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4th IEEE International Conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2024

作者： Liu, Xiaoxiao McGrath, Sean Flanagan, Colin Lei, Yiming Zeng, Liaoyuan Electronic and Computer Engineering University of Limerick Limerick Ireland School of Mathematics and Information HeBei University HeBei China Mobile Digital Hospital System School of Electronics Peking University Ministry of Education Engineering Research Center Beijing China University of Electronic Science and Technology of China Department of Information and Communication Engineering Chengdu China

ISBN: (纸本)9798350360721

A comprehensive understanding of physiological data is essential for anesthesiologists to monitor and maintain the health of surgical patients. Understanding anesthetic signals is essential to improve over the past ten decades to comprehend a variety of diseases, ensure the safety of patients, and accelerate their recovery. We identified and summarized four themes of artificial intelligence (AI) research in anesthesia: applications of AI in anesthesiology, signals monitored in different anesthesia stages, commonly monitored signs, and data standardization. The effect of various AI technologies on data analysis was studied, and the types, functions, sensors, characteristics, and intelligent analysis of physiological signals monitored during anesthesia are presented in this article. AI influences anesthesia practices in many ways, including preoperative data evaluation, anesthetic depth monitoring, and postoperative event prediction. © 2024 IEEE.

关键词： Machine learning

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Fuzzing DBMS via NNLM 7

Fuzzing DBMS via NNLM

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7th IEEE International Conference on Data Science in Cyberspace, DSC 2022

作者： Li, Yabin Nie, Yuanping Kuang, Xiaohui Beijing University of Posts and Telecommunications School of Computer Science Beijing China National Key Laboratory of Science and Technology on Information System Security Beijing China

ISBN: (数字)9781665474801

ISBN: (纸本)9781665474801

Vulnerabilities in database management system (DBMS) can cause serious security problems affecting hundreds of millions of software systems. Fuzzing is an effective vulnerability mining technology, but few studies utilize neural network language model (NNLM) to fuzz DBMS. In this paper, we explore this technical roadmap and use the sequence model to automatically generate test cases to fuzz DBMS. One of the advantages of the method is that it can effectively test the DBMS in a black-box situation. We implemented our tool NNFuzz and evaluated it on SQLite. Experimental results show that NNFuzz can generate valid test cases and achieve higher code coverage than the initial training set. © 2022 IEEE.

关键词： Database systems

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Multimodal Aspect-Based Sentiment Analysis under Conditional Relation 31

Multimodal Aspect-Based Sentiment Analysis under Conditional...

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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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i-Know: Revolutionizing Knowledge Management with Interactive Quizzes

i-Know: Revolutionizing Knowledge Management with Interactiv...

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Humanitarian technology Conference (KHI-HTC), IEEE Karachi Section

作者： Zahidah Zulkifli Muhammad Darwish Bin Abdul Halim Arief Iskandar Bin Shaffei Nisrin AlSaiari Department of Information System Kulliyyah of Information and Communication Technology International Islamic University Malaysia Faculty of Computer Studies Arab Open University Saudi Arabia

This project focuses on the development of a website system designed to facilitate knowledge acquisition for students enrolled in the Kulliyyah of information Communication and technology (KICT) at the International Islamic University Malaysia (IIUM). The aim is to alleviate the information overload experienced by new intake students during the Taaruf week (orientation week). Despite its establishment in 2010, KICT faces a persistent challenge where new students remain unaware of crucial system details, including rules, regulations, and academic matters. To address this issue, the project endeavors to provide a comprehensive platform enabling new students to access pertinent information and knowledge about KICT. An analysis of seven similar existing systems has been conducted, highlighting their main functions, advantages, and disadvantages. The system Development Life Cycle methodology has been selected for its practicality in guiding the project through the phases of Final Year Project (FYP) 1 and FYP2. Data collection involved surveying 30 KICT students to identify challenges faced by new students in obtaining the necessary information. Results underscore the urgent need for a technically guided application to enhance student understanding of KICT. The logical design of the app encompasses a Use Case Diagram, Use Case Narrative, Activity Diagram, Interface Flow, Low-Fidelity Design, and Interface Flow. The “i-know” system has been developed using PHP, HTML, CSS, and Javascript, with connectivity to MySQL through phpMyAdmin for user authentication. The User Acceptance Test (UAT) was conducted during implementation, following beta testing. The paper concludes with insights into the system’s effectiveness and its potential to address the identified challenges faced by new KICT students.

