding and Decoding Algorithms

引用

Chinese Journal of Electronics 2022年第2期31卷 277-284页

作者： JIA Lianyin LIANG Binbin LI Mengjuan LIU Yong CHEN Yinong DING Jiaman Faculty of Information Engineering and Automation Kunming University of Science and Technology Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and Technology Library Yunnan Normal University School of Information Science and Engineering Guangxi University for Nationalities School of Computing Informatics and Decision Systems Arizona State University

Hilbert curve describes a one-to-one mapping between multidimensional space and 1 D *** traditional 3D Hilbert encoding and decoding algorithms work on order-wise manner and are not aware of the difference between different input data and spend equivalent computing costs on them, thus resulting in a low efficiency. To solve this problem, in this paper we design efficient 3D state views for fast encoding and decoding. Based on the state views designed, a new encoding algorithm(JFK-3HE) and a new decoding algorithm(JFK-3HD) are proposed. JFK-3HE and JFK-3HD can avoid executing iteratively encoding or decoding each order by skipping the first 0 s in input data, thus decreasing the complexity and improving the efficiency. Experimental results show that JFK-3HE and JFK-3HD outperform the state-of-the-arts algorithms for both uniform and skew-distributed data.

关键词： order-wise manner multidimensional space encoding state-of-the-arts algorithms encoding algorithm parallel algorithms JFK-3HE statistical distributions decoding solid modelling design efficient 3D JFK-3HD traditional 3D Hilbert encoding equivalent computing costs different input data decoding algorithm Hilbert curve state views iterative methods

来源：评论

学校读者我要写书评

暂无评论

All-optically linearized silicon modulator with ultrahigh SFDR of 131 dB · Hz6/7

引用

Photonics Research 2025年第2期13卷 433-441页

作者： QIANG ZHANG QIKAI HUANG PENGHUI XIA YAN LI XINGYI JIANG SHUYUE ZHANG SHENGYU FANG JIANYI YANG HUI YU Zhejiang Lab Institute of Integrated Microelectronic Systems College of Information Science and Electronic Engineering Zhejiang University Faculty of Electrical Engineering and Computer Science Ningbo University

Integrated high-linearity modulators are crucial for high dynamic-range microwave photonic （MWP）systems. Conventional linearization schemes usually involve the fine tuning of radio-frequency （RF） power distribution, which is rather inconvenient for practical applications and can hardly be implemented on the integrated photonics chip. In this paper, we propose an elegant scheme to linearize a silicon-based modulator in which the active tuning of RF power is eliminated. The device consists of two carrier-depletion-based Mach–Zehnder modulators （MZMs）, which are connected in series by a 1×2 thermal optical switch （OS）.The OS is used to adjust the ratio between the modulation depths of the two sub-MZMs. Under a proper ratio, the complementary third-order intermodulation distortion （IMD3） of the two sub-MZMs can effectively cancel each other out. The measured spurious-free dynamic ranges for IMD3 are 131, 127, 118, 110,and 109 d B·Hz6∕7at frequencies of 1, 10, 20, 30, and 40 GHz, respectively, which represent the highest linearities ever reached by the integrated modulator chips on all available material platforms.

关键词： Effective refractive index Integrated photonics Lithium niobate Modulation transfer function Optical signals Silicon modulators

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：