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2022 IEEE International Conference on Consumer Electronics, ICCE 2022

作者： Alheeti, Khattab M. Ali Alzahrani, Abdulkareem Al Dosary, Duaa College of Computer and Information Technology University of Anbar Computer Networking Systems Dept. Ramadi Iraq Albaha University Faculty of Computer Science and Information Technology Computer Engineering and Science Department Albaha Saudi Arabia College of Computer Sciences and Information Technology University of Anbar Ramadi Iraq

ISBN: (纸本)9781665441544

Detecting 3D objects is a core task for autonomous vehicles (AVs), as it allows them to drive safely and responsibly. To detect objects quickly and accurately, AVs have LiDAR sensors, which can capture 3D data from 360° in various conditions, including harsh weather. However, LiDAR sensors may face a spoofing attack via laser satirizing. This type of attack does not require physical contact with the sensors nor does it need to change them. It can mislead AVs by providing them with false information, which can then put passengers, pedestrians, and other vehicles in danger. Therefore, this paper proposes a model utilizing machine learning (i.e., decision trees) to protect AVs from such attacks. The performance of the proposed model indicates that it can detect LiDAR spoofing attacks. © 2022 IEEE.

关键词： Autonomous vehicles

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Harnessing Big Data for Economic Transformation in a Digitalized World

Harnessing Big Data for Economic Transformation in a Digital...

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Creative Communication and Innovative technology (ICCIT), IEEE

作者： Riswan Efendi Tarigan Triyono Mahyuni Harry Agustian Rifky Nurfaizi Achani Rahmania Az Zahra Dept. of Information Systems Pelita Harapan University Tangerang Indonesia Dept. of Information Technology University of Raharja Tangerang Indonesia Dept. of Teacher Training and Education Science University of Mataram Mataram Indonesia Dept. of Computer Systems Sesindo Tangerang Indonesia Dept. of Information Technology Bosindo Tangerang Indonesia Dept. of Information Systems Pandawan Sejahtera Indonesia Tangerang Indonesia

ISBN: (数字)9798350367492

ISBN: (纸本)9798350367508

Air is essential to life and health, with oxygen (20.94%) and the ozone layer protecting against ultraviolet radiation. Depletion of oxygen reduces the ozone layer, increasing UV exposure. Good air quality is crucial for living organisms. In 2022, Indonesia’s PM 2.5 pollution ranked 26th worst globally, exceeding WHO standards, yet awareness and trust in air quality devices remain low. This study aims to implement and evaluate an AI-based machine learning system to predict the Air Quality Index (AQI) in healthcare services. Using Structural Equation Modeling with Partial Least Square analysis via SmartPLS 4.0, the research involves 120 participants and historical air quality data. Comparative analysis of machine learning algorithms assesses accuracy, robustness, and efficiency, highlighting their potential in forecasting AQI and its implications for public health and urban planning. The study demonstrates the effectiveness of these algorithms in predicting AQI, with a significant value of 0.874 for forecasting accuracy.

关键词： Machine learning algorithms Accuracy Urban planning Loading Air quality Mathematical models Indexes Forecasting Public healthcare Uninterruptible power systems

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Misogynistic Content Detection in Roman Urdu Tweets Based on Transformer Models

Misogynistic Content Detection in Roman Urdu Tweets Based on...

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IEEE International Conference on Multi Topic

作者： Waseem Ullah Khan Salman Ahmed Safdar Nawaz Khan Marwat Yousaf Khan Aftab Khan Shafi Ullah Kamran Dept. of Computer Systems Engg University of Engineering & Technology Peshawar Pakistan Dept. of Electrical Engg University of Engineering & Technology Peshawar Pakistan Dept. of Computer Science Allama Iqbal Open University Islamabad Pakistan Zong CMPak Islamabad Pakistan

