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Information Gerrymandering in Elections 1

19th Principle and Practice of Data and Knowledge Acquisition Workshop, PKAW 2023, held in conjunction with the 20th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2023

作者： Liu, Xiaoxue Kato, Shohei Ren, Fenghui Su, Guoxin Zhang, Minjie Gu, Wen School of Computing and Information Technology University of Wollongong Wollongong Australia Department of Computer Science and Engineering Nagoya Institute of Technology Nagoya Japan Center for Innovative Distance Education and Research Japan Advanced Institute of Science and Technology Ishikawa Japan

ISBN: (数字)9789819978557

ISBN: (纸本)9789819978540

When making decisions, individuals often seek advice from their family, friends, and social network connections. In this way, individ-uals’ opinions are susceptible to influence from their connections’ viewpoints. For example, in elections, individuals may initially support one party, while social influence may sway their choice to another. A recent study by Stewart et al. introduced a metric, influence assortment, to quantify the phenomenon of information gerrymandering that one party can influence more voters from other parties by strategically distributing their members among the social networks. While this metric correlates strongly with voting outcomes, the finding is only suitable for two-party elections. In this paper, we define the influence assortment that incorporates the level of similarity (homophily) among neighbours in the social network and extend it to multi-party elections. We examine its ability to predict voting outcomes when all parties initially have equal votes and average degrees. Through simulations using a stochastic model of voting behaviour, we demonstrate that the correlation between the influence gap and vote difference is a strong predictor in both small and large scale-free networks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Stochastic systems

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Learning to Localize Cross-Anatomy Landmarks in X-Ray Images with a Universal Model

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Biomedical engineering Frontiers 2022年第1期3卷 298-308页

作者： Heqin Zhu Qingsong Yao Li Xiao S.Kevin Zhou Key Lab of Intelligent Information Processing of Chinese Academy of Sciences(CAS) Institute of Computing TechnologyCASBeijing 100190China Center for Medical Imaging RoboticsAnalytic Computing&Learning(MIRACLE)School of Biomedical Engineering&Suzhou Institute for Advanced ResearchUniversity of Science and Technology of ChinaSuzhou 215123China

Objective and Impact *** this work,we develop a universal anatomical landmark detection model which learns once from multiple datasets corresponding to different anatomical *** with the conventional model trained on a single dataset,this universal model not only is more light weighted and easier to train but also improves the accuracy of the anatomical landmark *** accurate and automatic localization of anatomical landmarks plays an essential role in medical image ***,recent deep learning-based methods only utilize limited data from a single *** is promising and desirable to build a model learned from different regions which harnesses the power of big *** model consists of a local network and a global network,which capture local features and global features,*** local network is a fully convolutional network built up with depth-wise separable convolutions,and the global network uses dilated convolution to enlarge the receptive field to model global *** evaluate our model on four 2D X-ray image datasets totaling 1710 images and 72 landmarks in four anatomical *** experimental results show that our model improves the detection accuracy compared to the state-of-the-art *** model makes the first attempt to train a single network on multiple datasets for landmark *** results qualitatively and quantitatively show that our proposed model performs better than other models trained on multiple datasets and even better than models trained on a single dataset separately.

关键词： convolution utilize separable

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Zero Trust Networks: Evolution and Application from Concept to Practice

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Computers, Materials & Continua 2025年第2期82卷 1593-1613页

作者： Yongjun Ren Zhiming Wang Pradip Kumar Sharma Fayez Alqahtani Amr Tolba Jin Wang School of Computer Science School of Cyber Science and EngineeringEngineering Research Center of Digital ForensicsMinistry of EducationNanjing University of Information Science and TechnologyNanjing210044China Department of Computing Science University of AberdeenAberdeenAB243FXUK Software Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh12372Saudi Arabia Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Sanya Institute of Hunan University of Science and Technology Sanya572024China

In the context of an increasingly severe cybersecurity landscape and the growing complexity of offensive and defen-sive techniques,Zero Trust Networks(ZTN)have emerged as a widely recognized *** Trust not only addresses the shortcomings of traditional perimeter security models but also consistently follows the fundamental principle of“never trust,always verify.”Initially proposed by John Cortez in 2010 and subsequently promoted by Google,the Zero Trust model has become a key approach to addressing the ever-growing security threats in complex network *** paper systematically compares the current mainstream cybersecurity models,thoroughly explores the advantages and limitations of the Zero Trust model,and provides an in-depth review of its components and key ***,it analyzes the latest research achievements in the application of Zero Trust technology across various fields,including network security,6G networks,the Internet of Things(IoT),and cloud computing,in the context of specific use *** paper also discusses the innovative contributions of the Zero Trust model in these fields,the challenges it faces,and proposes corresponding solutions and future research directions.

