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2nd International Conference on Information science and Education, ICISE-IE 2021

作者： Chen, Huan Liu, Ying Shan, Chan Zhang, Hequn School of Journalism and Communication of Minjiang University Fujian Fuzhou350108 China Department of Software Technology Xiamen Institute of Software Technology Fujian Xiamen China Department of Computer System and Technology Faculty of Computer Science and Information Technology Universiti Malaya Kuala Lumpur50603 Malaysia College of Information Engineering Jimei University Xiamen361021 China

ISBN: (纸本)9781665438292

In the era of rapid development of intelligent technology, the children's digital publishing industry is facing a disruptive change, and this change may be realized through the reconstruction of the supply and demand chain. The value power of source content creation and the ability to gather users have been deconstructed. The increase in the amount of content requires platform institutions to have a more professional content operation system. The convenience of payment technology has greatly increased the digital content payment rate of users of children's digital products. A development model of the supply and demand chain of children's digital publishing with more innovative flexibility and enabling effects. © 2021 IEEE

关键词： Economics

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Towards an Intelligent Industrial Environment: Blockchain-Empowering Human-Centered Artificial Intelligence for Risk Assessment and Strategic Evaluation

SSRN

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SSRN 2023年

作者： Khan, Abdullah Ayub Chen, Yen-Lin Hajjej, Fahima Shaikh, Aftab Ahmed Yang, Jing Ku, Chin Soon Por, Lip Yee Department of Computer Science and Information Technology Benazir Bhutto Shaheed University Lyari Sindh Karachi75660 Pakistan Department of Computer Science Sindh Madressatul Islam University Sindh Karachi74000 Pakistan Department of Computer Science and Information Engineering National Taipei University of Technology Taipei106344 Taiwan Department of Software Engineering College of Computer and Information Sciences Princess Nourah bint Abdulrahman University P.O.Box 84428 Riyadh11671 Saudi Arabia Department of Computer System and Technology Faculty of Computer Science and Information Technology Universiti Malaya Kuala Lumpur50603 Malaysia Department of Computer Science Universiti Tunku Abdul Rahman Kampar31900 Malaysia

With the recent introduction of high-level human control and high-level IoT control in intelligent transportation systems, their association with blockchain increases the performance of the Internet of Vehicles (IoVs) and E-Healthcare, which leads to wider adaptation in the future as well. In this paper, the contributions of this systematic article are divided into three different folds: first, this paper evaluates more than a hundred previously published articles and highlights the gaps in futuristic concerns. Second, the paper presents a novel and secure human-centered AI-enabled risk assessment framework for the IoVs with blockchain distributed ledger technology (DLT). Third, a distributed public permissionless network with two operational channels of inter-communication for vehicle-to-vehicle (V2V) is proposed. It is considered an extension in the Vehicle-to-Everything (V2X) environment. Along with that, the pseudo-development of chaincodes to automate human-centered IoV node transactions. In addition, a Practical Byzantine Fault Tolerance (PBFT) consensus protocol and related controlled executions are programmed for fast scheduling, offloading, managing, and optimizing with reliability. © 2023, The Authors. All rights reserved.

关键词： Blockchain

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Implementation-First Approach of Developing Formal Semantics of a Simulation Language in VDM-SL

arXiv

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arXiv 2023年

作者： Oda, Tomohiro Dur, Gaël Ducasse, Stéphane Macedo, Hugo Daniel Software Research Associates Inc. Japan Faculty of Science Shizuoka University Japan Univ. Lille Inria CNRS Centrale Lille UMR 9189 CRIStAL France Aarhus University DIGIT Department of Electrical and Computer Engineering Denmark

Formal specification is a basis for rigorous software implementation. VDM-SL is a formal specification language with an extensive executable subset. Successful cases of VDM-family including VDM-SL have shown that producing a well-tested executable specification can reduce the cost of the implementation phase. This paper introduces and discusses the reversed order of specification and implementation. The development of a multi-agent simulation language called RE:MOBIDYC is described and examined as a case study of defining a formal specification after initial implementation and reflecting the specification into the implementation code. © 2023, CC BY.

关键词： Specification languages

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Spatial release from masking in varying spatial acoustic under higher order Ambisonic-based sound reproduction system 50

Spatial release from masking in varying spatial acoustic und...

