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Graphene oxide-coated microbottle resonators for relative humidity sensing

Optoelectronics Letters 2024年第7期20卷 400-405页

作者： Huda Adnan Zain Malathy Batumalay Md Ashadi Md Johari Hazli Rafis Abdul Rahim Sulaiman Wadi Harun Department of Electrical Engineering Faculty of EngineeringUniversity of MalayaKuala Lumpur 50603Malaysia Faculty of Data Science and Information Technology INTI International UniversityNilai 71800Malaysia1 Faculty of Electrical and Electronic Engineering Technology Universiti Teknikal Malaysia MelakaMelaka 76100Malaysia Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia MelakaMelaka 76100Malaysia

Graphene oxide(GO)is a 2D coating material used to improve fiber optics sensors’response to relative *** resonators(MBRs)have garnered more attention as sensing media *** MBR with a 190μm diameter was coated with ***,tapered fiber light coupling was used to investigate the relative humidity sensing performance in the range of 35—70%RH at 25℃.The MBR showed a higher Q factor before and after GO *** sensitivity of 0.115 dB/%RH was recorded with the 190μm GO-coated MBR sample compared to a sensitivity of 0.022 dB/%RH for the uncoated MBR *** results show that the MBR can be used in fiber optic sensing applications for environmental sensing.

关键词： humidity oxide bottle

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Physical Layer Covert Communication in B5G Wireless Networks - its Research, Applications, and Challenges

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Proceedings of the IEEE 2024年第1期112卷 47-82页

作者： Jiang, Yu'e Wang, Liangmin Chen, Hsiao-Hwa Shen, Xuemin University Key Laboratory of Intelligent Perception and Computing of Anhui Province Anqing Normal University Anqing246011 China Southeast University School of Cyber Science and Engineering Nanjing211189 China National Cheng Kung University Department of Engineering Science Taiwan70101 Taiwan University of Waterloo Department of Electrical and Computer Engineering WaterlooN2L 3G1 Canada

Physical layer covert communication is a crucial secure communication technology that enables a transmitter to convey information covertly to a recipient without being detected by adversaries. Unlike typical cryptography and physical layer security systems that concentrate on protecting the sent signal content, covert communications seek to conceal the existence of legitimate transmission. Thus, with beyond fifth-generation (B5G) wireless communications, covert communications can operate in tandem or as a supplement to conventional security techniques. We provide an extensive overview of the basic theories and several strategies in physical layer covert communications in this article. In particular, we go into great detail about the basic theories of physical layer covert communications, such as channel models, codes, secret keys, and covertness metrics, as well as various covert schemes in progressively more complicated scenarios, such as covert communications in single-antenna and multiantenna three-node systems and covert communications in jammer- and relay-aided systems. In addition, we identify the challenges and future directions for research on covert communications in B5G wireless networks. © 1963-2012 IEEE.

关键词： Transmitters

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BIE: Binary Image Encoding for the Classification of Tabular Data

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Journal of Data science 2025年第1期23卷 109-129页

作者： Halladay, James Cullen, Drake Briner, Nathan Miller, Darrin Primeau, Riley Avila, Abraham Watson, Warin Basnet, Ram Doleck, Tenzin Department of Computer Science and Engineering Colorado Mesa University (CMU) Grand Junction 81501 CO United States Faculty of Education Simon Fraser University Burnaby V5A 1S6 BC Canada

There has been remarkable progress in the field of deep learning, particularly in areas such as image classification, object detection, speech recognition, and natural language processing. Convolutional Neural Networks (CNNs) have emerged as a dominant model of computation in this domain, delivering exceptional accuracy in image recognition tasks. Inspired by their success, researchers have explored the application of CNNs to tabular data. However, CNNs trained on structured tabular data often yield subpar results. Hence, there has been a demonstrated gap between the performance of deep learning models and shallow models on tabular data. To that end, Tabular-to-Image (T2I) algorithms have been introduced to convert tabular data into an unstructured image format. T2I algorithms enable the encoding of spatial information into the image, which CNN models can effectively utilize for classification. In this work, we propose two novel T2I algorithms, Binary Image Encoding (BIE) and correlated Binary Image Encoding (cBIE), which preserve complex relationships in the generated image by leveraging the native binary representation of the data. Additionally, cBIE captures more spatial information by reordering columns based on their correlation to a feature. To evaluate the performance of our algorithms, we conducted experiments using four benchmark datasets, employing ResNet-50 as the deep learning model. Our results show that the ResNet-50 models trained with images generated using BIE and cBIE consistently outperformed or matched models trained on images created using the previous State of the Art method, Image Generator for Tabular Data (IGTD). © 2025 The Author(s).

