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5th Workshop on Computational Approaches to Discourse, CODI 2024

作者： Costa, Nelson Filipe Kosseim, Leila Laboratory Department of Computer Science and Software Engineering Concordia University MontréalQC Canada

ISBN: (纸本)9798891760790

This paper proposes a classification model for single label implicit discourse relation recognition trained on soft-label distributions. It follows the PDTB 3.0 framework and it was trained and tested on the DiscoGeM corpus, where it achieves an F1-score of 51.38 on third-level sense classification of implicit discourse relations. We argue that training on soft-label distributions allows the model to better discern between more ambiguous discourse relations. © 2024 Association for Computational Linguistics.

关键词： Classification (of information)

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MCIF-Transformer Mask RCNN:Multi-Branch Cross-Scale Interactive Feature Fusion Transformer Model for PET/CT Lung Tumor Instance Segmentation

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computers, Materials & Continua 2024年第6期79卷 4371-4393页

作者： Huiling Lu Tao Zhou School of Medical Information&Engineering Ningxia Medical UniversityYinchuan750004China School of Computer Science and Engineering North Minzu UniversityYinchuan750021China Key Laboratory of Image and Graphics Intelligent Processing of State Ethnic Affairs Commission NorthMinzu UniversityYinchuan750021China

The precise detection and segmentation of tumor lesions are very important for lung cancer computer-aided ***,in PET/CT(Positron Emission Tomography/Computed Tomography)lung images,the lesion shapes are complex,the edges are blurred,and the sample numbers are *** solve these problems,this paper proposes a Multi-branch Cross-scale Interactive Feature fusion Transformer model(MCIF-Transformer Mask RCNN)for PET/CT lung tumor instance segmentation,The main innovative works of this paper are as follows:Firstly,the ResNet-Transformer backbone network is used to extract global feature and local feature in lung *** pixel dependence relationship is established in local and non-local fields to improve the model perception ***,the Cross-scale Interactive Feature Enhancement auxiliary network is designed to provide the shallow features to the deep features,and the cross-scale interactive feature enhancement module(CIFEM)is used to enhance the attention ability of the fine-grained ***,the Cross-scale Interactive Feature fusion FPN network(CIF-FPN)is constructed to realize bidirectional interactive fusion between deep features and shallow features,and the low-level features are enhanced in deep semantic ***,4 ablation experiments,3 comparison experiments of detection,3 comparison experiments of segmentation and 6 comparison experiments with two-stage and single-stage instance segmentation networks are done on PET/CT lung medical image *** results showed that APdet,APseg,ARdet and ARseg indexes are improved by 5.5%,5.15%,3.11%and 6.79%compared with Mask RCNN(resnet50).Based on the above research,the precise detection and segmentation of the lesion region are realized in this *** method has positive significance for the detection of lung tumors.

关键词： PET/CT images instance segmentation mask RCNN interactive fusion transformer

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Real-Time Smart Healthcare System Based on Edge-Internet of Things and Deep Neural Networks for Heart Disease Prediction

Informatica (Slovenia)

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Informatica (Slovenia) 2025年第1期49卷 93-104页

作者： Hameurlaine, Messaoud Moussaoui, Abdelouhab Bensalah, Mustapha LEIMA Laboratory Tissemsilt University Tissemsilt Algeria Computer Science Department Faculty of Sciences Ferhat Abbas University - Sétif 1 Algeria Signal Processing Laboratory Military Polytechnic School Algiers Algeria

