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Dynamics modeling and optimal control for multi-information diffusion in Social Internet of Things

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Digital Communications and Networks 2024年第3期10卷 655-665页

作者： Yaguang Lin Xiaoming Wang Liang Wang Pengfei Wan School of computer science Shaanxi Normal UniversityXi'an710119China

As an ingenious convergence between the Internet of Things and social networks,the Social Internet of Things(SIoT)can provide effective and intelligent information services and has become one of the main platforms for people to spread and share ***,SIoT is characterized by high openness and autonomy,multiple kinds of information can spread rapidly,freely and cooperatively in SIoT,which makes it challenging to accurately reveal the characteristics of the information diffusion process and effectively control its *** this end,with the aim of exploring multi-information cooperative diffusion processes in SIoT,we first develop a dynamics model for multi-information cooperative diffusion based on the system dynamics theory in this ***,the characteristics and laws of the dynamical evolution process of multi-information cooperative diffusion are theoretically investigated,and the diffusion trend is *** this basis,to further control the multi-information cooperative diffusion process efficiently,we propose two control strategies for information diffusion with control objectives,develop an optimal control system for the multi-information cooperative diffusion process,and propose the corresponding optimal control *** optimal solution distribution of the control strategy satisfying the control system constraints and the control budget constraints is solved using the optimal control ***,extensive simulation experiments based on real dataset from Twitter validate the correctness and effectiveness of the proposed model,strategy and method.

关键词： Social Internet of Things Information diffusion Dynamics modeling Trend prediction Optimal control

A Video Captioning Method by Semantic Topic-Guided Generation

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computers, Materials & Continua 2024年第1期78卷 1071-1093页

作者： Ou Ye Xinli Wei Zhenhua Yu Yan Fu Ying Yang College of computer science and Technology Xi’an University of Science and TechnologyXi’an710054China

In the video captioning methods based on an encoder-decoder,limited visual features are extracted by an encoder,and a natural sentence of the video content is generated using a ***,this kind ofmethod is dep.ndent on a single video input source and few visual labels,and there is a problem with semantic alignment between video contents and generated natural sentences,which are not suitable for accurately comprehending and describing the video *** address this issue,this paper proposes a video captioning method by semantic topic-guided ***,a 3D convolutional neural network is utilized to extract the spatiotemporal features of videos during the ***,the semantic topics of video data are extracted using the visual labels retrieved from similar video *** the decoding,a decoder is constructed by combining a novel Enhance-TopK sampling algorithm with a Generative Pre-trained Transformer-2 deep neural network,which decreases the influence of“deviation”in the semantic mapping process between videos and texts by jointly decoding a baseline and semantic topics of video *** this process,the designed Enhance-TopK sampling algorithm can alleviate a long-tail problem by dynamically adjusting the probability distribution of the predicted ***,the experiments are conducted on two publicly used Microsoft Research Video Description andMicrosoft Research-Video to Text *** experimental results demonstrate that the proposed method outperforms several state-of-art ***,the performance indicators Bilingual Evaluation Understudy,Metric for Evaluation of Translation with Explicit Ordering,Recall Oriented Understudy for Gisting Evaluation-longest common subsequence,and Consensus-based Image Description Evaluation of the proposed method are improved by 1.2%,0.1%,0.3%,and 2.4% on the Microsoft Research Video Description dataset,and 0.1%,1.0%,0.1%,and 2.8% on the Microsoft Research-Video to Text dataset

关键词： Video captioning encoder-decoder semantic topic jointly decoding Enhance-TopK sampling

Data-driven Distributionally Adjustable Robust Chance-constrained DG Capacity Assessment

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 115-127页

作者： Masoume Mahmoodi Seyyed Mahdi Noori Rahim Abadi Ahmad Attarha Paul Scott Lachlan Blackhall the College of Engineering and computer science The Australian National UniversityCanberraAustralia

Moving away from fossil fuels towards renewable sources requires system operators to determine the capacity of distribution systems to safely accommodate green and distributed generation(DG).However,the DG capacity of a distribution system is often underestimated due to either overly conservative electrical demand and DG output uncertainty modelling or neglecting the recourse capability of the available *** improve the accuracy of DG capacity assessment,this paper proposes a distributionally adjustable robust chance-constrained approach that utilises uncertainty information to reduce the conservativeness of conventional robust *** proposed approach also enables fast-acting devices such as inverters to adjust to the real-time realisation of uncertainty using the adjustable robust counterpart *** achieve a tractable formulation,we first define uncertain chance constraints through distributionally robust conditional value-at-risk(CVaR),which is then reformulated into convex quadratic *** subsequently solve the resulting large-scale,yet convex,model in a distributed fashion using the alternating direction method of multipliers(ADMM).Through numerical simulations,we demonstrate that the proposed approach outperforms the adjustable robust and conventional distributionally robust approaches by up to 15%and 40%,respectively,in terms of total installed DG capacity.

