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3rd International Conference on Cyberspace data and Intelligence, Cyber DI 2019, and the International Conference on Cyber-Living, Cyber-Syndrome, and Cyber-Health, CyberLife 2019

作者： Zhao, Hui Liu, Xin Guo, Wenjie Gai, Keke Wang, Ying Educational Information Technology Laboratory Henan University KaifengHenan475004 China School of Software Henan University KaifengHenan475004 China School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China Henan Intelligent Data Processing Engineering Research Center KaifengHenan475004 China

ISBN: (纸本)9789811519215

With the rapid development of the Internet, online recruitment has gradually become a mainstream. In the process of obtaining the text of recruitment information, a large volume of texts are not part of recruitment information. Currently, common text categorization algorithms include k-Nearest Neighbor, Support Vector Machine (SVM) and Naive Bayes. In addition, there are numerous related technical terms in the recruitment information, which affects the accuracy of the ordinary Bayesian text categorization algorithm. However, there is not uniform format for the text information of recruitment. This paper improves the original Naive Bayes algorithm and proposes a Reinforcement Naive Bayes (R-NB) algorithm to enhance the accuracy of recruitment information categorization. Experiments have demonstrated that the improved algorithm has a higher categorization accuracy and practicability than the original algorithm. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Nearest neighbor search

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Towards adversarial patch analysis and certified defense against crowd counting

arXiv

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arXiv 2021年

作者： Wu, Qiming Zou, Zhikang Zhou, Pan Ye, Xiaoqing Wang, Binghui Li, Ang School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan China Baidu Inc. Shenzhen China The Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China Department of Computer Science Illinois Institute of Technology Chicago United States Department of Electrical and Computer Engineering Duke University Durham United States

Crowd counting has drawn much attention due to its importance in safety-critical surveillance systems. Especially, deep neural network (DNN) methods have significantly reduced estimation errors for crowd counting missions. Recent studies have demonstrated that DNNs are vulnerable to adversarial attacks, i.e., normal images with human-imperceptible perturbations could mislead DNNs to make false predictions. In this work, we propose a robust attack strategy called Adversarial Patch Attack with Momentum (APAM) to systematically evaluate the robustness of crowd counting models, where the attacker's goal is to create an adversarial perturbation that severely degrades their performances, thus leading to public safety accidents (e.g., stampede accidents). Especially, the proposed attack leverages the extreme-density background information of input images to generate robust adversarial patches via a series of transformations (e.g., interpolation, rotation, etc.). We observe that by perturbing less than 6% of image pixels, our attacks severely degrade the performance of crowd counting systems, both digitally and physically. To better enhance the adversarial robustness of crowd counting models, we propose the first regression model-based Randomized Ablation (RA), which is more sufficient than Adversarial Training (ADT) (Mean Absolute Error of RA is 5 lower than ADT on clean samples and 30 lower than ADT on adversarial examples). Extensive experiments on five crowd counting models demonstrate the effectiveness and generality of the proposed method. Copyright © 2021, The Authors. All rights reserved.

关键词： Network security

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Delay-Aware Cache-Enabled Cooperative D2D Transmission in Mobile Cellular Networks

Delay-Aware Cache-Enabled Cooperative D2D Transmission in Mo...

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IEEE Conference on Wireless Communications and Networking

作者： Nannan Zhang Wei Wang Ruining Lan Pan Zhou Aiping Huang Zhejiang Provincial Key Laboratory of Information Processing Communication and Networking College of Information Science and Electronic Engineering Zhejiang University Hangzhou China Huawei Technologies Co. Ltd. Shanghai China Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781728195056;9781728195063

By caching popular contents at edge nodes, the content can be delivered via device-to-device (D2D) communications to reduce the delay significantly. In this paper, we study cooperative content delivery from multiple edge nodes with duplicate caching, where the content caching and the cooperative transmission algorithms are designed jointly to minimize the average delay. Specifically, we decompose the delay optimization problem as short time-scale transmission subproblems for each time slot and a long time-scale caching master problem by primal decomposition. The transmission subproblem is modelled as a finite horizon Markov decision problem (MDP), and we propose a link selection algorithm based on the value function in the MDP model. For the caching master problem, we propose a caching algorithm by the simultaneous perturbation stochastic approximation (SPSA) method. Simulation results show that our proposed transmission and caching algorithms achieve lower delay than the conventional schemes.