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50th International Congress and Exposition of Noise Control engineering, INTER-NOISE 2021

作者： Hui, C.T. Justine Hioka, Yusuke Watson, Catherine I. Masuda, Hinako Acoustics Research Centre Department of Mechanical Engineering University of Auckland Auckland1010 New Zealand Department of Electrical Computer and Software Engineering University of Auckland Auckland1010 New Zealand Faculty of Science and Technology Seikei University Tokyo180-8633 Japan

ISBN: (纸本)9781732598652

A previous study found that spatial release from masking (SRM) could be observed under virtual reverberant environments using a first order Ambisonic-based sound reproduction system, however, poor localisation accuracy made it difficult to examine effect of varying reverberation time on SRM. The present study follows on using higher order Ambisonics (HOA) to examine how benefits from SRM vary in different spatial acoustics. Subjective speech intelligibility was measured where four room acoustics:reverberation time (RT)= 0.7 s (clarity (C50)= 15.9 dB, 6.8 dB);RT= 1.7 s (C50= 10.3 dB, 3.3 dB) were simulated via a third order Ambisonics system with a 16 channel spherical loudspeaker array. The masker was played from 8 azimuthal angles (0, ±45, ±90, ±135, 180 degrees) while the target speech was played from 0 degree. The listeners are deemed to benefit from SRM if their intelligibility scores were higher when the masker was projected from a different angle than that of the target. We found while listeners could benefit from SRM at C50 = 15.9 dB and 10.3 dB, the benefit starts to diminish at C50 = 6.8 dB, and listeners could no longer benefit from SRM at C50 = 3.3 dB. © INTER-NOISE 2021 .All right reserved.

关键词： Reverberation

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APlus: An Intelligent Lecture Delivery System using Artificial Intelligence Learning Analytics 3

APlus: An Intelligent Lecture Delivery System using Artifici...

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3rd International Conference on Advancements in Computing, ICAC 2021

作者： Kodagoda, Charith Madampe, Vihanga Ekanayake, Ridmi De Silva, Nirma Wijesundara, Malitha Atapattu, Pramadhi Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka Faculty of Humanities and Sciences Sri Lanka Institute of Information Technology Malabe Sri Lanka Ltd Colombo Sri Lanka

ISBN: (纸本)9781665408622

As technology advances, new ways of teaching and learning can be discovered. Online learning platforms are able to provide easy, informative, and effective methods of delivering information since people are getting more accustomed to the use of e-learning. With the help of Artificial Intelligence, these methods can be refined to understand the users on a deeper level and provide services that are helpful and are more tailored to each user. The purpose of this project is to design an e-learning platform equipped for both educators and students. The system will be able to allow users to record/upload lecture sessions and other related study materials to the service which in return, with the use of Artificial Intelligence, try to understand the context of each lesson, segment videos, generate questions and deliver the materials to the Learner. The system will use various inputs from the Learner including video observation time, watched duration, types of videos watched, answers for questions, etc. to build a comprehensive profile of Learners. The system will use the knowledge gathered to provide services such as recommendations to the Learner, track the progress of the Learner as well as provide useful statistics of lecture materials to the Content Providers. © 2021 IEEE.

关键词： Learning systems

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MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining

arXiv

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arXiv 2024年

作者： Wang, Di Zhang, Jing Xu, Minqiang Liu, Lin Wang, Dongsheng Gao, Erzhong Han, Chengxi Guo, Haonan Du, Bo Tao, Dacheng Zhang, Liangpei School of Computer Science Wuhan University Wuhan430072 China Institute of Artificial Intelligence Wuhan University Wuhan430072 China National Engineering Research Center for Multimedia Software Wuhan University Wuhan430072 China Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan University Wuhan430072 China School of Computer Science Faculty of Engineering The University of Sydney Australia iFlytek Co Ltd National Engineering Research Center of Speech and Language Information Processing Hefei230088 China State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan430079 China School of Computer Science and Engineering Nanyang Technological University Singapore Singapore

