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IEEE International Conference on Multimedia and Expo (ICME)

作者： Yiren Zhang Yuanwu Xu Mohan Chen Yuejie Zhang Rui Feng Shang Gao School of Computer Science Shanghai Key Laboratory of Intelligent Information Processing Shanghai Collaborative Innovation Center of Intelligent Visual Computing Fudan University School of Information Technology Deakin University

When a Pre-trained Language Model (PLM) is adopted in video grounding task, it usually acts as a text encoder without having its knowledge fully utilized. Also, there exists an inconsistency problem between the pre-training and downstream objectives. To solve the issues, we propose a new paradigm, named Span-based Prompt Tuning (SPTNet). It can convert the video grounding task into a cloze form. Specifically, a query is first changed into a form with mask token by a template, then the video and the query embeddings are integrated through a cross-modal transformer. The start and end points of the query matching time span are predicted with the embedding of the mask token. Experimental results on two public benchmarks ActivityNet Captions and Charades-STA show that our SPTNet achieves surpassing performance compared with state-of-the-art methods.

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Conditional Video-Text Reconstruction Network with Cauchy Mask for Weakly Supervised Temporal Sentence Grounding

Conditional Video-Text Reconstruction Network with Cauchy Ma...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Jueqi Wei Yuanwu Xu Mohan Chen Yuejie Zhang Rui Feng Shang Gao School of Computer Science Shanghai Key Laboratory of Intelligent Information Processing Shanghai Collaborative Innovation Center of Intelligent Visual Computing Fudan University School of Information Technology Deakin University

Temporal sentence grounding aims to detect the target segment most related to a given query in an untrimmed video. To alleviate the expensive annotation cost for temporal labels, researchers paid more attention to weakly supervised setting. Prior studies neglected the utilization of video representation reconstruction, which led to an unbalanced alignment learning. Moreover, they used different strategies to generate proposals which ignored the temporal structure in a query. In this paper, we propose a novel Conditional Video-Text Reconstruction Network (CVTRN). It supports conditional reconstruction of video and text representation. Specifically, video and text features are fused to compute semantic alignment, which is the condition of reconstruction. A new mask strategy for mask conditioned sentence reconstruction is also devised. This strategy focuses more on boundary regions than the widely used Gaussian mask in previous methods. Experimental results on two public benchmark datasets show that our CVTRN outperforms the state-of-the-art methods.

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Dynamic Regret with Unknown Delays

SSRN

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SSRN 2023年

作者： Wu, Ping Liu, Zhengyang Lu, Haolin Huang, Heyan School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications China

In this paper, we delve into the realm of delayed online convex optimization, addressing scenarios where unknown delays exist between the querying and revealing of feedback. Obtaining dynamic regret in this case poses challenges arising from the uncertainties associated with both comparator sequence and delay sequence. First, to handle the uncertainty of comparator sequence, we introduce an adaptive delayed algorithm, yielding an $\mathcal{O}(\max{\sqrt{(1+\Delta_T)D_T},(\hat{d}-1)\Delta_T})$ dynamic regret bound for arbitrary comparator sequences. Here, $\Delta_T$ represents the path-length of the comparator sequence, $\hat{d}$ denotes the maximum delay, and $D_T$ signifies the cumulative delay over the entire horizon. Our approach centers around employing a delayed meta algorithm to track parallel delayed expert algorithms with varying step sizes. To complement our theoretical analysis, we establish an $\Omega(\sqrt{(1+\Delta_T)D_T})$ lower bound. Furthermore, to address the uncertainty of delay sequence, we extend our adaptive algorithm to scenarios where the time horizon and cumulative delay are unknown, incorporating a delayed doubling trick tailored to the number of missing feedback instances, thereby achieving a comparable dynamic regret. Finally, numerical simulations are presented to validate the effectiveness of our proposed approach. © 2023, The Authors. All rights reserved.

关键词： Comparators (optical)

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An Auto-Parallel Method for Deep Learning Models Based on Genetic Algorithm 29

An Auto-Parallel Method for Deep Learning Models Based on Ge...