ISBN: (数字)9798331507213

ISBN: (纸本)9798331507220

Facebook, Instagram and Twitter serve as influential social media platforms for individuals where they express and share their thoughts, skills, knowledge and talents with a broad audience. However, these platforms are also used to disseminate offensive content including trolling and content that targets a person’s gender, religion, or race. When women become the targets of such content, it is often manifests as misogyny. In recent years, the growing prevalence of racial and verbal abuse directed at women on social media has drawn considerable attention to the issue of online misogyny and women based offending, by making the automatic detection of such offensive content an urgent priority. Moreover, many researchers have addressed misogyny detection in high resource languages i.e., English, Italian, Arabic, Hindi, and more, tackling this issue in low resource language like Roman Urdu presents a significant challenge. In this paper, a framework is proposed for detection of misogynistic content from Roman Urdu tweets. This paper leverages well known transformer models such as BERT, RoBERTa, GPT-2, and XLNet to train and evaluate misogyny detection performance. The research findings reveal that RoBERTa surpasses the other models in misogyny detection, by achieving the highest accuracy, precision, F1-score and recall i.e., 90.87%, 90%, 89%, and 91%, respectively.

关键词： Accuracy Social networking (online) Blogs Linguistics Transformers Web sites Reliability Multimedia communication

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Addressing the Imbalanced Class Distribution in Fatty Liver Detection in CT Images Using Transfer Learning

Addressing the Imbalanced Class Distribution in Fatty Liver ...

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International Conference on Information and Communication systems (ICICS)

作者： Hamzeh Hailat Ahmad M. Mustafa Hassan Najadat Mamoon Alomari Sofyan Freihat Dept. of Computer Information Systems Jordan University of Science and Technology Irbid Jordan Dept. of Diagnostic Radiology and Nuclear Medicine Jordan University of Science and Technology Irbid Jordan

ISBN: (数字)9798331540760

ISBN: (纸本)9798331540777

Addressing the common challenges posed by limitations in medical images, our study involved the collection of CT images from the abdominal area of patients. We meticulously selected the appropriate shot for diagnosing fatty liver disease and employed the appropriate data augmentation techniques suitable for medical images to overcome the scarcity of positive samples. Three pre-trained models, namely InceptionResNetV2, EfficientNetB4, and EfficientNetV2S, were used in the study to focus on the use of transfer learning; the performance of these models was evaluated both before and after applying data augmentation techniques. After obtaining the results, the EfficientNetV2S model produced promising results for the fatty liver disease classification. F1-score, Test Accuracy, and Test Loss on the balanced dataset were 0.86, 0.93, and 0.19, respectively.

关键词： Accuracy Liver diseases Communication systems Computed tomography Transfer learning Data augmentation Data models

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USDOT Tier-1 University Transportation Center for Advancing Cybersecurity Research and Education 1

USDOT Tier-1 University Transportation Center for Advancing ...

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1st IEEE International Conference on Mobility, Operations, Services and Technologies, MOST 2023

作者： Zhang, Yunpeng Jack Wang, Kailai Song, Lingguang Lendasse, Amaury Song, Houbing Herbert Han, Zhu Verma, Rakesh Silva, Arlei Rubio-Medrano, Carlos Li, Zhixia Richard Zhang, Guohui University of Houston Dept. of Information Science Technology HoustonTX United States University of Houston Dept. of Construction Management HoustonTX United States University of Maryland Baltimore County Dept. of Information Systems BaltimoreMD United States University of Houston Dept. of Electrical & Computer Engineering HoustonTX United States University of Houston Dept. of Computer Science HoustonTX United States Rice University Dept. of Computer Science HoustonTX United States Texas A&m University-Corpus Christi Dept. of Computer Science Corpus ChristiTX United States University of Cincinnati Dept. of Civil and Architectural Engineering and Construction Management CincinnatiOH United States University of Hawai'i at Mānoa Dept. Civil and Environmental Engineering HonoluluHI United States

ISBN: (纸本)9798350319958

The Transportation Cybersecurity Center for Advanced Research and Education (CYBER-CARE) is a US Department of Transportation (USDOT) Tier-1 University Transportation Center (UTC) funded in 2023. CYBER-CARE primarily focuses on the USDOT statutory research priority area of 'Reducing Transportation Cybersecurity Risks.' CYBER-CARE aims to establish a fundamental knowledge basis and explore advanced theory to mitigate the impacts of large-scale cyberattacks on transportation infrastructure and connected and automated vehicle (CAV) systems. The research projects at CYBER-CARE will develop conceptual frameworks, construct comprehensive datasets, explore novel analytical approaches, support the implementation of public policies and infrastructure investments, and build a high-quality industry workforce through education. All CYBER-CARE research projects can be organized into four thrusts: CAV cybersecurity, transportation data security, advanced traffic management system (ATMS) cybersecurity, and next-generation transportation cybersecurity systems. In addition, CYBER-CARE will accelerate industry collaborations, foster new technologies, and provide professionals with the skills and opportunities needed to become successful leaders in their fields. Notably, as CYBER-CARE will prioritize engagement with underrepresented minorities, these communities stand to benefit from professional development training in transportation cybersecurity. © 2023 IEEE.