关键词： Cellular networks Simulation Perturbation methods Conferences Performance gain Markov processes Approximation algorithms

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Diminished Mitigating Effect of Vegetation on Surface Urban Heat Islands in Large Cities

SSRN

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SSRN 2023年

作者： Deng, Xiangyi Yu, Wenping Shi, Jinan Huang, Yajun Li, Dandan He, Xuanwei Zhou, Wei Xie, Zunyi Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station School of Geographical Science Southwest University No. 2 Tiansheng Road Beibei District Chongqing400715 China Yibin Academy of Southwest University Sichuan Yibin644000 China Chongqing Engineering Research Center for Remote Sensing Big Data Application Southwest University Chongqing400715 China Software Engineering Institute Pass College of Chongqing Technology and Business University No. 593 Jiaotong Road Hechuan District Chongqing401520 China College of Geography and Environmental Science Henan University Kaifeng475004 China School of Environment The University of Queensland BrisbaneQLD4072 Australia

Given the increasing severity of the surface urban heat island (SUHI) phenomenon, urban residents face heightened heat stress. Consequently, mitigating the effects of SUHI becomes critically important to improve urban livability. Previous studies often overlooked the influence of city size on SUHI, focusing on the correlational between SUHI and drivers and sidelining the synergistic effects of multiple factors on SUHI. To address this issue, we introduced a novel method, "geographical convergent cross-mapping", coupled with the random forest and Shapley value theory. Our results indicated that: Globally, SUHI exhibited a decreasing trend during day and night, with significant spatiotemporal disparities, and in cities of varying sizes, the cooling capacity of vegetation for SUHI showed significant variation. Locally, in arid cities spanning 150-200 km², vegetation contributed to cooling SUHI by up to 61%, but this effect lessened in larger cities. Notably, in equatorial cities larger than 200 km², this capability dropped drastically during summer, from 49% to 7%. Long-term trends showed an increase in daytime SUHI in equatorial regions and large cities along the southeastern coasts of China and the United States. This study provides key insights for precise urban climate adaptation and sustainable planning in cities of different sizes. © 2023, The Authors. All rights reserved.

关键词： Vegetation

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Key Opinion Leaders: An Invisible Force in Digital Home Media 8

Key Opinion Leaders: An Invisible Force in Digital Home Medi...

引用

8th International Conference on Digital Home, ICDH 2020

作者： Wang, Yepeng Bai, Huifeng Li, Ji Wang, Ruomei Liverpool John Moores University Liverpool Business School Liverpool United Kingdom Guilin University of Electronic Technology School of Computer Science and Information Security Guilin Huigu Institute of Artificial Intelligence Industrial Technology Guilin China Sun Yat-Sen University National Engineering Research Center of Digital Life School of Data and Computer Science Guangdong China

ISBN: (纸本)9781728192345

With the process of home digitalization, short video media begins to infiltrate our daily living area. The key opinion leader, which indicates the person who is known as an influencer, is a modern concept in such short video media. In this paper, we analyze how KOLs appearing in the digital home media (Smart Tvs, phones and pads) affect the consumer goods marketing. Through the questionnaire, we show results of consumers' attitudes towards watching KOLs' short videos and their views of the future trends of KOL marketing. Also, this paper reveals that KOL marketing should be designed an appropriate management mechanism in order to control the actions of the KOLs. © 2020 IEEE.

关键词： Marketing

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A Survey for Large Language Models in Biomedicine

arXiv

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arXiv 2024年

作者： Wang, Chong Li, Mengyao He, Junjun Wang, Zhongruo Darzi, Erfan Chen, Zan Ye, Jin Li, Tianbin Su, Yanzhou Ke, Jing Qu, Kaili Li, Shuxin Yu, Yi Liò, Pietro Wang, Tianyun Wang, Yu Guang Shen, Yiqing School of Medical Engineering Xinxiang Medical University Xinxiang China Engineering Technology Research Center of Neurosense and Control of Henan Province Xinxiang China Henan International Joint Laboratory of Neural Information Analysis and Drug Intelligent Design Xinxiang China Shanghai AI Laboratory Shanghai China Amazon Palo AltoCA United States Boston Children's Hospital MA United States Harvard Medical School Harvard University MA United States Toursun Synbio Shanghai China Department of Data Science & AI Faculty of IT Monash University Melbourne Australia School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China School of Computer Science and Engineering University of New South Wales Sydney Australia Department of Computer Science and Technology University of Cambridge Cambridge United Kingdom School of Basic Medical Sciences Xinxiang Medical University Xinxiang China Institute of Natural Sciences Shanghai Jiao Tong University Shanghai China School of Mathematics and Statistics University of New South Wales Sydney Australia Department of Computer Science Johns Hopkins University MD United States