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

作者： Zeng, Yan Huang, Chengchuang Ni, Yijie Zhou, Chunbao Zhang, Jilin Wang, Jue Zhou, Mingyao Xue, Meiting Zhang, Yunquan Hangzhou Dianzi University School of Computer Science and Technology Hangzhou310018 China Ministry of Education Key Laboratory for Modeling and Simulation of Complex Systems Hangzhou310018 China Data Security Governance Zhejiang Engineering Research Center Hangzhou310018 China Hangzhou Dianzi University School of ITMO Joint Institute Hangzhou310018 China Institute of Computer Network Information Center of the Chinese Academy of Sciences Beijing100086 China HuaWei China Institute of Computing Technology of the Chinese Academy of Sciences State Key Laboratory of Computer Architecture Beijing100086 China

ISBN: (纸本)9798350330717

As the size of datasets and neural network models increases, automatic parallelization methods for models have become a research hotspot in recent years. The existing auto-parallel methods based on machine learning or graph algorithms still have issues with search efficiency and applicability. This paper proposes an automatic parallel method based on a dual-population genetic algorithm, TGA, which transforms model partitioning and placement into an integer linear programming problem and constructs a cost model to evaluate the solution. The solution space is built using the neural network's dataflow graph and device cluster's topology, and the dual-population genetic algorithm is used to search for the optimal model parallel strategy. Experiments with various models show that the proposed method can improve single-step execution time by up to 42% compared to the Baechi method and up to 37.7% compared to the Hierarchical method. © 2023 IEEE.

关键词： Auto-Parallel Distributed machine learning Genetic algorithm Integer linear programming Model parallelism

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GSLB: The Graph Structure Learning Benchmark 37

GSLB: The Graph Structure Learning Benchmark

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37th Conference on Neural Information Processing Systems, NeurIPS 2023

作者： Li, Zhixun Wang, Liang Sun, Xin Luo, Yifan Zhu, Yanqiao Chen, Dingshuo Luo, Yingtao Zhou, Xiangxin Liu, Qiang Wu, Shu Yu, Jeffrey Xu Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Hong Kong Center for Research on Intelligent Perception and Computing State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences China School of Artificial Intelligence University of Chinese Academy of Sciences China Department of Automation University of Science and Technology of China China School of Cyberspace Security Beijing University of Posts and Telecommunications China Department of Computer Science University of California Los Angeles United States Heinz College of Information Systems and Public Policy Machine Learning Department School of Computer Science Carnegie Mellon University United States

ISBN: (纸本)9781713899921

Graph Structure Learning (GSL) has recently garnered considerable attention due to its ability to optimize both the parameters of Graph Neural Networks (GNNs) and the computation graph structure simultaneously. Despite the proliferation of GSL methods developed in recent years, there is no standard experimental setting or fair comparison for performance evaluation, which creates a great obstacle to understanding the progress in this field. To fill this gap, we systematically analyze the performance of GSL in different scenarios and develop a comprehensive Graph Structure Learning Benchmark (GSLB) curated from 20 diverse graph datasets and 16 distinct GSL algorithms. Specifically, GSLB systematically investigates the characteristics of GSL in terms of three dimensions: effectiveness, robustness, and complexity. We comprehensively evaluate state-of-the-art GSL algorithms in node- and graph-level tasks, and analyze their performance in robust learning and model complexity. Further, to facilitate reproducible research, we have developed an easy-to-use library for training, evaluating, and visualizing different GSL methods. Empirical results of our extensive experiments demonstrate the ability of GSL and reveal its potential benefits on various downstream tasks, offering insights and opportunities for future research. The code of GSLB is available at: https://***/GSL-Benchmark/GSLB. © 2023 Neural information processing systems foundation. All rights reserved.

关键词： Graphic methods

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Saliency-based image correction for colorblind patients

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Computational Visual Media 2020年第2期6卷 169-189页

作者： Jinjiang Li Xiaomei Feng Hui Fan School of Computer Science and Technology Shandong Technology and Business UniversityYantai264005China Co-innovation Center of Shandong Colleges and Universities Future Intelligent ComputingYantai264005China

Improper functioning, or lack, of human cone cells leads to vision defects, making it impossible for affected persons to distinguish certain colors. Colorblind persons have color perception, but their ability to capture color information differs from that of normal people: colorblind and normal people perceive the same image differently. It is necessary to devise solutions to help persons with color blindness understand images and distinguish different colors. Most research on this subject is aimed at adjusting insensitive colors,enabling colorblind persons to better capture color information, but ignores the attention paid by colorblind persons to the salient areas of images. The areas of the image seen as salient by normal people generally differ from those seen by the colorblind. To provide the same saliency for colorblind persons and normal people, we propose a saliency-based image correction algorithm for color blindness. Adjusted colors in the adjusted image are harmonious and realistic, and the method is practical. Our experimental results show that this method effectively improves images, enabling the colorblind to see the same salient areas as normal people.

