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31st International Conference on Computational Linguistics, COLING 2025

作者： Liu, Xinjing Li, Ruifan Ye, Shuqin Zhang, Guangwei Wang, Xiaojie School of Artificial Intelligence Beijing University of Posts and Telecommunications China School of Computer Science Beijing University of Posts and Telecommunications China Engineering Research Center of Information Networks Ministry of Education China Key Laboratory of Interactive Technology and Experience System Ministry of Culture and Tourism China

ISBN: (纸本)9798891761964

Multimodal Aspect-Based Sentiment Analysis (MABSA) aims to extract aspect terms from text-image pairs and identify their sentiments. Previous methods are based on the premise that the image contains the objects referred by the aspects within the text. However, this condition cannot always be met, resulting in a suboptimal performance. In this paper, we propose COnditional Relation based Sentiment Analysis framework (CORSA). Specifically, we design a conditional relation detector (CRD) to mitigate the impact of the unmet conditional image. Moreover, we design a visual object localizer (VOL) to locate the exact condition-related visual regions associated with the aspects. With CRD and VOL, our CORSA framework takes a multi-task form. In addition, to effectively learn CORSA we conduct two types of annotations. One is the conditional relation using a pretrained referring expression comprehension model;the other is the bounding boxes of visual objects by a pretrained object detection model. Experiments on our built C-MABSA dataset show that CORSA consistently outperforms existing methods. The code and data are available at https://***/Liuxj-Anya/CORSA. © 2025 Association for Computational Linguistics.

关键词： Computational linguistics

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Performance degradation/failure detection on a Independent Cart system using ANN

Performance degradation/failure detection on a Independent C...

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IEEE National Conference on Aerospace and Electronics (NAECON)

作者： Rahul Sharma Francis Wolff Chris Papachristou Electrical Computer and System Engineering Case Western Reserve University Case School of Engineering Cleveland OH USA

ISBN: (数字)9798350367621

ISBN: (纸本)9798350367638

Asset management is a critical area of machine management and maintenance, especially in areas where the cost of asset failure is extremely high and sometimes dangerous. This work explores the use of Artificial Neural Network (ANN) in identifying a mover in independent cart system (ICT) technology, irrespective of the identification assigned to the mover at power up time, and also identify the mover that is having degraded performance, in real-time. With the training data that mimics degraded characteristics of a mover, possibly also predict the cause of degradation of performance/failure, and a time window in which corrective action would be needed on the mover.

关键词： Degradation Training Analytical models Tracking Training data Artificial neural networks Predictive models

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An NTT/INTT Accelerator with Ultra-High Throughput and Area Efficiency for FHE 24

An NTT/INTT Accelerator with Ultra-High Throughput and Area ...

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61st ACM/IEEE Design Automation Conference, DAC 2024

作者： Lu, Zhaojun Yu, Weizong Xu, Peng Wang, Wei Zhang, Jiliang Feng, Dengguo Hubei Key Laboratory of Distributed System Security School of Cyber Science and Engineering Hust Wuhan JinYinHu Laboratory Hubei Wuhan China School of Cyber Science and Engineering Hust Hubei Wuhan China School of Computer Science and Technology Hust Hubei Wuhan China Hnu Hunan Changsha China State Key Laboratory of Cryptology Beijing China

ISBN: (纸本)9798400706011

As a core arithmetic operation and security guarantee of Fully Homomorphic Encryption (FHE), Number Theoretic Transform (NTT) of a large degree is the primary source of computational and time overhead. In this paper, we propose a scalable and conflict-free memory mapping algorithm that breaks the memory bound and releases a large amount of on-chip resources. A flexible and no-stall hardware/software pipeline architecture is designed to boost the throughput of NTT/INTT of N = 216 to over 48,543 operations per second with area efficiency, which 4× and 10× speed up the FPGA-based (HPCA'23) and GPU-based (HPCA'23) schemes. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Memory architecture

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Exploring Low Rate Dos Attack Detection Methods: A Bibliometric Analysis and Roadmap for Further Research

Exploring Low Rate Dos Attack Detection Methods: A Bibliomet...