Foundation models have reshaped the landscape of Remote Sensing (RS) by enhancing various image interpretation tasks. Pretraining is an active research topic, encompassing supervised and self-supervised learning methods to initialize model weights effectively. However, transferring the pretrained models to downstream tasks may encounter task discrepancy due to their formulation of pretraining as image classification or object discrimination tasks. In this study, we explore the Multi-Task Pretraining (MTP) paradigm for RS foundation models to address this issue. Using a shared encoder and task-specific decoder architecture, we conduct multi-task supervised pretraining on the SAMRS dataset, encompassing semantic segmentation, instance segmentation, and rotated object detection. MTP supports both convolutional neural networks and vision transformer foundation models with over 300 million parameters. The pretrained models are finetuned on various RS downstream tasks, such as scene classification, horizontal and rotated object detection, semantic segmentation, and change detection. Extensive experiments across 14 datasets demonstrate the superiority of our models over existing ones of similar size and their competitive performance compared to larger state-of-the-art models, thus validating the effectiveness of MTP. The codes and pretrained models will be released at https://***/ViTAE-Transformer/MTP. Copyright © 2024, The Authors. All rights reserved.

关键词： Object detection

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A systematic review and meta-data analysis of clinical data repositories in Africa and beyond: recent development, challenges, and future directions

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Discover Data 2024年第1期2卷 1-39页

作者： Adewole, Kayode S. Alozie, Emmanuel Olagunju, Hawau Faruk, Nasir Aliyu, Ruqayyah Yusuf Imoize, Agbotiname Lucky Abdulkarim, Abubakar Imam-Fulani, Yusuf Olayinka Garba, Salisu Baba, Bashir Abdullahi Hussaini, Mustapha Oloyede, Abdulkarim A. Abdullahi, Aminu Kanya, Rislan Abdulazeez Usman, Dahiru Jafaru Department of Computer Science University of Ilorin Ilorin Nigeria Department of Information Technology Sule Lamido University Kafin Hausa Nigeria Department Information and Media Studies Faculty of Communication Bayero University Kano Nigeria Department of Electrical and Electronics Engineering Faculty of Engineering University of Lagos Lagos Nigeria Department of Electrical Engineering Ahmadu Bello University Zaria Nigeria Department of Electrical and Telecommunications Engineering Kampala International University Kampala Uganda Department of Telecommunication Science University of Ilorin Ilorin Nigeria Department of Software Engineering Sule Lamido University Kafin Hausa Kafin Hausa Nigeria Department of Cyber Security Sule Lamido University Kafin Hausa Kafin Hausa Nigeria Department of Economics Faculty of Social and Management Sciences Kafin Hausa Nigeria Department: University Medical Services Sule Lamido University Kafin Hausa Kafin Hausa Nigeria Department of Computer Science and Information Technology Baze University Abuja Nigeria Department: International Law and Jurisprudence Faculty of Law Bayero University Kano Nigeria

A Clinical Data Repository (CDR) is a dynamic database capable of real-time updates with patients' data, organized to facilitate rapid and easy retrieval. CDRs offer numerous benefits, ranging from preserving patients' medical records for follow-up care and prescriptions to enabling the development of intelligent models that can predict, and potentially mitigate serious health conditions. While several research works have attempted to provide state-of-the-art reviews on CDR design and implementation, reviews from 2013 to 2023 cover CDR regulations, guidelines, standards, and challenges in CDR implementation without providing a holistic overview of CDRs. Additionally, these reviews need to adequately address critical aspects of CDR; development and utilization, CDR architecture and metadata, CDR management tools, CDR security, use cases, and artificial intelligence (AI) in CDR design and implementation. The collective knowledge gaps in these works underscore the imperative for a comprehensive overview of the diverse spectrum of CDR as presented in the current study. Existing reviews conducted over the past decade, from 2013 to 2023 have yet to comprehensively cover the critical aspects of CDR development, which are essential for uncovering trends and potential future research directions in Africa and beyond. These aspects include architecture and metadata, security and privacy concerns, tools employed, and more. To bridge this gap, in particular, this study conducts a comprehensive systematic review of CDR, considering critical facets such as architecture and metadata, security and privacy issues, regulations guiding development, practical use cases, tools employed, the role of AI and machine learning (ML) in CDR development, existing CDRs, and challenges faced during CDR development and deployment in Africa and beyond. Specifically, the study extracts valuable discussions and analyses of the different aspects of CDR. Key findings revealed that most architectural mod