关键词： computer vision DeepInsight IGTD native representation ResNet-50 tabular-to-image

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Design and Analysis of Quantum Safe Virtual Private Network 4

Design and Analysis of Quantum Safe Virtual Private Network

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4th International Conference on Innovations in computer science, ICONICS 2024

作者： Saad, Muhammad Ahmed, Waseem Khan, Muhammad Mubashir NED University of Engineering & Technology Department of Computer Science & Information Technology Karachi Pakistan Engineering Department PureSquare FZ LLC Office No: 2001 Nassima Tower Trade Centre 1 Sheikh Zayed Road Dubai United Arab Emirates

ISBN: (纸本)9798331504342

The start of quantum computing poses a significant security threat to the existing Virtual Private Networks that reinforce secure communication on the internet. Quantum computers have the potential to break widely used encryption algorithms, such as RSA and ECC, by efficiently solving complex mathematical problems. Therefore, there is an urgent need to develop and analyze quantum-safe alternatives for Virtual Private Networks. This thesis embarks on a journey of quantum-safe algorithms and how we used to design and implement them to make a quantum-safe VPN environment, aiming to path towards a secure digital future. In this thesis, we have designed a quantum-safe VPN and then analyzed how it works compared to traditional VPNs. We used NIST's algorithms: Dilithium3 for digital signatures. © 2024 IEEE.

关键词： Quantum computers

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Recurrent Neural Network-based Modeling Approach for 4D Printing Design : Long sequence prediction based on short sequences

Recurrent Neural Network-based Modeling Approach for 4D Prin...

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2024 International Conference on Advanced Mechatronic Systems, ICAMechS 2024

作者： Xu, Yifan Wang, Mengtao Wang, Zhongkui Meng, Lin Ritsumeikan University Graduate School of Science and Engineering 1-1-1 Noji-higashi Kusatsu Shiga525-8577 Japan Ritsumeikan University Department of Robotics 1-1-1 Noji-higashi Kusatsu Shiga525-8577 Japan Ritsumeikan University Department of Electronic and Computer Engineering 1-1-1 Noji-higashi Kusatsu Shiga525-8577 Japan

ISBN: (纸本)9798350366204

This study presents a method for predicting the deformation of hydrogel models fabricated by four-dimensional printing technology using deep learning. In this method, a large number of hydrogel models with the same shape but different distributions of length and expansion ratio are first created using the modeling software Abaqus. Then, deformation simulations are performed based on finite element analysis using the thermal expansion method, and the simulation results are processed and organized to create a data set. Afterward, a recurrent neural network (RNN) was created and trained using a composite dataset consisting of multiple hydrogel model sequences of different lengths to enable the RNN to learn model deformation features and, accordingly, predict the deformation of various longer sequences of hydrogels in a very short period of time while recording the change in accuracy of the prediction for each length. This research provides a new approach to modeling and inverse design for 4D printing technology. © 2024 IEEE.

关键词： Prediction models

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Deep Learning-Based Decision-Making of Autonomous Vehicles to Predict Accidents

Deep Learning-Based Decision-Making of Autonomous Vehicles t...

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2023 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2023

作者： Khanum, Abida Lee, Chao-Yang Yang, Chu-Sing National Cheng Kung University No.1 Department of Electrical Engineering Tainan City701 Taiwan National Yunlin University of Science and Technology Department of Computer Science and Information Engineering National Formosa University Yunlin Taiwan

ISBN: (纸本)9798350313154

The autonomous vehicle system ensures safe driving by certainly controlling a vehicle's motion in the lane to reduce the risk of a collision. The proposed architecture is based on convolutional neural network (CNN) deep learning-based with three convolutional blocks. As output, the CNN framework can predict three different risk factor evaluations, i.e., high risk, medium risk, and low risk, used to predict the accident of the AV. The deep learning-based network had a better accuracy rate and computing time for all MTs with a 70% accuracy rate and an 8-ms computing time for risk prediction in autonomous vehicles. The experimental accuracy demonstrates that our trained method has fruitfully accurate results. The self-driving vehicle model successfully predicts the accident risk during driving a vehicle on the road. © 2023 IEEE.

关键词： Decision making

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Application of a High Power Fabry-Perot QW Laser Diode on Multi-Channel Coherent Optical System

Application of a High Power Fabry-Perot QW Laser Diode on Mu...