关键词： Distributed generation(DG)capacity assessment distributionally robust optimisation chance-constrained optimisation distribution system

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Identifying influential spreaders in complex networks based on density entropy and community structure

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Chinese Physics B 2024年第5期33卷 765-774页

作者：苏湛陈磊艾均郑雨语别娜 School of Optical-Electrical and computer Engineering University of Shanghai for Science and Technology

In recent years,exploring the relationship between community structure and node centrality in complex networks has gained significant attention from researchers,given its fundamental theoretical significance and practical *** address the impact of network communities on target nodes and effectively identify highly influential nodes with strong propagation capabilities,this paper proposes a novel influential spreaders identification algorithm based on density entropy and community structure(DECS).The proposed method initially integrates a community detection algorithm to obtain the community partition results of the *** then comprehensively considers the internal and external density entropies and degree centrality of the target node to evaluate its *** validation is conducted on eight networks of varying sizes through susceptible–infected–recovered(SIR)propagation experiments and network static attack *** experimental results demonstrate that the proposed method outperforms five other node centrality methods under the same comparative conditions,particularly in terms of information spreading capability,thereby enhancing the accurate identification of critical nodes in networks.

关键词： corrigendum electron impact ionization cross sections carbon monoxide

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Exploring a Promising Region and Enhancing Decision Space Diversity for Multimodal Multi-Objective Optimization

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Tsinghua science and Technology 2024年第2期29卷 325-342页

作者： Fei Ming Wenyin Gong School of computer science China University of GeosciencesWuhan 430074China

During the past decade,research efforts have been gradually directed to the widely existing yet less noticed multimodal multi-objective optimization problems(MMOPs)in the multi-objective optimization ***,researchers have begun to investigate enhancing the decision space diversity and preserving valuable dominated solutions to overcome the shortage caused by a preference for objective space ***,many existing methods still have limitations,such as giving unduly high priorities to convergence and insufficient ability to enhance decision space *** overcome these shortcomings,this article aims to explore a promising region(PR)and enhance the decision space diversity for handling *** traditional methods,we propose the use of non-dominated solutions to determine a limited region in the PR in the decision space,where the Pareto sets(PSs)are included,and explore this region to assist in solving ***,we develop a novel neighbor distance measure that is more suitable for the complex geometry of PSs in the decision space than the crowding *** on the above methods,we propose a novel dual-population-based coevolutionary *** studies on three benchmark test suites demonstrates that our proposed methods can achieve promising performance and versatility on different *** effectiveness of the proposed neighbor distance has also been justified through comparisons with crowding distance methods.

关键词： multimodal multi-objective optimization evolutionary algorithms promising region neighbor distance decision space coevolution

Unbalanced private set intersection with linear communication complexity

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science China(Information sciences) 2024年第3期67卷 79-93页

作者： Quanyu ZHAO Bingbing JIANG Yuan ZHANG Heng WANG Yunlong MAO Sheng ZHONG dep.rtment of computer science and Technology Nanjing University Purple Mountain Lab

The private set intersection(PSI) protocol allows two parties holding a set of integers to compute the intersection of their sets without revealing any additional information to each other. The unbalanced PSI schemes consider a specific setting where a client holds a small set of the size n and a server holds a much larger set of the size m(n ■ m). The communication overhead of state-of-the-art balanced PSI schemes is O(m + n) and the unbalanced PSI schemes are O(nlogm). In this paper, we propose a novel secure unbalanced PSI protocol based on a hash proof system. The communication complexity of our protocol grows only linearly with the size of the small set. In other words, our protocol achieves communication overhead of O(n). We test the performance on a personal computer(PC) machine with a local area network(LAN)setting for the network. The experimental results demonstrate that the client only takes 2.01 s of online computation, 4.27 MB of round trip communication to intersect 1600 pieces of 32-bit integers with 220pieces of 32-bit integers with the security parameter λ = 512. Our protocol is efficient and can be applied to resource-constrained devices, such as cell phones.