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A New Perspective of Deep Learning Testing Framework: Human-computer Interaction Based Neural Network Testing

A New Perspective of Deep Learning Testing Framework: Human-...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Wei Kong Hu Li Qianjin Du Huayang Cao Xiaohui Kuang National Key Laboratory of Science and Technology on Information System Security Beijing China Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Deep learning models have revolutionized various domains but have also raised concerns regarding their security and reliability. Adversarial attacks and coverage-based testing have been extensively studied to assess and enhance the dependability of deep neural networks. However, current research in this area has reached a state of stagnation. Adversarial attacks focus on exploiting vulnerabilities in models, while coverage-based testing aims to achieve comprehensive testing but overlooks application scenarios. Moreover, evaluating test cases solely based on their fault-revealing capability is insufficient. To address these limitations, we propose an innovative interdisciplinary framework that incorporates human-computer interaction methods in deep learning security testing. By considering the attributes of model application scenarios, we can design more effective test suites that intend to reveal the model's behavior across various scenarios, aiding in the identification of potential defects. Consequently, the test suite plays a crucial role in the testing process of deep learning models, contributing to the assurance of model robustness and reliability. Additionally, we establish a comprehensive evaluation metric for test suite quality, considering factors such as diversity and naturalness. This framework promotes reliable and secure deployment of deep learning models, fostering interdisciplinary collaboration between artificial intelligence and human-computer interaction.

关键词： Deep learning Human computer interaction Measurement Diversity reception Collaboration Robustness Security

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technology Integration in Cultural Heritage Preservation Enhancing Community Engagement and Effectiveness 3

Technology Integration in Cultural Heritage Preservation Enh...

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3rd International Conference on Creative Communication and Innovative technology, ICCIT 2024

作者： Lukita, Chandra Lutfiani, Ninda Salam, Rahmat Pangilinan, Greian April Setiani Rafika, Ageng Ahsanitaqwim, Ridhuan University of Catur Insan Cendekia Master of Management Cirebon Indonesia University of Raharja Master of Information System Tangerang Indonesia University of Muhamadiyah Jakarta Master of Administrative Sciences Jakarta Indonesia Centro Escolar University Medical Technology Manila Philippines University of Raharja Department of Computer System Tangerang Indonesia Kreatif Desain Department of Engineering Tangerang Indonesia

ISBN: (纸本)9798350367492

In the digital era, the preservation of cultural heritage faces unique challenges and opportunities. This research explores the integration of technology with traditional cultural practices, aiming to ensure sustainable preservation and promotion of cultural heritage. A key component of the study is the application of SmartPLS, a structural equation modeling tool, to analyze relationships between variables, including Technological Adoption (TA), Cultural Engagement (CE), Preservation Effectiveness (PE), Digital Documentation (DD), and Community Involvement (CI). Preliminary data indicate that Technological Adoption accounts for approximately 45.5% of the variance in Cultural Engagement, while Digital Documentation contributes to 38% of the variance in Preservation Effectiveness. Community Involvement influences Preservation Effectiveness by 30%. The research employs qualitative methods, including interviews and case studies, to evaluate various digital preservation initiatives. The study aims to provide a framework for integrating technology into cultural preservation, guidelines for effective documentation, and policy recommendations for sustainable cultural tourism. It holds significant implications for cultural organizations, communities, and policymakers, offering a pathway to ensure that cultural traditions are not only remembered but also experienced and appreciated by future generations in a rapidly evolving digital landscape. © 2024 IEEE.

关键词： Digital Documentation Engagement Heritage Preservation SmartPLS technology Integration

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An authenticated spectrum acquirement and transmission of encrypted images over fusion centre

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Multimedia Tools and Applications 2024年 1-24页

作者： V, Thanikaiselvan Y, PiyaDessi S, Renuga devi Shanthini, S. Suba Mahalingam, Hemalatha S, Aashiq Banu R, Dhivya V.M, Padmapriya Amirtharajan, Rengarajan School of Electronics Engineering Vellore Institute of Technology Vellore Vellore India School of Information Technology Vellore Institute of Technology Vellore India Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah22254 Saudi Arabia System Engineering Department Military Technological College Muscat Oman Department of Electronics and Communication Engineering Mepco Schlenk Engineering College Tamilnadu Sivakasi626005 India Department of Computer Sciences Marquette University MilwaukeeWI53233 United States School of Electrical & amp Electronics Engineering SASTRA Deemed University 613 401 Thanjavur India

These days, spectrum insufficiency is the most common issue. If the number of smartphone users who access the radio spectrum grows, the radio spectrum becomes increasingly scarce. Certain types of technology equipment are designed to work only within a specific spectrum range, and there is rivalry in specifications for various other applications. As a result, this paper effectively exploits a licensed user’s unused spectrum to reduce the crowded spectrum and eradicate the Radio spectrum shortage. Licensed primary users (PUs) and secondary users (SUs) would be accepted into a Fusion Centre (FC) based on a spectrum framework with authentication. The approved PUs begin by updating their information to FC1;thenceforth, encryption is performed on the information uploaded to FC1. This information from FC1 is stored in Cloud Storage after encryption using the Blowfish algorithm & De-oxy DNA, a fast encryption algorithm. Following that, FC2, connected to the same cloud environment, downloads the PU data uploaded. The spectrum is then allocated to the authenticated SU linked to FC2 based on signal conditions and priority. This proposed method also avoids any delay in the network and encryption by acquiring a fast encryption algorithm, making the system faster and avoiding the Primary User Emulation (PUE) attack. Later, the time taken for the Tiny Encryption Algorithm (TEA) and the Blowfish/DNA algorithm are compared to validate the run time for different input images. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Authentication

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A third-party platoon coordination service: Pricing under government subsidies

A third-party platoon coordination service: Pricing under go...