Recent breakthroughs in large language models (LLMs) offer unprecedented natural language understanding and generation capabilities. However, existing surveys on LLMs in biomedicine often focus on specific applications or model architectures, lacking a comprehensive analysis that integrates the latest advancements across various biomedical domains. This review, based on an analysis of 484 publications sourced from databases including PubMed, Web of Science, and arXiv, provides an in-depth examination of the current landscape, applications, challenges, and prospects of LLMs in biomedicine, distinguishing itself by focusing on the practical implications of these models in real-world biomedical contexts. Firstly, we explore the capabilities of LLMs in zero-shot learning across a broad spectrum of biomedical tasks, including diagnostic assistance, drug discovery, and personalized medicine, among others, with insights drawn from 137 key studies. Then, we discuss adaptation strategies of LLMs, including fine-tuning methods for both uni-modal and multi-modal LLMs to enhance their performance in specialized biomedical contexts where zero-shot fails to achieve, such as medical question answering and efficient processing of biomedical literature. Finally, we discuss the challenges that LLMs face in the biomedicine domain including data privacy concerns, limited model interpretability, issues with dataset quality, and ethics due to the sensitive nature of biomedical data, the need for highly reliable model outputs, and the ethical implications of deploying AI in healthcare. To address these challenges, we also identify future research directions of LLM in biomedicine including federated learning methods to preserve data privacy and integrating explainable AI methodologies to enhance the transparency of LLMs. As this field of LLM rapidly evolves, continued research and development are essential to fully harness the capabilities of LLMs in biomedicine while ensuring their respon

关键词： Federated learning

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Peripheral-free device pairing by randomly switching power

arXiv

引用

arXiv 2020年

作者： Shao, Zhijian Weng, Jian Zhang, Yue Wu, Yongdong Li, Ming Weng, Jiasi Luo, Weiqi Yu, Shui College of Informatin Science and Technology College of Cyber security National Joint Engineering Research Center of Network Security Detection and Protection Technology Guangdong Key Laboratory of Data Security and Privacy Preserving Jinan University Guangzhou510632 China University of Technology Sydney UltimoNSW Australia

The popularity of Internet-of-Things (IoT) comes with security concerns. Attacks against wireless communication venues of IoT (e.g., Man-in-the-Middle attacks) have grown at an alarming rate over the past decade. Pairing, which allows the establishment of the secure communicating channels for IoT devices without a prior relationship, is thus a paramount capability. Existing secure pairing protocols require auxiliary equipment/peripheral (e.g., displays, speakers and sensors) to achieve authentication, which is unacceptable for low-priced devices such as smart lamps. This paper studies how to design a peripheral-free secure pairing protocol. Concretely, we design the protocol, termed SwitchPairing, via out-of-box power supplying chargers and on-board clocks, achieving security and economics at the same time. When a user wants to pair two or more devices, he/she connects the pairing devices to the same power source, and presses/releases the switch on/off button several times. Then, the press and release timing can be used to derive symmetric keys. We implement a prototype via two CC2640R2F development boards from Texas Instruments (TI) due to its prevalence. Extensive experiments and user studies are also conducted to benchmark our protocol in terms of efficiency and security. Copyright © 2020, The Authors. All rights reserved.

关键词： Internet of things

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Improving preparation and luminescence properties of Eu and dy doped Sr2MgSi2O7 phosphors by adding excess silica

引用

Scientific reports 2025年第1期15卷 18367页

作者： Chi Zhang Liuming Wei Qin Liu Ruirui Cui Chaoyong Deng Jingyu Li College of Electrical Engineering Henan University of Technology Zhengzhou 450001 China. chizhang@***. Department of Network Security Henan Police College Zhengzhou 450046 China. Anqiu Qingyun Bilingual School Weifang China. Key Laboratory of Functional Composite Materials of Guizhou Province College of Big Data and Information Engineering Guizhou University Guiyang 550025 China. Key Laboratory of Functional Composite Materials of Guizhou Province College of Big Data and Information Engineering Guizhou University Guiyang 550025 China. cydeng@***. Spallation Neutron Source Science Center Dongguan 523803 China. ***@***.

Solid state reaction method is most commonly used to synthesize SrMgSiO: Eu, Dy phosphors. In order to avoid the energy waste caused by high sintering temperature, we systematically studied and optimized the preparation process of SrMgSiO: Eu, Dy long afterglow phosphors by increasing the Si/Sr ratio in the raw materials. The appropriate addition of silica not only facilitates the preparation of single phase SrMgSiO: Eu, Dy phosphor but also enhances the rate of solid state reaction, so as to achieve the purpose of reducing the sintering temperature. The photoluminescence performance of the sample with a Si/Sr ratio of 1.1 sintered at 1350 °C is the highest, followed by that of the sample sintered at 1400 °C with a Si/Sr ratio of 1.0. Notably, the photoluminescence properties of the Si/Sr ratio of 1.3 sample sintered at 1300 °C are comparable to those of the Si/Sr ratio of 1.0 sample sintered at 1400 °C. However, in terms of afterglow properties, the former exhibits an enhancement by a factor of 3.5 compared to the latter. This finding suggests that strategically increasing the Si/Sr ratio can reduce the sintering temperature by 100 °C while maintaining or even enhancing the luminescence and afterglow properties of the samples. Additionally, the electronic structures of the SrMgSiO host, the doped luminescence center Eu, the oxygen vacancies and the co-doped activator Dy have been methodically investigated through first-principles calculations. By integrating the findings on the distribution of the dopants and defects levels, we predict and propose the photoluminescence and afterglow mechanisms of SrMgSiO: Eu, Dy. These studies suggest an efficient, cheap and energy-saving strategy for the preparation of SrMgSiO: Eu, Dy long afterglow phosphor, and reveal the roles of oxygen vacancies and co-doped Dy in the afterglow luminescence.