With technological advancements, smart health monitoring systems have become increasingly vital and popular. The rise of smart homes, appliances, and medical systems, along with the pivotal role of the Internet of Things (IoT), is significantly enhancing healthcare services by improving data processing and predictive capabilities. IoT not only aids in predicting heart disease but also supports emergency responses. However, traditional data transfer methods are inefficient in terms of time and energy, resulting in high latency and consumption. Edge computing, alongside deep learning methods, provides effective solutions with superior performance. This paper introduces a Real-Time Smart Healthcare System utilizing Edge-Internet of Things and Deep Learning. The primary objective of this system is to monitor patient health changes, predict heart disease, and automate medication administration in real time. The study presents a DNN-based prediction model that leverages edge computing and IoT. This model processes health data from IoT devices, while edge devices deliver timely health predictions to doctors and patients via edge and cloud servers. The proposed system is evaluated on performance parameters, demonstrating superior results compared to other methods. By integrating edge computing, IoT, and deep learning, this system enables efficient real-time health monitoring and prediction, benefiting both healthcare professionals and patients. It demonstrates exceptional performance with an accuracy of 96.15%, precision of 92.86%, recall (sensitivity) of 97.50%, and an F1-score of 94.87%. © 2025 Slovene Society Informatika. All rights reserved.

关键词： Electronic health record

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Stochastic Unit Commitment with High-Penetration Offshore Wind Power Generation in Typhoon Scenarios

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Journal of Modern Power Systems and Clean Energy 2024年第2期12卷 535-546页

作者： Yanqi Liu Dundun Liu Hongcai Zhang State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering University of MacaoMacao 999078China University of Macao Zhuhai UM Science and Technology Research Institute ZhuhaiChina

To tackle the energy crisis and climate change,wind farms are being heavily invested in across the *** China's coastal areas,there are abundant wind resources and numerous offshore wind farms are being *** secure operation of these wind farms may suffer from typhoons,and researchers have studied power system operation and resilience enhancement in typhoon ***,the intricate movement of a typhoon makes it challenging to evaluate its spatial-temporal *** published papers only consider predefined typhoon trajectories neglecting *** address this challenge,this study proposes a stochastic unit commitment model that incorporates high-penetration offshore wind power generation in typhoon *** adopts a data-driven method to describe the uncertainties of typhoon trajectories and considers the realistic anti-typhoon mode in offshore wind farms.A two-stage stochastic unit commitment model is designed to enhance power system resilience in typhoon *** formulate the model into a mixed-integer linear programming problem and then solve it based on the computationally-efficient progressive hedging algorithm(PHA).Finally,numerical experiments validate the effectiveness of the proposed method.

关键词： Unit commitment two-stage stochastic programming offshore wind farm typhoon

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Emerging Trends and Challenges in Cybersecurity Data science: A State-of-the-Art Review 6

Emerging Trends and Challenges in Cybersecurity Data Science...

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6th Parul International Conference on Engineering and Technology, PICET 2024

作者： Datta, Nippon Mahmud, Tanjim Aziz, Mohammad Tarek Das, Rahul Kanti Hossain, Mohammad Shahadat Andersson, Karl Department of Computer Science and Engineering Chittagong University of Engineering & Technology Chittagong Bangladesh Department of Computer Science and Engineering Rangamati Science and Technology University Rangamati4500 Bangladesh Department of Computer Science and Engineering University of Chittagong Chittagong4331 Bangladesh Cybersecurity Laboratory Luleå University of Technology Luleå97187 Sweden

ISBN: (纸本)9798350369748

Cybersecurity is the process of defending computer networks, systems, and digital data from intrusions, hacks, damage, and other cyber threats. It also prevents illegal access, and exploitation of sensitive and personal data, including financial records, healthcare information, and intellectual property. It is essential to extract the security incident patterns from the cybersecurity data to build a data-driven model that assists in making a cybersecurity system intelligent and automated. As the review is based on "Cybersecurity data science" So, this study is focused on recent cybersecurity data science and evaluates their methodologies as well as their findings. In this review, the research significance of cybersecurity has been explained clearly and recent activities on cybersecurity briefly described. We also summarized the reason behind several cyber attacks along with their countermeasures. It seeks to be a useful tool for scholars, industry professionals, and decision-makers by providing a comprehensive and current summary of cybersecurity, emphasizing the most important problems. © 2024 IEEE.

