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Provably Secure Conditional-Privacy Access Control Protocol for Intelligent Customers-Centric Communication in VANET

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IEEE Transactions on Consumer Electronics 2024年第1期70卷 1747-1756页

作者： Saleem, Muhammad Asad Li, Xiong Mahmood, Khalid Shamshad, Salman Ayub, Muhammad Faizan Bashir, Ali Kashif Omar, Marwan University of Electronic Science and Technology of China School of Computer Science and Engineering Sichuan Chengdu12599 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan The University of Lahore Department of Software Engineering Lahore54590 Pakistan Manchester Metropolitan University Department of Computing and Mathematics ManchesterM15 6BH United Kingdom Woxsen University Woxsen School of Business Hyderabad502345 India Lebanese American University Department of Computer Science and Mathematics Beirut1102 2801 Lebanon Illinois Institute of Technology Information Technology and Management ChicagoIL60555 United States

Globally, the development of Intelligent Cyber-Physical Transportation Systems (ICTS) aims to tackle several challenges, including reducing traffic accidents and fuel usage, alleviating congestion, shortening travel time, and enhancing overall transportation safety. These systems leverage advanced customer-centric communication and networked control methods, such as inter-vehicle, vehicle-to-roadside (V2R), and vehicle-to-vehicle (V2V) communication through the use of vehicular ad hoc networks (VANETs) to cover all aspects of transportation-based information. In existing systems, once devices are registered with a Trusted Authority (TA), subsequent authentication still relies on the TA's assistance. However, these devices typically remain stationary, and frequent interaction with the TA becomes impractical and costly in highly mobile VANET environments. To address this challenge, we propose a secure access control protocol with conditional privacy for VANETs. Unlike other protocols, our protocol does not require the TA's involvement during authentication between vehicles and RSUs. Additionally, our protocol leverages pseudonym mechanisms to provide conditional privacy, enabling legitimate vehicles to remain anonymous while malicious ones can be tracked. Our proposed scheme is supported by both formal and informal security analyses and has been shown to be secure against several known attacks in VANETs. Furthermore, compared to relevant studies, our protocol achieves 30.2505% of efficiency in terms of computation cost and 11.09276% of efficiency in terms of communication cost, respectively. © 1975-2011 IEEE.

关键词： Vehicular ad hoc networks

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Implementation and Performance Evaluation of Collective Communications Using CIRCUS on Multiple FPGAs

Implementation and Performance Evaluation of Collective Comm...

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2023 International Conference on High Performance Computing in Asia-Pacific Region Workshops, HPC Asia 2023

作者： Kikuchi, Kohei Fujita, Norihisa Kobayashi, Ryohei Boku, Taisuke Master's Program in Computer Science Degree Programs in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Tsukuba Japan Center for Computational Sciences University of Tsukuba Tsukuba Japan

ISBN: (纸本)9781450399890

In the high-performance computing domain, Field programmable Gate Array (FPGA) is a novel accelerator that exhibits high flexibility and performance characteristics distinct from other accelerators such as the Graphics Processing Unit (GPU). Recent advanced high-end FPGA is equipped with multiple channels of high speed optical link up to 100Gbps performance for each. This is a crucial feature when we construct PC clusters with FPGAs as accelerators, however it is not easy to utilize from user kernels because this feature is implemented in low level and simple direct communication between neighboring FPGAs. In order to provide the communication feature between FPGAs for accelerated PC clusters, we developed a communication system named CIRCUS which implies a user-friendly API from OpenCL and is equipped with routing function over multi-hop communication on multi-dimensional torus network of FPGAs. However, current CIRCUS only provides a point-to-point communication between source and destination FPGAs. In ordinary parallel processing environment such as MPI, the user program the message passing with various collective communication functions for parallel algorithm, for instance Allreduce, Allgather, etc. In this paper, we implement the collective communication function over CIRCUS for user-friendly programming of ordinary parallel algorithms on FPGAs. As the first target, we implement Allreduce function which is the most essential and important function. The paper describes the CIRCUS system briefly followed by the design, implementation and preliminary performance evaluation on Intel Stratix10 FPGAs. © 2023 ACM.

关键词： Field programmable gate arrays (FPGA)

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Predictive Analytics for Future Air Pollution Levels Based on Population Growth

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Procedia computer science 2024年 245卷 834-843页

作者： Darel Yeshe Irma Kartika Wairooy Brilly Andro Makalew Computer Science Department School of Computer Science Jakarta Indonesia 11480 Mobile Application & Technology Program Computer Science Department School of Computer Science Jakarta Indonesia 11480

Air is very beneficial and crucial for every living creature on earth, hence it is very important to protect the air quality in order to avoid diseases. However, due to the increase in population, some human activities have been causing detrimental damage to the air quality. Some people have realized the potential impact of this problem and have done studies on predicting future air pollution. Some implemented machine learning models such as random forest regression, support vector machine, etc, while others have utilized deep learning models in their research.. This study will implement five different models, specifically linear regression, ridge regression, random forest regression, and multilayer perceptron regression. There will be two datasets used in this paper which will be merged and processed. There will be three key evaluation metrics being used in this paper namely root mean squared error, mean absolute error, and r-squared. The results from all of the models have concluded that more optimization and factors are needed in order to boost the final result of this study.

关键词： Machine Learning Predicting Regression Algorithm technology Education Artificial Intelligence

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Analyzing the Effect of Observer Node Addition Strategy on Bitcoin Double-Spending Attack Detection Using Graph Neural Network 24

Analyzing the Effect of Observer Node Addition Strategy on B...