关键词： Zero trust cybersecurity software-defined perimeter micro-segmentation internet of things

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Mamba-Enhanced Text-Audio-Video Alignment Network for Emotion Recognition in Conversations

arXiv

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arXiv 2024年

作者： Li, Xinran Fan, Xiaomao Wu, Qingyang Peng, Xiaojiang Li, Ye College of Big Data and Internet Shenzhen Technology University Shenzhen China Institute of Advanced Computing and Digital Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China

Emotion Recognition in Conversations (ERCs) is a vital area within multimodal interaction research, dedicated to accurately identifying and classifying the emotions expressed by speakers throughout a conversation. Traditional ERC approaches predominantly rely on unimodal cues—such as text, audio, or visual data—leading to limitations in their effectiveness. These methods encounter two significant challenges: 1)Consistency in multimodal information. Before integrating various modalities, it is crucial to ensure that the data from different sources is aligned and coherent. 2)Contextual information capture. Successfully fusing multimodal features requires a keen understanding of the evolving emotional tone, especially in lengthy dialogues where emotions may shift and develop over time. To address these limitations, we propose a novel Mamba-enhanced Text-Audio-Video alignment network (MaTAV) for the ERC task. MaTAV is with the advantages of aligning unimodal features to ensure consistency across different modalities and handling long input sequences to better capture contextual multimodal information. The extensive experiments on the MELD and IEMOCAP datasets demonstrate that MaTAV significantly outperforms existing state-of-the-art methods on the ERC task with a big margin. The source code is available at URL(https://***/AlenaXinran/MaTAV). Copyright © 2024, The Authors. All rights reserved.

关键词： Emotion Recognition

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On-site Testing and Preventive Maintenance for a Fire Automation System Employing PSO, FA and ANN Algorithms 1

On-site Testing and Preventive Maintenance for a Fire Automa...

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1st IEEE International Conference on Emerging research in Computational Science, ICERCS 2023

作者： Rubini, B. Kalaiarasi, G. Vasuki, S. Pradeep Kumar, S. Murugan, Suganiya Arul Stephen, C. Vels Institute of Science Technology and Advanced Studies Department of Electrical and Electronics Engineering Pallavaram Chennai India Vignan Foundation for Science Technology and Research Deemed to Be University Department of Advanced Computer Science and Engineering Andhrapradesh Guntur India M. Kumarasamy College of Engineering Department of Electronics and Communication Engineering Tamilnadu Karur India Srm Institute of Science and Technology Department of Computing Technologies Kaattankulathur Chennai India Vels Institute of Science Technology and Advanced Studies Department of Electronics and Communication Engineering Pallavaram Chennai India

ISBN: (纸本)9798350359756

engineering elements influencing in commercial and government buildings fire safety rendition buildings have been deliberated. For both new and existing buildings, all variables such as structure of building, damage due to fire from prevention compartments, Time of incidents evacuation routes should be control leverage on people's evacuation routes, controlled, and additional standard fire protection equipment are imposed. This page outlines the classes of diesel fire pumps, batteries, and pumping systems, besides the elements prompting fire rendition. Onsite diesel generator pump must be connected to a hydrant and the water pumping pressure range must be customized to 8 bar using a pressure gauge. The substantive intent of this concert is to reinforce firefighter safety. Only experienced technicians and training professionals in fire guard are responsible for this part. To simulate the battery tightness position, an extra-critical condition has been considered. Owing to the position of the fire safety properties and battery reaction in buildings, the Firefly and Particle Swarm optimization algorithms have been exerted on the iterations with objective values used for analysis in the iterative process using Matlab 2021 software. Two well-known algorithms are compared to see which provides the best results. The ANN serves as a tool for analyzing and optimizing the pump's rendition in maintaining an adequate water supply for fire emergencies. © 2023 IEEE.

关键词： Fires

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Implementation of a FHIR Specification for the Interoperability of a Remote Monitoring Platform of Patients with Vascular Diseases 20th

Implementation of a FHIR Specification for the Interoperabil...