关键词： technology transfer

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Demonstration of a Networked Music Performance Experience with MEVO

arXiv

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arXiv 2024年

作者： Severi, Leonardo Sacchetto, Matteo Bianco, Andrea Rottondi, Cristina Knapińska, Aleksandra Lechowicz, Piotr Dept. of Electronics and Telecommunications Politecnico di Torino Turin Italy Dept. of Systems and Computer Networks Wroclaw University of Science and Technology Wroclaw Poland

In this paper we present a Networked Music Performance system currently under development at Politecnico di Torino. We demonstrate its use in a distributed concert held in June 2023, which featured three musicians in Turin (Italy) and three musicians in Wroclaw (Poland). Although in its early stages, the system proved to be already stable enough to appear transparent to the remote audience. © 2024, CC BY-NC-ND.

关键词： Audio acoustics

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Using Ethereum Platform to Securely Register Students' Extracurricular Activities

Using Ethereum Platform to Securely Register Students' Extra...

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IEEE Southeastcon

作者： Chafic W. Bou-Saba Alexis Guillen Computer Technology & Informtion Systems Dept. Guilford College Greensboro NC USA

An official transcript is a document that is produced by the registrar's office and that provides a complete representation of a student's academic record. Yet, an official transcript does not record any of the student's extracurricular activities despite the fact that such activities can shape the student's personal and professional development. It is usually the student's responsibility to keep a running log to document the attended events and the participated activities, their dates and locations, and the number of participants in such activities. These activities, not only improve the student's communications level, expand the learned skills, and develop the pursued interests, but also open the door to present an in-dept. path of the student's professional and personal growth. However, students in general, have hard time documenting and providing proof of all of their extracurricular activities during their educational years. This project addresses and solves this problem and present an innovative, reliable, secure, and even portable (possibly across educational institutions) solution. Our solution encompasses a decentralized Web3 App (dApp), Ethereum smart contract and blockchain, and Metamask crypto wallet. The dApp registers the students' activities using tokens applied to smart contracts that are saved/inserted on the Ethereum blockchain. The student can then use the combination of Etherscan block explorer and the crypto wallet's public address, to provide a detailed and certified extracurricular transcript or log of the extracurricular activities participated in or attended. The extracurricular transcript could be requested by a recruiter or an employee of the human resources department as a part of the hiring process or a promotion.

关键词： Codes Shape Smart contracts Documentation Decentralized applications Software Blockchains

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Blockchain Based Digital Forensic Data for Unbreakable Trust and Security

Blockchain Based Digital Forensic Data for Unbreakable Trust...

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IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)

作者： M. Imrankhan M. Viji R. Sathishkumar T. Gnanaprakash R. Karthik Roshan G. Saravanan Dept. of CSE Manakula Vinayagar Institute of Technology Puducherry Dept. of Computer Science and Business Systems Sri Manakula Vinayagar Engineering College Puducherry

ISBN: (数字)9798331510022

ISBN: (纸本)9798331510039

This can be one of the most magnificent advantages realized from applying blockchain technology in a forensic investigation context, namely, a transformative approach to address challenges embedded within legal and criminal justice systems. For example, smart contracts, being self-executing agreements with the automated inclusion of predefined rules, may even automate and secure the process of tracking evidence, managing chain of custody, and access control. This smart contract will ensure that forensic operations are transparent and of sound integrity. Every transaction and action performed on the blockchain is recorded there, instantaneously bringing down tampering to the lowest possibility and any chance for human mistakes. Regarding decentralized nature and cryptography-based security combined with immutability, blockchain is a technology known to have safeguards over sensitive data. Once recorded on the blockchain, the information thereupon becomes completely un-changeable, assuring the reliability and authenticity of evidence. This will be especially important in the management of an unforgeable chain of custody and in ensuring that forensic evidence remains unchanged and can be relied on with integrity throughout the court process.[6] Critical data can then be maintained tamper-proof for management and storage by developing Ethereum-based smart contracts on Remix IDE using Solidity.[15]Each transaction will be time-stamped and safely logged on the Ethereum blockchain, thus developing an unchallenged ledger that makes any investigation that much more trustworthy. In a nutshell, the application of blockchain in forensic activities builds greater control and efficiencies, reduces possible errors and conflicts, and provides transparency, integrity, and an unchangeable, permanent record for forensic processes. The invention thereby significantly upgrades the general integrity and confidence in legal and criminal justice inquiries.

