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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Li, Jiawei Wang, Dawei Zhang, Jiankang Alfarraj, Osama He, Yixin Al-Rubaye, Saba Yu, Keping Mumtaz, Shahid Northwestern Polytechnical University School of Electronics and Information Xi'an710072 China Bournemouth University Department of Computing and Informatics United Kingdom Jiaxing University College of Information Science and Engineering Jiaxing314001 China Cranfield University School of Aerospace Transport and Manufacturing United Kingdom King Saud University Community College Department of Computer Science Riyadh11437 Saudi Arabia Hosei University School of Science and Engineering Tokyo184-8584 Japan Silesian University of Technology Department of Applied Informatics Gliwice44-100 Poland Nottingham Trent University Departement of Computer Sciences United Kingdom

ISBN: (纸本)9798350351255

This paper investigates the secure transmissions in the Unmanned Aerial Vehicle (UAV) communication network facilitated by a Reconfigurable Intelligent Surface (RIS). In this network, the RIS acts as a relay, forwarding sensitive information to the legitimate receiver while preventing eavesdropping. We optimize the positions of the UAV at different time slots, which gives another degree to protect the privacy information. For the proposed network, a secrecy rate maximization problem is formulated. The non-convex problem is solved by optimizing the RIS's phase shifts and UAV trajectory. The RIS phase shift optimization problem is converted into a series of subproblems, and a non-linear fractional programming approach is conceived to solve it. Furthermore, the first-order taylor expansion is employed to transform the UAV trajectory optimization into convex function, and then we use the deep Q-network (DQN) method to obtain the UAV's trajectory. Simulation results show that the proposed scheme enhances the secrecy rate by 18.7% compared with the existing approaches. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Visual saliency guided normal enhancement technique for 3D shape depiction

Visual saliency guided normal enhancement technique for 3D s...

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作者： Miao, Yongwei Feng, Jieqing Pajarola, Renato College of Computer Science and Technology Zhejiang University of Technology Hangzhou 310023 China State Key Laboratory of CAD and CG Zhejiang University Hangzhou 310027 China Department of Informatics University of Zürich Zürich CH-8050 Switzerland

Visual saliency can effectively guide the viewer's visual attention to salient regions of a 3D shape. Incorporating the visual saliency measure of a polygonal mesh into the normal enhancement operation, a novel saliency guided shading scheme for shape depiction is developed in this paper. Due to the visual saliency measure of the 3D shape, our approach will adjust the illumination and shading to enhance the geometric salient features of the underlying model by dynamically perturbing the surface normals. The experimental results demonstrate that our non-photorealistic shading scheme can enhance the depiction of the underlying shape and the visual perception of its salient features for expressive rendering. Compared with previous normal enhancement techniques, our approach can effectively convey surface details to improve shape depiction without impairing the desired appearance. © 2011 ElsevierLtd. Allrightsreserved.

关键词： Behavioral research

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Web-Based Intuitive and Effective Design of Symmetric Tiles 00

Web-Based Intuitive and Effective Design of Symmetric Tiles

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2000 ACM Workshops on Multimedia, MULTIMEDIA 2000

作者： Akleman, Ergun Chen, Jianer Meric, Burak Visualization Sciences Department of Architecture Texas A&M University College StationTX United States Department of Computer Science Texas A&M University College StationTX United States Knowledge Based Information Systems Inc. College StationTX77845 United States

ISBN: (纸本)9781581133110

This paper presents a new approach for intuitive and effective design of periodic symmetric tiles. We observe that planar graphs can effectively represent symmetric tries and graph drawing provides an intuitive paradigm for designing symmetric tiles. Moreover, based on our theoretical work to represent hexagonal symmetry by rectangular symmetry, we are able to present all symmetric tiles as graphs embedded on a torus and based on simple modulo operations. This approach enables us to develop a simple and efficient algorithm, which has been implemented in Java. By using this software, designers, architects and artists can create interesting symmetric tiles directly on the web. We also have designed a few examples of symmetric tiles to show the effectiveness of the approach. Copyright © ACM 2000.