关键词： color vision colorblindness saliency color correction

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computing knots by quadratic and cubic polynomial curves

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Computational Visual Media 2020年第4期6卷 417-430页

作者： Fan Zhang Jinjiang Li Peiqiang Liu Hui Fan School of Computer Science and Technology Shandong Technology and Business UniversityYantai 264005China Co-Innovation Center of Shandong Colleges and Universities:Future Intelligent Computing Yantai 264005China

A new method is presented to determine parameter values(knot)for data points for curve and surface *** four adjacent data points,a quadratic polynomial curve can be determined uniquely if the four points form a convex *** the four data points do not form a convex polygon,a cubic polynomial curve with one degree of freedom is used to interpolate the four points,so that the interpolant has better shape,approximating the polygon formed by the four data *** degree of freedom is determined by minimizing the cubic coefficient of the cubic polynomial *** advantages of the new method are,firstly,the knots computed have quadratic polynomial precision,i.e.,if the data points are sampled from a quadratic polynomial curve,and the knots are used to construct a quadratic polynomial,it reproduces the original quadratic ***,the new method is affine invariant,which is significant,as most parameterization methods do not have this ***,it computes knots using a local *** show that curves constructed using knots computed by the new method have better interpolation precision than for existing methods.

关键词： knot interpolation polynomial curve affine invariant

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A dynamic platform for global pullorum disease and fowl typhoid

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Animal Diseases 2025年第1期5卷 113-123页

作者： Xiamei Kang Canghong Jin Pengkun Gu Song Wang Zhengjie Gao Chenyi Dai Xiao Zhou Abubakar Siddique Haiyang Zhou Linlin Huang Yan Li Min Yue Department of Veterinary Medicine Zhejiang University College of Animal SciencesHangzhou 310058China School of Computer and Computing Science Hangzhou City UniversityHangzhou 310015China Hainan Institute of Zhejiang University Sanya 572000China School of Life Science Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhou 310024China State Key Laboratory for Diagnosis and Treatment of Infectious Diseases National Clinical Research Center for Infectious DiseasesNational Medical Center for Infectious DiseasesThe First Affiliated HospitalCollege of MedicineZhejiang UniversityHangzhou 310003China Ningbo Academy of Agricultural Sciences Ningbo 315040China NewFit(Hangzhou)Information Technology Co. LtdHangzhou 310000China

Pullorum disease and fowl typhoid are caused by the Salmonella serovars Gallinarum biovars Pullorum and Gal-linarum,*** prevalence of these diseases varies across regions and is affected by different risk fac-tors that remain insufficiently *** fill this knowledge gap,we have compiled a global dataset for its prevalence,drawing upon a collection of literature from the last seven decades obtained from bilingual ***,a more interactive and dynamic platform is still needed for both academics and policymakers to improve biosecurity measures,limit disease transmission,and prevent future outbreaks at the global and local ***,we developed an advanced visualization platform to depict the prevalence of Salmonella Pullorum and Gallinarum,espe-cially in China,which is categorized by geographical region and temporal *** platform offers a user-friendly,efficient,and visually engaging tool to explore the prevalence of pullorum disease and fowl typhoid between 1945 and 2021 in different ***,this platform allows users to understand the influence of various fac-tors,such as breed,farm mode,economic usage and even the sex of the primary host,chickens,on the prevalence of this *** further provided a detailed overview of individual province within *** particular,by selecting two different provinces on the interface,users can quickly visualize and grasp the disparities in disease prevalence between the chosen *** interactive toolkit enables a dynamic exploration of the patterns and factors con-tributing to the prevalence of Salmonella Pullorum and *** interactive platform is freely available open source at http://139.9.85.208/.

关键词： Pullorum disease Fowl typhoid Interactive platform Prevalence prediction

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Feature Selection for Detecting ICMPv6-Based DDoS Attacks Using Binary Flower Pollination Algorithm

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computer Systems science & Engineering 2023年第10期47卷 553-574页

作者： Adnan Hasan Bdair Aighuraibawi Selvakumar Manickam Rosni Abdullah Zaid Abdi Alkareem Alyasseri Ayman Khallel Dilovan Asaad Zebari Hussam Mohammed Jasim Mazin Mohammed Abed Zainb Hussein Arif National Advanced IPv6 Centre(NAv6) Universiti Sains MalaysiaPenang11800Malaysia Baghdad College of Economic Sciences University BaghdadIraq School of Computer Sciences Universiti Sains MalaysPenang11800Malaysia Information Technology Research and Development Center University of KufaNajafIraq College of Engineering University of Warith Al-AnbiyaaKarbalaIraq Faculty of Computing and Informatics Universiti Malaysia SabahSabahMalaysia Business Administration College of Administration and Financial SciencesImam Ja’afar Al-Sadiq UniversityBaghdad10001Iraq College of Computer Science and Information Technology University of AnbarRamadi AnbarIraq Department of Computer Science College of ScienceNawroz UniversityDuhok42001Kurdistan RegionIraq