关键词： Network intrusion

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Beyond 5G Networks: Integration of Communication, Computing, Caching, and Control

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China Communications 2023年第7期20卷 137-174页

作者： Musbahu Mohammed Adam Liqiang Zhao Kezhi Wang Zhu Han State Key Laboratory of Integrated Service Networks Xidian UniversityXi’an 710071China Department of Computer and Information Sciences Northumbria UniversityNewcastle upon TyneUK Department of Electrical and Computer Engineering University of HoustonHoustonTX 77004 USAand also with the Department of Computer Science and EngineeringKyung Hee UniversitySeoul 02447 South Korea

In recent years,the exponential proliferation of smart devices with their intelligent applications poses severe challenges on conventional cellular *** challenges can be potentially overcome by integrating communication,computing,caching,and control(i4C)*** this survey,we first give a snapshot of different aspects of the i4C,comprising background,motivation,leading technological enablers,potential applications,and use ***,we describe different models of communication,computing,caching,and control(4C)to lay the foundation of the integration *** review current stateof-the-art research efforts related to the i4C,focusing on recent trends of both conventional and artificial intelligence(AI)-based integration *** also highlight the need for intelligence in resources ***,we discuss the integration of sensing and communication(ISAC)and classify the integration approaches into various ***,we propose open challenges and present future research directions for beyond 5G networks,such as 6G.

关键词： 4C 6G integration of communication,computing,caching,and control i4C multi-access edge computing(MEC)

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Multi-objective cooling control optimization for air-liquid cooled data centers using TCN-BiGRU-Attention-based thermal prediction models

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Building Simulation 2024年第12期17卷 2145-2161页

作者： Jianpeng Lin Wenjun Lin Weiwei Lin Tianyi Liu Jiangtao Wang Hongliang Jiang Department of Computer Science and Engineering South China University of TechnologyGuangzhou 510000China Peng Cheng Laboratory Shenzhen 518066China Huawei Technologies Co. Ltd.Shenzhen 518066China

With the breakthroughs in generative artificial intelligence(GAI)models,the vast computational demands are placing an unprecedented burden on the data center(DC)energy *** cooling system is the second major energy consumer in the DC,maintaining the safe and efficient operation of computing ***,time-varying temperature gradients and power distribution pose a considerable challenge for efficient cooling management in *** this problem,this work proposes a multi-objective cooling control optimization(MCCO)method to minimize cooling energy consumption while maximizing the rack cooling index(RCI)to ensure energy efficiency and security of hybrid-cooled *** proposed method relies on high-fidelity models that characterize the dynamic thermal evolution and cooling ***,a novel network model(TCN-BiGRU-Attention)combining temporal convolutional network(TCN),bidirectional gated recurrent unit(BiGRU),and attention mechanism is designed to capture the features of multivariate time-series to predict temperature changes in thermal environments and cooling ***,considering the complex heat transfer and operational characteristics of hybrid cooling systems,a machine learning(ML)-based power model is constructed to evaluate the holistic cooling ***,the NSGA-II algorithm formulates the optimal cooling decision based on the predicted thermal distribution and cooling power,realizing the trade-off between energy consumption and cooling *** results of numerical experiments using Marconi 100 data traces suggest that the proposed MCCO significantly reduces cooling energy consumption in summer and winter while maintaining the RCI above 95%.

关键词： data center thermal prediction cooling control multi-objective optimization energy saving

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Two-view attention-guided convolutional neural network for mammographic image classification

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CAAI Transactions on Intelligence Technology 2023年第2期8卷 453-467页

作者： Lilei Sun Jie Wen Junqian Wang Yong Zhao Bob Zhang Jian Wu Yong Xu College of Computer Science and Technology Guizhou UniversityGuiyangChina Shenzhen Key Laboratory of Visual Object Detection and Recognition Harbin Institute of TechnologyShenzhenChina Harbin Institute of Technology ShenzhenChina School of Electronic and Computer Engineering Shenzhen Graduate School of Peking UniversityShenzhenChina Department of Computer and Information Science University of MacaoTaipaChina Science for Life Laboratory KTH Royal Institute of TechnologyStockholmSweden