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Locally differentially private distributed algorithms for set intersection and union

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science China(Information sciences) 2021年第11期64卷 234-236页

作者： Qiao XUE Youwen ZHU Jian WANG Xingxin LI Ji ZHANG College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Collaborative Innovation Center of Novel Software Technology and Industrialization Faculty of Health Engineering and Science University of Southern Queensland

Dear editor,Privacy-preserving distributed set intersection and union(PPSI, PPSU) have received much attention in recent years because of their wide applications. Most of existing solutions [1, 2] utilize secure multiparty computation protocols(SMCP) [3, 4] to settle the problem, but the SMCP methods are expensive in computation and communication. Even worse, most SMCP methods hardly continue to work if some participants disconnect.

关键词： Information Systems and Communication Service

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Backscatter Communication-Based Wireless Sensing (BBWS): Performance Enhancement and Future Applications

TechRxiv

引用

TechRxiv 2022年

作者： Toro, Usman Saleh ElHalawany, Basem M. Wong, Aslan B. Wang, Lu Wu, Kaishun Shenzhen University College of Computer Science and Software Engineering Gaungdong Shenzhen518060 China Information Hub Gaungdong Guangzhou511453 China Benha University Faculty of Engineering at Shoubra Cairo11629 Egypt

Wireless Sensing (WS) provides a low-cost means of monitoring humans and objects for the next generation of IoT. However, the deployment of WS for various applications is limited by;the heterogeneous nature of underlying technology in IoT devices, limited battery, and computational power of sensing devices. Backscatter Communication (BackCom) enables wireless sensing and communication by reflecting wireless signals (such as radio frequency (RF), acoustic and visible light (VL)) from a source to a receiver using a backscatter tag at an ultra-low (microwatt) power level. Hence, backscatter communication-based wireless sensing (BBWS) could enable ubiquitously and battery-free applications (such as human and plant physiology, orientation sensing, and localization). Despite existing surveys and literature on BackCom, a study on leveraging BackCom for WS is still lacking. This paper takes the first approach in discussing applications of BackCom in WS and techniques for enhancing performance (such as power management, channel model, range and coverage, throughput, security, quality of backscatter signal, modulation, and coding) in BBWS applications. It also discusses future sensing applications where BBWS is applicable and research issues related to such applications. © 2022, CC BY.

关键词： Internet of things

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Deep learning based DeepFake video detection

Deep learning based DeepFake video detection

引用

Smart Computing and Application (ICSCA), International Conference on

作者： Sarra Guefrachi Marwa Ben Jabra Naif A. Alsharabi Mohamed Tahar Ben Othman Yasser O. Alharabi Abdulsalam Alkholidi Habib Hammam Faculty of Engineering Université de Moncton) Moncton NB Canada Spectrum of Knowledge Production & Skills Development Sfax Tunisia Computer Engineering University of Ha'il Computer Science Amran University Yemen Ha'il KSA Department of Computer Science College of Computer) Qassim University Buraydah Saudi Arabia line Computer Science and Information College of computer sc. & engneering Ha'il University Ha'il KSA College Department of Software Engineering Canadian Institute of Technology Tirana Canada International Institute of Technology and Management Commune d'Akanda Libreville BP Ga-bon Dept of Electrical and Electronic Eng. Science School of Electrical Engineering University of Johannes-burg Tirana Canada

Recent advances in DeepFake face-swapping technology have made it simple to create fake videos that appear remarkably real. Since it has been employed in numerous instances for deceit, extortion, and the falsification of facts, its widespread use has generated a huge social, security, and political risk. Its use on websites and social media has become more widespread. Detecting this crime is becoming more and more important due to the potential harm false videos may inflict on a global scale. This research offers a method for building a deep learning model that really can tell the difference between authentic and false videos. The article describes how to create new models based on the VGG16 neural network, a previously created neural network that does image categorization, using transfer learning in the computer vision field. Deep learning is still becoming better at both producing and spotting DeepFakes. DeepFake detection algorithms are developed using dated public datasets, and as a result, they may become obsolete with time. and require continual updating. The research findings are encouraging, and our results reached an accuracy rate of over 90%.

关键词： Deep learning Deepfakes computer vision Social networking (online) Computational modeling Neural networks Transfer learning

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