关键词： unbalanced private set intersection Hash proof system linear communication complexity small set resource-constrained devices

Self-Aligning Multi-Modal Transformer for Oropharyngeal Swab Point Localization

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Tsinghua science and Technology 2024年第4期29卷 1082-1091页

作者： Tianyu Liu Fuchun Sun dep.rtment of computer science and Technology Tsinghua UniversityBeijing 100083China

The oropharyngeal swabbing is a pre-diagnostic procedure used to test various respiratory diseases, including COVID and Influenza A (H1N1). To improve the testing efficiency of testing, a real-time, accurate, and robust sampling point localization algorithm is needed for robots. However, current solutions rely heavily on visual input, which is not reliable enough for large-scale dep.oyment. The transformer has significantly improved the performance of image-related tasks and challenged the dominance of traditional convolutional neural networks (CNNs) in the image field. Inspired by its success, we propose a novel self-aligning multi-modal transformer (SAMMT) to dynamically attend to different parts of unaligned feature maps, preventing information loss caused by perspective disparity and simplifying overall implementation. Unlike preexisting multi-modal transformers, our attention mechanism works in image space instead of embedding space, rendering the need for the sensor registration process obsolete. To facilitate the multi-modal task, we collected and annotate an oropharynx localization/segmentation dataset by trained medical personnel. This dataset is open-sourced and can be used for future multi-modal research. Our experiments show that our model improves the performance of the localization task by 4.2% compared to the pure visual model, and reduces the pixel-wise error rate of the segmentation task by 16.7% compared to the CNN baseline.

关键词： segmentation localization transformer multi-modal perception robotic perception

Total ionizing dose effect modeling method for CMOS digital-integrated circuit

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Nuclear science and Techniques 2024年第2期35卷 32-46页

作者： Bo Liang Jin-Hui Liu Xiao-Peng Zhang Gang Liu Wen-Dan Tan Xin-Dan Zhang School of computer science and Technology Xidian UniversityXi’an 710071China

Simulating the total ionizing dose(TID)of an electrical system using transistor-level models can be difficult and expensive,particularly for digital-integrated circuits(ICs).In this study,a method for modeling TID effects in complementary metaloxide semiconductor(CMOS)digital ICs based on the input/output buffer information specification(IBIS)was *** digital IC was first divided into three parts based on its internal structure:the input buffer,output buffer,and functional *** of these three parts was separately *** the IBIS model,the transistor V-I characteristic curves of the buffers were processed,and the physical parameters were extracted and modeled using *** the functional area,logic functions were modeled in VHDL according to the data sheet.A golden digital IC model was developed by combining the input buffer,output buffer,and functional area ***,the golden ratio was reconstructed based on TID experimental data,enabling the assessment of TID effects on the threshold voltage,carrier mobility,and time series of the digital *** experiments were conducted using a CMOS non-inverting multiplexer,NC7SZ157,and the results were compared with the simulation results,which showed that the relative errors were less than 2%at each dose *** confirms the practicality and accuracy of the proposed modeling *** TID effect model for digital ICs developed using this modeling technique includes both the logical function of the IC and changes in electrical properties and functional degradation impacted by TID,which has potential applications in the design of radiation-hardening tolerance in digital ICs.

关键词： CMOS digital-integrated circuit Total ionizing dose IBIS model Behavior-physical hybrid model Physical parameters

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Incorporating contextual evidence to improve implicit discourse relation recognition in Chinese

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Frontiers of computer science 2024年第3期18卷 91-104页

作者： Sheng XU Peifeng LI Qiaoming ZHU School of computer science and Technology Soochow UniversitySuzhou 215000China

The discourse analysis task,which focuses on understanding the semantics of long text spans,has received increasing attention in recent *** a critical component of discourse analysis,discourse relation recognition aims to identify the rhetorical relations between adjacent discourse units(e.g.,clauses,sentences,and sentence groups),called arguments,in a *** works focused on capturing the semantic interactions between arguments to recognize their discourse relations,ignoring important textual information in the surrounding ***,in many cases,more than capturing semantic interactions from the texts of the two arguments are needed to identify their rhetorical relations,requiring mining more contextual *** this paper,we propose a method to convert the RST-style discourse trees in the training set into dep.ndency-based trees and train a contextual evidence selector on these transformed *** this way,the selector can learn the ability to automatically pick critical textual information from the context(i.e.,as evidence)for arguments to assist in discriminating their *** we encode the arguments concatenated with corresponding evidence to obtain the enhanced argument ***,we combine original and enhanced argument representations to recognize their *** addition,we introduce auxiliary tasks to guide the training of the evidence selector to strengthen its selection *** experimental results on the Chinese CDTB dataset show that our method outperforms several state-of-the-art baselines in both micro and macro F1 scores.

关键词： discourse parsing discourse relation recognition contextual evidence selection