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2023 IEEE International Conference on Data and Software engineering, ICoDSE 2023

作者： Widodo, Anteng Rochim, Adian Fatchur Warsito, Budi School of Postgraduated Studies Diponegoro University Doctoral Program of Information System Semarang Indonesia Muria Kudus University Faculty of Engineering Department of Information System Kudus Indonesia Diponegoro University Faculty of Engineering Department of Computer Engineering Semarang Indonesia Diponegoro University Faculty of Science and Mathematics Department of Statistics Semarang Indonesia

ISBN: (纸本)9798350381382

Low-Rate Denial of Service (LDoS) attacks, an emerging breed of DoS attacks, present a formidable challenge in terms of their detectability. Within the realm of network security, these attacks cast a substantial shadow over the availability and integrity of services. This study seeks to delve into the intricate mechanics of LDoS attacks and explore the landscape of developed detection methodologies. Employing bibliometric analysis, we employ a multifaceted approach to gather research insights pertaining to LDoS attack detection. This approach encompasses the examination of evolving research trends, scrutiny of widely cited scientific publications within the same domain, identification of prolific researchers shaping the field, and a judicious selection of reputable publishers for dependable information acquisition. Furthermore, our study undertakes a meticulous categorization and classification of previously proposed LDoS detection methods documented in well-established scientific literature. This endeavor not only provides a more profound comprehension of the evolutionary trajectory and thematic thrusts within LDoS attack detection research, but it also facilitates the identification of gaps and directions for future exploration. The culmination of these analytical efforts culminates in a comprehensive framework. This contribution manifests through structured categorization, classification, and a forward-looking research roadmap, which collectively serve as valuable tools for both current and aspiring researchers engaged in LDoS attack detection. In summary, this research not only delves into the complexities of LDoS attacks and their mechanisms but also augments the current understanding of detection capabilities. Through its nuanced contributions, this paper extends a helpful guide to the dynamic realm of LDoS attack detection, thus catalyzing advancements and insights for the future. copy;2023 IEEE. © 2023 IEEE.

关键词： Denial-of-service attack

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Range-angle Imaging Based on the Prior of Target Scattering Characteristics in Distributed Arrays 2

Range-angle Imaging Based on the Prior of Target Scattering ...

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2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024

作者： Mei, Yongjie Zhang, Guangbin Huang, Tianyao Wang, Yan Beijng Institute of Technology School of Information and Electronics Beijing China Yangtze Delta Region Academy Beijing Institute of Technology Radar System and Intelligent Signal Processing Jiaxing China University of Science and Technology Beijing School of Computer and Communication Engineering Beijing China

ISBN: (纸本)9798331515669

We consider the problem of target range-angle imaging using distributed arrays. High resolution imaging requires a large array aperture. However, due to the limited number of array elements, the subarrays are usually sparsely located, which results in severe under-sampling and ambiguity problem, degrading the imaging performance. To this end, we propose a range-angle imaging method based on the prior of target scattering characteristic to resolve the ambiguity. The main idea is to use the information increment of priors to reduce the dependence on the measurements. Particularly, we first statistically extract the prior distribution of target scattering intensity by data analysis on the target images. Then we use these priors to design weighting parameters and achieve the ambiguity-free images by solving a weighted sparse recovery problem. Finally, numerical simulation results verify the feasibility of the proposed method. © 2024 IEEE.

关键词： ambiguity distributed array Range-angle imaging the prior of target scattering characteristics weight

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A Node Confidence Determination Based Moving Target Defense Strategy for SDN 15

A Node Confidence Determination Based Moving Target Defense ...