关键词： Electron traps First-principles calculation Optimizing synthesis Persistent luminescence Sr2MgSi2O7

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A Dual-Band Tunable Electromagnetically Induced Transparency (EIT) Metamaterial Based on Vanadium Dioxide

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Photonics 2025年第5期12卷 463-463页

作者： Lei Zhu Shujie Wang Yun Wang Liang Dong Hailong Li Yiya Wang Xumin Ding Heilongjiang Key Laboratory of Big Data Network Security Detection and Analysis Qiqihar University Qiqihar 161006 China Communication and Electronics Engineering Institute Qiqihar University Qiqihar 161006 China School of Computer and Control Engineering Qiqihar University Qiqihar 161006 China Advanced Microscopy and Instrumentation Research Center Harbin Institute of Technology Harbin 150080 China

A dual-band tunable terahertz electromagnetically induced transparency (EIT) metamaterial is introduced. The EIT metamaterial consists of two rectangular split rings, two metal strips, and a patterned vanadium dioxide (VO2) located at the back. The rectangular split rings serve as the bright resonator to generate two resonance valleys at distinct frequencies. The metal strips act as the dark resonator and are indirectly activated via the coupling influence of the bright resonator. The EIT metamaterial’s response mechanism is analyzed via the field effect and the two-particle model, with theoretical fitting results showing strong agreement with the simulation results. Moreover, VO2’s conductivity is altered to dynamically control the EIT effect in both frequency bands. Two transparency windows, with modulation depths of 70% and 75%, are observed as the conductivity of VO2 decreases. Simultaneously, the simulation results reveal a favorable slow light effect, with group delays reaching 51 ps and 74 ps at the transparency windows. The proposed metamaterial holds considerable promise for future modulator, filter, and slow light device applications.

关键词： metamaterial electromagnetically induced transparency (EIT) effect vanadium dioxide (VO )

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The DUDFTO Attack: Towards Down-to-UP Timeout Probing and Dynamically Flow Table Overflowing in SDN

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IEEE Transactions on Network and Service Management 2025年

作者： Li, Jiasong Cui, Yunhe Chen, Yi Shen, Guowei Guo, Chun Qian, Qing Guizhou University State Key Laboratory of Public Big Data Engineering Research Center of Text Computing and Cognitive Intelligence Ministry of Education College of Computer Science and Technology Guizhou Provincial Characteristic Key Laboratory of Software Engineering and Information Security Guiyang550000 China Guizhou University of Finance and Economics School of Information Guiyang550000 China

As a new network structure, the decoupling of the control plane and forwarding plane makes Software-Defined Networking (SDN) widely used in large-scale network scenarios. However, the decoupling network architecture also brings new vulnerabilities. The flow table overflow attack is an attack strategy that can overwhelm SDN switches. Nevertheless, the existing flow table overflow attacks may fail in probing timeouts and match fields of flow entries, due to link failure, measurement of the round-trip time (RTT) of different packets, interference of hard-timeout and idle-timeout. Meanwhile, the stealthiness of the existing attacks may also reduce, as these attacks use fixed attack rate. To improve the timeout probing accuracy and the stealthiness of attack, a new flow table overflow attack strategy, DUDFTO, is proposed to accurately probe timeout settings and match fields, then stealthily overflow SDN flow tables. Firstly, it probes the match fields by measuring the one-sided transmission delay of the packets. After that, DUDFTO designs a down-to-up feedback-based timeout probing algorithm to eliminate the issues caused by high RTT, link failure, interference between hard-timeout and idle-timeout. Then, DUDFTO designs a dynamic attack packets sending algorithm to improve its stealthiness. Finally, DUDFTO probes the flow table state to stop sending new attack packets. The evaluation results demonstrate that DUDFTO outperforms the existing attacks in terms of match fields probing ability, timeout probing relative error, number of packet_in and flow_mod messages generated by the attack, rate distribution of packet_in and flow_mod messages generated during the attack, and number of detected attack packets. © 2004-2012 IEEE.

关键词： flow table overflow attack information probing SDN switchs

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