Internet Protocol version 6(IPv6)is the latest version of IP that goal to host 3.4×10^(38)unique IP addresses of devices in the ***6 has introduced new features like Neighbour Discovery Protocol(NDP)and Address Auto-configuration ***6 needed several protocols like the Address Auto-configuration Scheme and Internet Control Message Protocol(ICMPv6).IPv6 is vulnerable to numerous attacks like Denial of Service(DoS)and Distributed Denial of Service(DDoS)which is one of the most dangerous attacks executed through ICMPv6 messages that impose security and financial ***,an Intrusion Detection System(IDS)is a monitoring system of the security of a network that detects suspicious activities and deals with amassive amount of data comprised of repetitive and inappropriate features which affect the detection rate.A feature selection(FS)technique helps to reduce the computation time and complexity by selecting the optimum subset of *** paper proposes a method for detecting DDoS flooding attacks(FA)based on ICMPv6 messages using a Binary Flower PollinationAlgorithm(BFPA-FA).The proposed method(BFPA-FA)employs FS technology with a support vector machine(SVM)to identify the most relevant,influential ***,The ICMPv6-DDoS dataset was used to demonstrate the effectiveness of the proposed method through different attack *** results show that the proposed method BFPAFA achieved the best accuracy rate(97.96%)for the ICMPv6 DDoS detection with a reduced number of features(9)to half the total(19)*** proven proposed method BFPA-FAis effective in the ICMPv6 DDoS attacks via IDS.

关键词： IPv6 ICMPv6 DDoS feature selection flower pollination algorithm anomaly detection

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Natural Human Skin‑Inspired Wearable and Breathable Nanofiber‑based Sensors with Excellent Thermal Management Functionality

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Advanced Fiber Materials 2024年第6期6卷 1955-1968页

作者： Peng Wang Xiaodan Li Guifen Sun Guoqing Wang Qing Han Chuizhou Meng Zhonghe Wei Yang Li School of Mechanical Engineering University of JinanJinan 250022China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China State Key Laboratory for Reliability and Intelligence of Electrical Equipment Engineering Research Center of Ministry of Education for Intelligent Rehabilitation Device and Detection TechnologyHebei Key Laboratory of Smart Sensing and Human‑Robot InteractionSchool of Mechanical EngineeringHebei University of TechnologyTianjin 300401China Shandong Provincial Key Laboratory of Network‑Based Intelligent Computing School of Information Science and EngineeringUniversity of JinanJinan 250022China Network Information Center Department of Computer ScienceQilu University of Technology(Shandong Academy of Sciences)Jinan 250353China School of Integrated Circuits Shandong UniversityJinan 250101China

Wearable sensors have been rapidly developed for application in various human monitoring ***,the wearing comfort and thermal properties of these devices have been largely ignored,and these characteristics urgently need to be ***,we develop a wearable and breathable nanofiber-based sensor with excellent thermal management functionality based on passive heat preservation and active Joule heating *** multifunctional device consists of a micropatterned carbon nanotube(CNT)/thermoplastic polyurethane(TPU)nanofiber electrode,a microporous ionic aerogel electrolyte and a microstructured Ag/TPU nanofiber *** to the presence of a supercapacitive sensing mechanism and the appli-cation of microstructuration,the sensor shows excellent sensing performance,with a sensitivity of 24.62 ***,due to the overall porous structure and hydrophobicity of TPU,the sensor shows good breathability(62 mm/s)and water repellency,with a water contact angle of 151.2°.In addition,effective passive heat preservation is achieved by combining CNTs with high solar absorption rates(85%)as the top layer facing the outside,aerogel with a low thermal conductivity(0.063 W m-1 k-1)as the middle layer for thermal insulation,and Ag with a high infrared reflectance rate as the bottom layer facing the *** warming,this material yields a higher temperature than ***,the active Joule heat-ing effect is realized by applying current through the bottom resistive electrode,which can quickly increase the temperature to supply controlled warming on *** proposed wearable and breathable sensor with tunable thermal properties is promising for monitoring and heat therapy applications in cold environments.

关键词： Wearable sensor Breathable Personal thermal management Electrospun nanofibers Joule heating

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