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20th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2022

作者： Vieira, Ana Conceição, Luís Faria, Luiz Novais, Paulo Marreiros, Goreti GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Institute of Engineering – Polytechnic of Porto Porto Portugal ALGORITMI Centre University of Minho Braga Portugal

ISBN: (纸本)9783031186967

To address the current burdens in the healthcare of patients with vascular diseases, the Portuguese consortium of the Inno4Health project is currently developing a remote monitoring platform that aims to support the self-management of patients with vascular diseases. With the continuous remote monitoring of patients, it is intended that the platform supports both patients and health professionals. Patients will be supported through the presentation of personalized recommendations of activities to perform and health professionals will be supported in the clinical decision making through the presentation of meaningful insights. As the platform is composed by several components, including monitoring sensors, data processing modules and user applications, theressss is a need for the standardization of the data used. This work presents the implementation of a Fast Healthcare Interoperability Resources (FHIR) specification in the remote monitoring platform to ensure the standardization of the data that will be collected and exchanged between the several components of the platform. With this work, it will be possible to easily and securely exchange data, as well as integrating new monitoring sensors and user applications in the platform. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Standardization

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Estimating Blood Glucose Levels Using Machine Learning Models with Non- ?nvasive Wearable Device Data

Estimating Blood Glucose Levels Using Machine Learning Model...

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21st International Conference on Informatics, Management, and Technology in Healthcare, ICIMTH 2023

作者： Aziz, Sarah Ahmed, Arfan Abd-Alrazaq, Alaa Qidwai, Uvais Farooq, Faisal Sheikh, Javaid AI Center for Precision Health Weill Cornell Medicine-Qatar Doha Qatar Department of Computer Science and Engineering Qatar University Qatar Center for Digital Health and Precision Medicine Qatar Computing Research Institute Doha Qatar

ISBN: (纸本)9781643684000

In 2019 alone, Diabetes Mellitus impacted 463 million individuals worldwide. Blood glucose levels (BGL) are often monitored via invasive techniques as part of routine protocols. Recently, AI-based approaches have shown the ability to predict BGL using data acquired by non-invasive Wearable Devices (WDs), therefore improving diabetes monitoring and treatment. It is crucial to study the relationships between non-invasive WD features and markers of glycemic health. Therefore, this study aimed to investigate accuracy of linear and non-linear models in estimating BGL. A dataset containing digital metrics as well as diabetic status collected using traditional means was used. Data consisted of 13 participants data collected from WDs, these participants were divided in two groups young, and Adult Our experimental design included Data Collection, Feature engineering, ML model selection/development, and reporting evaluation of metrics. The study showed that linear and non-linear models both have high accuracy in estimating BGL using WD data (RMSE range: 0.181 to 0.271, MAE range: 0.093 to 0.142). We provide further evidence of the feasibility of using commercially available WDs for the purpose of BGL estimation amongst diabetics when using Machine learning approaches. © 2023 The authors and IOS Press.

关键词： Wearable technology

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Wearable AI Reveals the Impact of Intermittent Fasting on Stress Levels in School Children During Ramadan

Wearable AI Reveals the Impact of Intermittent Fasting on St...

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21st International Conference on Informatics, Management, and Technology in Healthcare, ICIMTH 2023

作者： Ahmed, Arfan Aziz, Sarah Abd-Alrazaq, Alaa Qidwai, Uvais Farooq, Faisal Sheikh, Javaid AI Center for Precision Health Weill Cornell Medicine-Qatar Doha Qatar Department of Computer Science and Engineering Qatar University Qatar Center for Digital Health and Precision Medicine Qatar Computing Research Institute Doha Qatar

ISBN: (纸本)9781643684000

Intermittent fasting has been practiced for centuries across many cultures globally. Recently many studies have reported intermittent fasting for its lifestyle benefits, the major shift in eating habits and patterns is associated with several changes in hormones and circadian rhythms. Whether there are accompanying changes in stress levels is not widely reported especially in school children. The objective of this study is to examine the impact of intermittent fasting during Ramadan on stress levels in school children as measured using wearable artificial intelligence (AI). Twenty-nine school children (aged 13-17 years and 12M / 17F ratio) were given Fitbit devices and their stress, activity and sleep patterns analyzed 2 weeks before, 4 weeks during Ramadan fasting and 2 weeks after. This study revealed no statistically significant difference on stress scores during fasting, despite changes in stress levels being observed for 12 of the participants. Our study may imply intermittent fasting during Ramadan poses no direct risks in terms of stress, suggesting rather it may be linked to dietary habits, furthermore as stress score calculations are based on heart rate variability, this study implies fasting does not interfere the cardiac autonomic nervous system. © 2023 The authors and IOS Press.