关键词： Drawing (graphics)

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Multi-Criteria Decision Making for Machine Learning Algorithms Using AHP-VIKOR techniques: Case Study Adult Autism Diagnosis 5

Multi-Criteria Decision Making for Machine Learning Algorith...

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5th International Conference on Engineering Technology and its Applications, IICETA 2022

作者： Jassim, Mustafa Mohammed Ali, Manar Hassan Elamer, Amer S. Jaber, Mustafa Musa Mohammed, Mohammed Q. Alkhayyat, Ahmed Al-Farahidi University Department of Medical Instruments Engineering Techniques Baghdad10021 Iraq Institute for Postgraduate Studies Iraqi Commission for Computers and Informatics Informatics Baghdad10011 Iraq Dijlah University Collage Department of Computer Science Baghdad10021 Iraq Al-Esraa University College Department of Information Technology Baghdad10021 Iraq The Islamic University College of Technical Engineering Najaf Iraq

ISBN: (纸本)9781665472159

autism spectrum disorder is known as a neurodevelopmental disorder with sensory problems. Many infected adults die frequently due to the psychological conditions they live in. Machine learning helps doctors detect cases of autism spectrum disorders in adults. It has proven very successful in this field. In this study, after pre-processing and solving the data class imbalance problem the data we proposed to use MCDM methods to know prioritization and the best method to diagnose autism between four algorithms (SVM, Random Forest, Neural Network, and KNN), after obtaining the classification results we utilized AHP method to assign weights to each classification performance metrics based on expert assessment then he used both the obtained weights and the classification results to enter them into the VIKOR method to make a decision based on the weighted table where we would get the ranking of the algorithms. The random Forest method scores the best in this classification for diagnosing autism, with an accuracy rate of 0.9957 and sensitivity 0.9841. © 2022 IEEE.

关键词： Decision trees

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New Algorithms for the Detection of Malicious Traffic in 5G-MEC

New Algorithms for the Detection of Malicious Traffic in 5G-...

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IEEE Conference on Wireless Communications and Networking

作者： Omesh A Fernando Hannan Xiao Joseph Spring Department of Computer Science University of Hertfordshire Hatfield UK Department of Informatics King’s College London London UK

This paper presents a new Intrusion Detection System (IDS) using a 3 layer Convolutional Neural Network (CNN), capable of identifying malicious network traffic. We employ a new injective algorithm to encode network traffic without loss of information. We also include a new algorithm to decode, encoded RGB images back into network traffic. We evaluate the proposed IDS in terms of its computational complexity in for example: time, memory and CPU utilisation for the encoding and decoding algorithms, and its accuracy and loss during training and detection. Lastly, we compare the proposed IDS against a significant IDS algorithm that uses a different approach for encoding, decoding and CNN detection.

关键词： Training Image coding Neural networks Intrusion detection Telecommunication traffic Encoding Decoding

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Blockchain Based Dead Reckoning navigation system for Fault detection and secure Communication over VANET

Blockchain Based Dead Reckoning navigation system for Fault ...

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2023 International Conference on New Frontiers in Communication, Automation, Management and Security, ICCAMS 2023

作者： Byeon, Haewon Keshta, Ismail Mahalakshmi, V. Soni, Mukesh Khan, Ihtiram Raza Maranan, Ramya Inje University Department of Digital Anti-Aging Healthcare Gimhae50834 Korea Republic of AlMaarefa University College of Applied Sciences Computer Science and Information Systems Department Riyadh Saudi Arabia Jazan University College of Computer Science & Information Technology Department of Computer Science Jazan Saudi Arabia Dr. D. Y. Patil Vidyapeeth Pune Dr. D. Y. Patil School of Science & Technology Tathawade Pune India Academician Jamia Hamdard Delhi India Saveetha School of Engineering Simats Department of Research and Innovation Tamil Nadu Chennai602105 India