关键词： Technological innovation Forensics Smart contracts Digital forensics Process control Market research Blockchains Reliability Protection Standards

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Exploring Key Factors Driving QR Payment Adoption in Digital Banking in Indonesia

Exploring Key Factors Driving QR Payment Adoption in Digital...

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International Conference on Cyber and IT Service Management (CITSM)

作者： Marchesa Ruisli Marviola Hardini Yulia Putri Ayu Sanjaya Padeli Harry Agustian Dept. of Information Technology University of Raharja Tangerang Indonesia Dept. of Retail Management University of Raharja Tangerang Indonesia Dept. of Computer Systems University of Raharja Tangerang Indonesia

ISBN: (数字)9798331528799

ISBN: (纸本)9798331528805

Technological progress within the banking industry has facilitated the extensive adoption of digital payment solutions, particularly those utilizing QR codes. Although these methods offer convenience and efficiency, significant hurdles remain in securing widespread consumer endorsement. This study analyzes factors influencing the intention to adopt QR payments, focusing on Perceived Ease of Use, Perceived Usefulness, technology Readiness, Trust in technology, and Behavioral Intention. Using Structural Equation Modeling (SEM) with SmartPLS, the study surveyed 400 digital banking users in Indonesia. Results reveal that perceived ease of use and usefulness significantly impact behavioral intention to adopt QR payments. Additionally, tech-nology readiness and trust in technology are critical drivers of adoption. The findings emphasize that enhancing QR payment adoption requires not only technological advancements but also ensuring user-friendliness and trust, which are statistically signif-icant factors in driving adoption, as demonstrated by the p-value <0.01 in our analysis.

关键词： Industries Numerical analysis Green products Banking QR codes Software systems Mathematical models User experience Security Sustainable development

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Assessment of IT Governance Maturity Level for Yemeni Telecom Sector Using COBIT 2019 Framework 1

Assessment of IT Governance Maturity Level for Yemeni Teleco...

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1st International Conference on Emerging Technologies for Dependable Internet of Things, ICETI 2024

作者： Ghallab, Abdullatif Alswari, Tahani Alhazbi, Saleh Al-Fuhaidi, Belal Hadwan, Mohammed Al-Fahaidy, Farouk Al-Dowail, Mohammed Maqtary, Naseebah Department of Computer Science University of Science and Technology Sana’a Yemen Department of IT Open University Malaysia Sana’a Yemen Dept. of Computer Science & Eng. Qatar University Doha Qatar Department of IT Qassim University Buraydah Saudi Arabia Department of Electrical Engineering Ibb University Ibb Yemen Department of Information Systems University of Science and Technology Sana’a Yemen

ISBN: (纸本)9798331533557

Information technology (IT) plays a crucial role in business operations most organizations rely on IT resources for gaining competitive advantages and creating innovative and continuous values. This increased the importance of enterprise IT governance (EGIT) and developed the recent version of the control objectives for information and related technology (COBIT), COBIT 2019 framework. It identifies the seven components of an effective EGIT system: processes, organizational structures, information flows and items, people, skills and competencies, policies and procedures, culture, ethics and behavior, services, infrastructure, and applications. The EGIT maturity level (ITGML) assessment helps to align the EGIT with strategic objectives. This study aims to assess the ITGML of the Yemeni telecom sector using COBIT 2019 framework. A quantitative method was applied, with a 73.6% response rate (148 out of 201 questionnaires collected). The study revealed that the current ITGML is 3.48, reflecting a defined maturity level. The findings suggested that IT governance practices based on COBIT 2019 are well documented and standardized within the Yemeni telecom sector. © 2024 IEEE.

关键词： Telecommunication industry

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