关键词： Wearable technology

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Thermally Evaporated ZnSe for Efficient and Stable Regular/Inverted Perovskite Solar Cells by Enhanced Electron Extraction

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Energy & Environmental Materials 2023年第5期6卷 440-448页

作者： Xin Li Guibin Shen Xin Ren Ng Zhiyong Liu Yun Meng Yongwei Zhang Cheng Mu Zhi Gen Yu Fen Lin Solar Energy Research Institute of Singapore(SERIS) National University of SingaporeSingapore 117574Singapore Key Laboratory of Advanced Light Conversion Materials and Biophotonics Department of ChemistryRenmin University of ChinaBeijing 100872China State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China School of Materials Science and Engineering Nanyang Technological UniversitySingapore 639798Singapore Shandong Provincial Engineering and Technical Center of Light Manipulation and Shandong Provincial Key Laboratory of Optics and Photonic Devices School of Physics and ElectronicsShandong Normal UniversityJinan 250014China Institute of High Performance Computing A^(*)STARSingapore 138632Singapore

Electron transport layers(ETLs)are crucial for achieving efficient and stable planar perovskite solar cells(PSCs).Reports on versatile inorganic ETLs using a simple film fabrication method and applicability for both low-cost planar regular and inverted PSCs with excellent efficiencies(>22%)and high stability are very ***,we employ a novel inorganic ZnSe as ETL for both regular and inverted PSCs to improve the efficiency and stability using a simple thermal evaporation *** TiO_(2)-ZnSe-FAPbl_(3)heterojunction could be formed,resulting in an improved charge collection and a decreased carrier recombination further proved through theoretical *** optimized regular PSCs based on TiO_(2)/ZnSe have achieved 23.25%efficiency with negligible *** addition,the ZnSe ETL can also effectively replace the unstable bathocuproine(BCP)in inverted ***,the ZnSe-based inverted device realizes a champion efficiency of 22.54%.Moreover,the regular device comprising the TiO_(2)/ZnSe layers retains 92%of its initial PCE after 10:00 h under 1 Sun continuous illumination and the inverted device comprising the C_(60)/ZnSe layers maintains over 85%of its initial PCE at 85℃for 10:00 *** highlights one of the best results among universal ETLs in both regular and inverted perovskite photovoltaics.

关键词： high efficiency long-term stability planar regular/inverted perovskite solar cells thermal evaporation ZnSe electron transport layer

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Multiscale Bilateral Attention Fusion Network for Pansharpening

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第11期5卷 5828-5843页

作者： Guo, Zhongyuan Li, Jiawei Lei, Jia Liu, Jinyuan Zhou, Shihua Wang, Bin Kasabov, Nikola K. Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian116622 China University of the Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China Dalian University of Technology School of Mechanical Engineering Dalian116024 China Auckland University of Technology Knowledge Engineering and Discovery Research Institute Auckland1061 New Zealand University of Ulster Intelligent Systems Research Center LondonderryBT48 7JL United Kingdom Bulgarian Academy of Sciences IICT Sofia1000 Bulgaria

High-resolution multispectral (HRMS) images combine spatial and spectral information originating from panchromatic (PAN) and reduced-resolution multispectral (LRMS) images. Pansharpening performs well and is widely used to obtain HRMS images. However, most pansharpening approaches determine the ratio of PAN and LRMS images through direct interpolation, which may introduce artifacts and distort the color of the fused results. To address this issue, an unsupervised progressive pansharpening framework, MSBANet, is proposed, which adopts a multistage fusion strategy. Each stage contains an attention interactive extraction module (AIEM) and a multiscale bilateral fusion module (MBFM). The AIEM extracts spatial and spectral features from input images and captures the correlations between features. The MBFM can efficiently integrate information from the AIEM and improve MSBANet context awareness. We design a hybrid loss function that enhances the ability of the fusion network to store spectral and texture details. In qualitative and quantitative experimental studies on four datasets, MSBANet outperformed state-of-the-art pansharpening techniques. The code will be released. © 2024 IEEE.

关键词： Data mining

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