ISBN: (纸本)9798350317060

This research paper presents a blockchain-based approach for fault detection and secure communication in vehicular ad hoc networks (VANETs). VANETs are an emerging technology that allows vehicles to communicate with each other and with the surrounding infrastructure to improve safety and efficiency on the roads. However, the decentralized and dynamic nature of VANETs makes them vulnerable to various types of attacks, including false data injection and communication interference. To address these challenges, the proposed approach utilizes blockchain technology to ensure the integrity and authenticity of data exchanged among vehicles and the infrastructure. The system also includes a fault detection mechanism that can detect and isolate faulty vehicles to prevent them from disrupting the communication network. However, VANETs are distinct from conventional mobile ad hoc networks due to the high mobility of vehicles, which creates dynamic network environments and frequent link interruptions that result in message loss. A hierarchical defect detection method based on dead reckoning is proposed to address these issues. The technique uses the dead reckoning model to predict the transmission time of pulse messages and builds a hierarchical detection architecture with Roadside Units (RSUs) functioning as static nodes. This architecture enhances the efficacy of VANET fault detection. The proposed method was validated by NS-2 simulations, demonstrating superior performance in terms of detection speed, accuracy, and detection burden compared to the baseline fault detection method. © 2023 IEEE.

关键词： Vehicle to vehicle communications

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Color-conversion displays:current status and future outlook

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Light(science & Applications) 2024年第12期13卷 2941-2961页

作者： Guijun Li Man-Chun Tseng Yu Chen Fion Sze-Yan Yeung Hangyu He Yuechu Cheng Junhu Cai Enguo Chen Hoi-Sing Kwok Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Physics and Optoelectronic EngineeringShenzhen UniversityShenzhen 518060China State Key Laboratory of Advanced Displays and Optoelectronics Technologies Department of Electronic and Computer EngineeringThe Hong Kong University of Science and TechnologyHong KongChina National and Local United Engineering Laboratory of Flat Panel Display Technology College of Physics and Information EngineeringFuzhou UniversityCollege of Physics and Information Engineering 350108FuzhouChina Fujian Science&Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou 350108China

The growing focus on enhancing color quality in liquid crystal displays(LCDs)and organic light-emitting diodes(OLEDs)has spurred significant advancements in color-conversion ***,color conversion is also important for the development and commercialization of *** article provides a comprehensive review of different types of color conversion methods as well as different types of color conversion *** summarize the current status of patterning process,and discuss key strategies to enhance display ***,we speculate on the future prospects and roles that color conversion will play in ultra-high-definition micro-and projection displays.

关键词： materials projection outlook

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Improving deep neural network acoustic modeling for audio corpus indexing under The IARPA Babel program 15

Improving deep neural network acoustic modeling for audio co...

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15th Annual Conference of the International Speech Communication Association: Celebrating the Diversity of Spoken Languages, INTERSPEECH 2014

作者： Cui, Xiaodong Kingsbury, Brian Cui, Jia Ramabhadran, Bhuvana Rosenberg, Andrew Rasooli, Mohammad Sadegh Rambow, Owen Habash, Nizar Goel, Vaibhava IBM T. J. Watson Research Center Yorktown HeightsNY10598 United States Department of Computer Science Queens College City University New YorkNY11367 United States Department of Computer Science Columbia University NY10027 United States Center for Computational Learning Systems Columbia University NY10115 United States

This paper is focused on several techniques that improve deep neural network (DNN) acoustic modeling for audio corpus indexing in the context of the IARPA Babel program. Specifically, fundamental frequency variation (FFV) and channelaware (CA) features and data augmentation based on stochastic feature mapping (SFM) are investigated not only for improved automatic speech recognition (ASR) performance but also for their impact to the final spoken term detection on the pre-indexed audio corpus. Experimental results on development languages of Babel option period one show that the improved DNN acoustic models can reduce word error rates in ASR and also help the keyword search performance compared to already competitive DNN baseline systems. Copyright © 2014 ISCA.