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15th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2023

作者： Sun, Shimin Xu, Guowei Han, Li Tianjin Key Laboratory of Autonomous Intelligent Technology and System School of Software Tiangong Tianjin China Tianjin Univ. of Technol. Natl. Eng. Laboratory for Computer Virus Prevention and Control Technology School of Computer Science and Engineering Tianjin China

ISBN: (纸本)9798350308693

With the rapid development of Internet technology, network assets have become an indispensable part of modern society. Especially in the face of high-value network assets, the attacker is faced with paying a greater cost to study the network structure. Due to the unknown attacker and attack means, the attacker has an advantage in the attack and defense situation. The moving target defense technique can flexibly change the static characteristics of the network attack surface and increase the difficulty for the attacker to detect the network, thus achieving the purpose of enhancing network security. Based on this technique, this paper proposes a defense strategy based on node confidence. It puts forward stricter constraints on the differential selection of address/port hopping paths, dynamically selects the hopping objects according to the node's confidence, and implements the defense strategy of differential complexity. This further increases the network's uncertainty and the difficulty for the attacker to detect the network structure. The experimental results show that in the path differentiation comparison, the maximum improvement is about 18% compared to the Dynamic Random Route Hopping strategy. In the CPU load experiment, the CPU load rate is reduced by about 4.625% on average compared to the Double Address Hopping strategy. Moreover, for larger hopping period, the proposed strategy also performs well in terms of CPU load rate. The proposed strategy also exhibits good performance in terms of CPU load ratio for large hopping cycles. © 2023 IEEE.

关键词： Network security

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Deep Learning and Machine Learning Algorithms to Predict Lung Cancer

Deep Learning and Machine Learning Algorithms to Predict Lun...

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Emerging Trends in Information Technology and engineering (ic-ETITE), Conference on

作者： K. Gowthami Kamalakannan. J School of Computer Science Engineering and Information System. Vellore Institute Of Technology Vellore India

Lung cancer is the most deadly illness for patients, and it is an incurable condition. Patient survival rates are greatly increased by early cancer prognosis and identification. The Computed Tomography (CT) scan is an important imaging tool for a lung cancer diagnosis. On the other hand, a manual CT scan inspection is laborious and prone to mistakes. Lung cancer can be impulsively recognized by utilizing an image processing technique of computer-Aided Diagnosis (CAD). In recent years, various researchers identified various ways for accurate prediction by Using techniques for deep learning (DL) and machine learning (ML). This research represents a number of methodologies like Lung cancer disease prediction analysis makes use of Artificial Neural Network (ANN), Logistic Regression (LR), Support Vector Machine (SVM), K-means clustering, Convolutional Neural Network (CNN) Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM).

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Wavelet method optimised by ant colony algorithm used for extracting stable and unstable signals in intelligent substations

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CAAI Transactions on Intelligence Technology 2022年第2期7卷 292-300页

作者： Tianyan Jiang Xiao Yang Yuan Yang Xi Chen Maoqiang Bi Jianfei Chen School of Electrical and Electronic Engineering Chongqing University of TechnologyChongqingChina DepartmentState Key Laboratory of Power Transmission Equipment&System and New Technology Chongqing UniversityChongqingChina Department of Electrical and Computer Engineering University of MarylandCollege ParkMarylandUSA

Partial discharge(PD)signals are an important index to evaluate the operation state of intelligent *** correct distinction of PD pulse and interference pulse has become a challenging *** of the noise and the low signal-to-noise ratio,the stable signals become *** selection of a wavelet basis,the selection rule of thresholdλand the design of the threshold function are the key factors affecting the final denoising ***,an enhanced ant colony optimisition wavelet(ACOW)algorithm was applied to find the global optimal threshold through the continuous derivative threshold function and the ant colony optimisation(ACO)*** the same time the efficiency of adaptive search calculation,was also significantly *** method of the ACOW algorithm was compared with the soft wavelet method,gradient-based wavelet method and the genetic optimisation wavelet(GOW)*** these four methods to denoise four typical signals,different mean square errors(MSE),magnitude errors(ME)and time costs were ***,the results show that the ACOW method can achieve the minimum MSE and has less time *** generates significantly smaller waveform distortion than the other three threshold estimation *** addition,the high efficiency and good quality of the output signals are beneficial to the diagnosis of local discharge signals in intelligent substations.