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作者： Bai, Ting Johansson, Alexander Li, Shaoyuan Johansson, Karl Henrik Mårtensson, Jonas School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden KTH Royal Institute of Technology Stockholm Sweden Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China Digital Futures Stockholm Sweden

This paper models a platooning system consisting of trucks and a third-party service provider (TPSP), which performs platoon coordination, distributes the platooning profit in platoons, and charges trucks in exchange for the services. Government subsidies used to incentivize platooning are also considered. We propose a pricing rule for the TPSP, which keeps part of the platooning profit including the subsidy each time a platoon is formed. In addition, a platoon coordination solution based on the distributed model predictive control (MPC) is proposed, in which the pricing rule under government subsidies is integrated. We perform a realistic simulation over the Swedish road network to evaluate the impact of the pricing rule and subsidies on the achieved profits and fuel savings. Our results show that subsidies are an effective mean to boost fuel savings from platooning. Moreover, the simulation study indicates that high pricing corresponds to a low platooning rate of the system, as trucks' incentives for platooning decrease. © 2023 The Authors. Asian Journal of Control published by John Wiley & Sons Australia, Ltd on behalf of Chinese Automatic Control Society.

关键词： Trucks

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Internet of Things-based pregnancy tracking and monitoring service

Internet of Things-based pregnancy tracking and monitoring s...

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2022 International Conference Automatics and Informatics, ICAI 2022

作者： Ivanov, Rosen Yordanov, Stanimir Dinev, Dinko Technical University - Gabrovo Department Computer System and Technologies Gabrovo Bulgaria Technical University - Gabrovo Department Automation Information and Control Technology Gabrovo Bulgaria

ISBN: (数字)9781665476256

ISBN: (纸本)9781665476256

This paper presents the architecture and implementation of a service for pregnancy tracking and monitoring. The main goal of the service is to analyze the behavior of pregnant women in order to proactively decide to notify medical staff when symptoms are detected that are risky for the normal pregnancy. This is achieved by (1) providing the necessary pregnancy-related information for each of the gestational weeks (nutrition, physical activity, normal and risk symptoms, necessary screening tests, etc.), (2) analysis of physical activity of pregnant women, (3) measurement and analysis of basic biological indicators using a wireless sensor network (pulse oximeter, human body temperature, biopotential channel to obtain electrocardiogram (ECG) and bioimpedance channel to measure respiration), and (4) receiving push notifications about important events related to the pregnancy;scheduled medical examinations;risk factors;and messages from the obstetrician under whose supervision the pregnant woman is. The service has a distributed architecture - it uses multiple microservices. The communication between clients (mobile app), wireless sensor network and microservices is realized through a message broker. Microservices use its own MongoDB databases hosted in the Azure cluster. Experiments were conducted to prove the feasibility of the service on simulated wireless sensor network. © 2022 IEEE.

关键词： Wireless sensor networks

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Drug-Target Interaction Prediction Based on Drug Subgraph Fingerprint Extraction Strategy and Subgraph Attention Mechanism 9th

Drug-Target Interaction Prediction Based on Drug Subgraph Fi...

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19th International Conference on Advanced Data Mining and Applications, ADMA 2023

作者： Wang, Lizhi Zhang, Xiaolong Lin, Xiaoli Hu, Jing College of Computer Science and Technology Wuhan University of Science and Technology Hubei Wuhan China Hubei Key Laboratory of Intelligent Information Processing and Realtime Industrial System Hubei Wuhan China Institute of Big Data Science and Engineering Wuhan University of Science and Technology Hubei Wuhan China

ISBN: (纸本)9783031466700

Drug discovery is a major focus of modern research, and predicting drug-target interactions is one of the strategies to facilitate this research process. Traditional laboratory methods have long time cycles and are relatively costly, so the use of high-precision virtual screening is essential. Previous virtual screens have only considered the sequence structure of the drug or the graph structure of the drug, without considering the role of the drug subgraph structure. Therefore, this paper adopts a method for extracting drug subgraphs and designs a strategy for extracting drug subgraph fingerprints. Then, the fingerprint vector data of the drugs are trained by the graph neural network to produce drug information vectors containing the spatial structure of the drug subgraph. Finally, the subgraph attention mechanism is used to update the information on protein targets, facilitating the model to extract more information about the target site. The experimental results show that the model can predict drug-target interactions well, outperforming the state-of-the-art model in all metrics. And it is also effective in both classification prediction and affinity regression prediction. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Graph neural networks

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