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CLEO: science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Ghosh, Shalmoli Raisa, Sharmila O'Sullivan, Maurice Laperle, Charles Hui, Rongqing Department of Electrical Engineering and Computer Science University of Kansas LawrenceKS66045 United States Ciena Corporation NepeanONK2K 0L1 Canada

We investigate the property of a Fabry-Perot quantum-well laser diode which emits multiple spectral lines with a total power exceeding 120mW. We show its application as an optical source in a multi-channel coherent op... 详细信息

关键词： Fabry-Perot interferometers

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Application of a High Power Fabry-Perot QW Laser Diode on Multi-Channel Coherent Optical System

Application of a High Power Fabry-Perot QW Laser Diode on Mu...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

ISBN: (纸本)9781957171395

关键词： Fabry-Perot interferometers

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Joint Class-Balanced Client Selection and Bandwidth Allocation for Cost-Efficient Federated Learning in Mobile Edge Computing Networks

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IEEE Transactions on Mobile Computing 2025年第7期24卷 5681-5698页

作者： Tang, Jian Li, Xiuhua Li, Hui Li, Penghua Wang, Xiaofei Leung, Victor C. M. Chongqing University School of Big Data & Software Engineering Chongqing400000 China Chongqing University of Posts and Telecommunications School of Automation Chongqing400065 China Tianjin University College of Intelligence and Computing Tianjin300072 China Shenzhen MSU-BIT University Artificial Intelligence Research Institute Shenzhen518172 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T1Z4 Canada

Federated Learning (FL) has significant potential to protect data privacy and mitigate network burden in mobile edge computing (MEC) networks. However, due to the system and data heterogeneity of mobile clients (MCs), client selection and bandwidth allocation is key for achieving cost-efficient FL in MEC networks with limited bandwidth. To address these challenges, we investigate the issue of joint client selection and bandwidth allocation for reducing the cost (i.e., latency and energy consumption) of FL training. We formulate the problem and decompose it into a holistic subproblem to reduce the number of rounds and a partial subproblem to reduce the costs of FL each round. We propose a joint class-balanced client selection and bandwidth allocation (CBCSBA) framework to address the whole problem. Specifically, for the holistic subproblem, CBCSBA combines MCs into groups, each having data distribution as close as possible to class-balanced distribution;For the partial subproblem, CBCSBA reduces costs by exploratively selecting a group and sequentially optimizing the latency and energy consumption of MCs within the group. Experimental results show that CBCSBA outperforms the baseline frameworks in reducing latency by 28.2% and energy consumption by 25.3% on average in the considered four datasets. © 2002-2012 IEEE.

关键词： Federated learning

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Efficient Joint Key Authentication Model in E-Healthcare

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computers, Materials & Continua 2022年第5期71卷 2739-2753页

作者： Muhammad Sajjad Tauqeer Safdar Malik Shahzada Khurram Akber Abid Gardezi Fawaz Alassery Habib Hamam Omar Cheikhrouhou Muhammad Shafiq Department of Computer Science Air University Multan CampusMultan60000Pakistan Faculty of Computing The Islamia University of BahawalpurBahawalpur 63100Pakistan Department of Computer Science COMSATS University IslamabadIslamabadPakistan Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaifSaudi Arabia Faculty of Engineering Moncton UniversityNBE1A3E9Canada CES Laboratory National School of Engineers of SfaxUniversity of SfaxSfax3038Tunisia Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

Many patients have begun to use mobile applications to handle different health needs because they can better access high-speed Internet and *** devices and mobile applications are now increasingly used and integrated through the medical Internet of Things(mIoT).mIoT is an important part of the digital transformation of healthcare,because it can introduce new business models and allow efficiency improvements,cost control and improve patient *** the mIoT system,when migrating from traditional medical services to electronic medical services,patient protection and privacy are the priorities of each ***,it is recommended to use different user authentication and authorization methods to improve security and *** this paper,our prosed model involves a shared identity verification process with different situations in the e-health *** aim to reduce the strict and formal specification of the joint key authentication *** use the AVISPA tool to verify through the wellknown HLPSL specification language to develop user authentication and smart card use cases in a user-friendly *** model has economic and strategic advantages for healthcare organizations and healthcare *** medical staff can increase their knowledge and ability to analyze medical data more *** model can continuously track health indicators to automatically manage treatments and monitor health data in real ***,it can help customers prevent chronic diseases with the enhanced cognitive functions *** necessity for efficient identity verification in e-health care is even more crucial for cognitive mitigation because we increasingly rely on mIoT systems.

关键词： E-health systems joint key authentication mutual authentication

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