关键词： algorithm noise method

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High-Resolution Data on Human Behavior for Effective COVID-19 Policy-Making—Wuhan City,Hubei Province,China,January 1–February 29,2020

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China CDC weekly 2023年第4期5卷 76-81,I0004-I0009页

作者： Jingyuan Wang Honghao Shi Jiahao Ji Xin Lin Huaiyu Tian School of Computer Science and Engineering Beihang UniversityBeijingChina Pengcheng Laboratory Shenzhen CityGuangdong ProvinceChina School of Economics and Management Beihang UniversityBeijingChina State Key Laboratory of Remote Sensing Science Center for Global Change and Public HealthCollege of Global Change and Earth System ScienceBeijing Normal UniversityBeijingChina

Introduction:High-resolution data is essential for understanding the complexity of the relationship between the spread of coronavirus disease 2019(COVID-19),resident behavior,and interventions,which could be used to inform policy responses for future prevention and ***:We obtained high-resolution human mobility data and epidemiological data at the community *** propose a metapopulation Susceptible-Exposed-Presymptomatic-Infectious-Removal(SEPIR)compartment model to utilize the available data and explore the internal driving forces of COVID-19 transmission dynamics in the city of ***,we will assess the effectiveness of the interventions implemented in the smallest administrative units(subdistricts)during the ***:In the Wuhan epidemic of March 2020,intra-subdistrict transmission caused 7.6 times more infections than inter-subdistrict *** the city was closed,this ratio increased to 199 *** main transmission path was dominated by population activity during peak evening ***:Restricting the movement of people within cities is an essential measure for controlling the spread of ***,it is difficult to contain intra-street transmission solely through citywide mobility restriction *** can only be accomplished by quarantining communities or buildings with confirmed cases,and conducting mass nucleic acid testing and enforcing strict isolation protocols for close contacts.

关键词： district utilize Wuhan

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A Novel Determination of Soluble NPK Nutrient Measurement system Using K-means and SOM Methods Compared with UV Visible Spectrophotometer

A Novel Determination of Soluble NPK Nutrient Measurement Sy...

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2023 International Electrical engineering Congress, iEECON 2023

作者： Tipwong, Wallop Sirikham, Adisorn Konpang, Jessada Kirdpipat, Putthiphong Chongjarearn, Yutana Preutisrunyanont, Oradee Rajamangala University of Technology Krungthep Department of Electrical and Telecommunication Engineering Bangkok Thailand Thammasat School of Engineering Thammasat University Faculty of Engineering Department of Electrical and Computer Engineering Pathum Thani Thailand Dhurakij Pundit University Department of Robotic Engineering and Automation System Bangkok Thailand

ISBN: (纸本)9798350332360

Technologies are currently being used in smart farms to improve productivity. Agricultural innovation is also widespread. Therefore, the development of Internet of Things (IoTs) technologies and devices to collect data is important. Finding essential nutrients for growth such as Nitrogen (N), Phosphorus (P) and Potassium (K) are important factors. Competitiveness is the important key for growing vertically or indoors. However, soil testing can be expensive, complicated and time consuming. The development of devices that can effectively measure nutrient NPK levels could be used over time. This paper presents a suitable clustering using the K-means method and a forecasting method using the Self-Organizing Map (SOM) method to enhance the device's ability to analyze nutrients in real time. A total of 50,688 samples were tested using the K-Means clustering algorithm, and the sample data were also analyzed. A SOM was prepared to predict the accuracy of the analysis. A total of 11,486 samples were tested and analyzed, then the results of the soluble NPK nutrient monitoring system were taken. It has an efficiency of 84.15% compared to using a UV Visible spectrophotometer, allowing data to be predicted during nutrient solubility changes and to operate according to the proposed system. Therefore, the unsupervised machine learning will improve the measurement system of future cultivation systems. © 2023 IEEE.

关键词： Nutrients

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