关键词： Deep neural networks

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Learning output kernels with block coordinate descent

Learning output kernels with block coordinate descent

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28th International Conference on Machine Learning, ICML 2011

作者： Dinuzzo, Francesco Ong, Cheng Soon Gehler, Peter Pillonetto, Gianluigi Max Planck Institute for Intelligent Systems 72076 Tübingen Germany Department of Computer Science ETH Zürich 8092 Zürich Switzerland Max Planck Institute for Informatics 66123 Saarbrücken Germany Department of Information Engineering University of Padova 35131 Padova Italy

ISBN: (纸本)9781450306195

We propose a method to learn simultaneously a vector-valued function and a kernel between its components. The obtained kernel can be used both to improve learning performance and to reveal structures in the output space which may be important in their own right. Our method is based on the solution of a suitable regularization problem over a reproducing kernel Hilbert space of vector-valued functions. Although the regularized risk functional is non-convex, we show that it is invex, implying that all local minimizers are global minimizers. We derive a block-wise coordinate descent method that efficiently exploits the structure of the objective functional. Then, we empirically demonstrate that the proposed method can improve classification accuracy. Finally, we provide a visual interpretation of the learned kernel matrix for some well known datasets. Copyright 2011 by the author(s)/owner(s).

关键词： Learning systems

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Feature Selection for Detecting ICMPv6-Based DDoS Attacks Using Binary Flower Pollination Algorithm

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computer systems science & Engineering 2023年第10期47卷 553-574页

作者： Adnan Hasan Bdair Aighuraibawi Selvakumar Manickam Rosni Abdullah Zaid Abdi Alkareem Alyasseri Ayman Khallel Dilovan Asaad Zebari Hussam Mohammed Jasim Mazin Mohammed Abed Zainb Hussein Arif National Advanced IPv6 Centre(NAv6) Universiti Sains MalaysiaPenang11800Malaysia Baghdad College of Economic Sciences University BaghdadIraq School of Computer Sciences Universiti Sains MalaysPenang11800Malaysia Information Technology Research and Development Center University of KufaNajafIraq College of Engineering University of Warith Al-AnbiyaaKarbalaIraq Faculty of Computing and Informatics Universiti Malaysia SabahSabahMalaysia Business Administration College of Administration and Financial SciencesImam Ja’afar Al-Sadiq UniversityBaghdad10001Iraq College of Computer Science and Information Technology University of AnbarRamadi AnbarIraq Department of Computer Science College of ScienceNawroz UniversityDuhok42001Kurdistan RegionIraq

Internet Protocol version 6(IPv6)is the latest version of IP that goal to host 3.4×10^(38)unique IP addresses of devices in the ***6 has introduced new features like Neighbour Discovery Protocol(NDP)and Address Auto-configuration ***6 needed several protocols like the Address Auto-configuration Scheme and Internet Control Message Protocol(ICMPv6).IPv6 is vulnerable to numerous attacks like Denial of Service(DoS)and Distributed Denial of Service(DDoS)which is one of the most dangerous attacks executed through ICMPv6 messages that impose security and financial ***,an Intrusion Detection System(IDS)is a monitoring system of the security of a network that detects suspicious activities and deals with amassive amount of data comprised of repetitive and inappropriate features which affect the detection rate.A feature selection(FS)technique helps to reduce the computation time and complexity by selecting the optimum subset of *** paper proposes a method for detecting DDoS flooding attacks(FA)based on ICMPv6 messages using a Binary Flower PollinationAlgorithm(BFPA-FA).The proposed method(BFPA-FA)employs FS technology with a support vector machine(SVM)to identify the most relevant,influential ***,The ICMPv6-DDoS dataset was used to demonstrate the effectiveness of the proposed method through different attack *** results show that the proposed method BFPAFA achieved the best accuracy rate(97.96%)for the ICMPv6 DDoS detection with a reduced number of features(9)to half the total(19)*** proven proposed method BFPA-FAis effective in the ICMPv6 DDoS attacks via IDS.

关键词： IPv6 ICMPv6 DDoS feature selection flower pollination algorithm anomaly detection

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