Deep learning has been widely used in the field of mammographic image classification owing to its superiority in automatic feature ***,general deep learning models cannot achieve very satisfactory classification results on mammographic images because these models are not specifically designed for mammographic images and do not take the specific traits of these images into *** exploit the essential discriminant information of mammographic images,we propose a novel classification method based on a convolutional neural ***,the proposed method designs two branches to extract the discriminative features from mammographic images from the mediolateral oblique and craniocaudal(CC)mammographic *** features extracted from the two-view mammographic images contain complementary information that enables breast cancer to be more easily ***,the attention block is introduced to capture the channel-wise information by adjusting the weight of each feature map,which is beneficial to emphasising the important features of mammographic ***,we add a penalty term based on the fuzzy cluster algorithm to the cross-entropy function,which improves the generalisation ability of the classification model by maximising the interclass distance and minimising the intraclass distance of the *** experimental results on The Digital database for Screening Mammography INbreast and MIAS mammography databases illustrate that the proposed method achieves the best classification performance and is more robust than the compared state-ofthe-art classification methods.

关键词： convolutional neural network deep learning medical image processing mammographic image

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Security challenges and defense approaches for blockchain-based services from a full-stack architecture perspective

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Blockchain(Research and Applications) 2023年第3期4卷 18-38页

作者： Hongsong Chen Xietian Luo Lei Shi Yongrui Cao Yongpeng Zhang Department of Computer Science University of Science and Technology Beijing(USTB)Beijing100083China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083China

As an advantageous technique and service,the blockchain has shown great development and application ***,its security has also met great challenges,and many security vulnerabilities and attack issues in blockchain-based services have ***,security issues of blockchain have attracted extensive ***,there is still a lack of blockchain security research from a full-stack architecture perspective,as well as representative quantitative experimental reproduction and *** aim to provide a security architecture to solve security risks in blockchain services from a full-stack architecture ***,we propose a formal definition of the full-stack security architecture for blockchain-based services,and we also propose a formal expression of security issues and defense solutions from a full-stack security *** use ConCert to conduct a smart contract formal verification experiment by property-based *** security vulnerabilities of blockchain services in the Common Vulnerabilities and Exposures(CVE)and China Nation Vulnerability Database(CNVD)are selected and ***,three real contract-layer real attack events are reproduced by an experimental *** Alibaba's blockchain services and Identity Mixer in Hyperledger Fabric as a case study,the security problems and defense techniques are analyzed and *** last,the future research directions are proposed.

关键词： Security and privacy Blockchain-based services Full stack Architecture perspective Case and experimental study Formal verification

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Detecting Double Mixed Compressed Images Based on Quaternion Convolutional Neural Network

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Chinese Journal of Electronics 2024年第3期33卷 657-671页

作者： Hao WANG Jinwei WANG Xuelong HU Bingtao HU Qilin YIN Xiangyang LUO Bin MA Jinsheng SUN Department of Automation Nanjing University of Science and Technology Engineering Research Center of Digital Forensics Ministry of Education Department of Computer and Software Nanjing University of Information Science and Technology School of Management Nanjing University of Posts and Telecommunications Department of Computer Science and Engineering Guangdong Province Key Laboratory of Information Security Technology Sun Yat-sen University State Key Laboratory of Mathematical Engineering and Advanced Computing Qilu University of Technology

Detection of color images that have undergone double compression is a critical aspect of digital image *** the existence of various methods capable of detecting double Joint Photographic Experts Group(JPEG) compression,they are unable to address the issue of mixed double compression resulting from the use of different compression *** particular,the implementation of Joint Photographic Experts Group 2000(JPEG2000)as the secondary compression standard can result in a decline or complete loss of performance in existing *** tackle this challenge of JPEG+JPEG2000 compression,a detection method based on quaternion convolutional neural networks(QCNN) is *** QCNN processes the data as a quaternion,transforming the components of a traditional convolutional neural network(CNN) into a quaternion *** relationships between the color channels of the image are preserved,and the utilization of color information is ***,the method includes a feature conversion module that converts the extracted features into quaternion statistical features,thereby amplifying the evidence of double *** results indicate that the proposed QCNN-based method improves,on average,by 27% compared to existing methods in the detection of JPEG+JPEG2000 compression.

关键词： Color image forensics JPEG JPEG2000 Mixed double compression Quaternion convolutional neural network

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