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24th Asia-Pacific Network Operations and Management Symposium, APNOMS 2023

作者： Kang, Changhoon Woo, Jongsoo Hong, James Won-Ki Department of Computer Science and Engineering POSTECH Korea Republic of Graduate School of Information Technology POSTECH Korea Republic of

ISBN: (纸本)9788995004395

Bitcoin transactions are created through the concept called Unspent Transaction Output (UTXO). Users put their own UTXOs as inputs into a transaction for Bitcoin transfer and create multiple outputs, each specifying the recipient’s wallet address and the amount to be sent. UTXO refers to an output that has not been used as an input for any transaction yet and each UTXO can only be used as an input once. However, attempting to use a UTXO more than once is called a double-spending attack. Although double-spending in Bitcoin is ultimately impossible due to the system structure, it can occur when a transaction is deemed confirmed and off-chain goods or services are provided before sufficient transaction finality is guaranteed. We consider an attempt of double-spending attack when a UTXO used as an input in a transaction for payment exists together with another transaction on the Bitcoin network that uses the same UTXO as an input. In previous research, we randomly deployed observer nodes on the Bitcoin network and proposed a method to detect double-spending attacks using transaction data in the memory pool and a graph neural network model. In this paper, we analyze the impact of adding observer nodes to the Bitcoin network on the performance of graph neural network-based Bitcoin double-spending attack detection. We conducted experiments to examine the performance differences among three strategies for adding observer nodes. However, it was difficult to compare clear differences due to the performance degradation of the model caused by the differences in graph structure between datasets. Therefore, we provide an analysis of the causes and suggestions for improvement. Copyright 2023 KICS.

关键词： Graph neural networks

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Expanding chiral metamaterials for retrieving fingerprints via vibrational circular dichroism

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Light(science & Applications) 2023年第7期12卷 1401-1414页

作者： Cheng Xu Zhihao Ren Hong Zhou Jingkai Zhou Chong Pei Ho Nan Wang Chengkuo Lee Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore Center for Inteligent Sensors and MEMS(CISM) National University of SingaporeSingapore 117608Singapore institute of Microelectronics(IME) Agency for ScienceTechnology and Research(A*STAR)Singapore 138634Singapore NUS Graduate School for Integrative Science and Engineering Program(ISEP) National University of SingaporeSingapore 117456Singapore

Circular dichroism(CD)spectroscopy has been widely demonstrated for detecting chiral ***,the determination of chiral mixtures with various concentrations and enantiomeric ratios can be a challenging *** solve this problem,we report an enhanced vibrational circular dichroism(VCD)sensing platform based on plasmonic chiral metamaterials,which presents a 6-magnitude signal enhancement with a selectivity of chiral *** by coupled-mode theory,we leverage both in-plane and out-of-plane symmetry-breaking structures for chiral metamaterial design enabled by a two-step lithography process,which increases the near-field coupling strengths and varies the ratio between absorption and radiation loss,resulting in improved chiral light-matter interaction and enhanced molecular VCD ***,we demonstrate the thin-film sensing process of BSA andβ-lactoglobulin proteins,which contain secondary structures a-helix andβ-sheet and achieve a limit of detection down to zeptomole ***,we also,for the first time,explore the potential of enhanced VCD spectroscopy by demonstrating a selective sensing process of chiral mixtures,where the mixing ratio can be successfully differentiated with our proposed chiral *** findings improve the sensing signal of molecules and expand the extractable information,paving the way toward label-free,compact,small-volume chiral molecule detection for stereochemical and clinical diagnosisapplications.

关键词： chiral vibrational circular

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An Adaptive Learning Support System based on Ontology of Multiple programming Languages 31

An Adaptive Learning Support System based on Ontology of Mul...

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31st International Conference on computers in Education, ICCE 2023

作者： Na Nongkhai, Lalita Wang, Jingyun Mendori, Takahiko Graduate School of Engineering Kochi University of Technology Japan Department of Computer Science Durham University United Kingdom

ISBN: (纸本)9786269689019

This research proposes to develop an adaptive ontology-based learning support system for computer programming learning. Firstly, the system adopts a previously developed ontology called CONTINUOUS, which represents programming concepts and their relation in a graph and makes use of its content to serve as hints within programming questions. Secondly, we design an adaptive strategy for recommending suitable exercises to learners, which uses CONTINUOUS as metadata of exercises and the Elo rating system to estimate learners' skills. This work aims to design a system to provide personalized exercise path for the learner and evaluate its effectiveness. © 2023 Asia-Pacific Society for computers in Education.

关键词： Ontology

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Low-Temperature Methanolysis of Polycarbonate over Solid Base Sodium Aluminate

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Langmuir 2024年第10期40卷 5338-5347页

作者： Krisbiantoro, Philip Anggo Sato, Miyu Lin, Tzu-Ming Chang, Yu-Chia Peng, Tzu-Yun Wu, Yun-Chih Liao, Weisheng Kamiya, Yuichi Otomo, Ryoichi Wu, Kevin C.-W. Molecular Science and Technology Program Taiwan International Graduate Program Academia Sinica Taipei11529 Taiwan International Graduate Program of Molecular Science and Technology National Taiwan University Taipei10617 Taiwan Department of Chemical Engineering College of Engineering National Taiwan University Taipei10617 Taiwan Graduate School of Environmental Science Hokkaido University Nishi 5 Kita 10 Sapporo060-0810 Japan Faculty of Environmental Earth Science Hokkaido University Nishi 5 Kita 10 Sapporo060-0810 Japan Center of Atomic Initiative for New Materials National Taiwan University Taipei10617 Taiwan Department of Chemical Engineering and Materials Science Yuan Ze University Taoyuan320 Taiwan

Herein, a low-cost and readily available sodium aluminate (NaAlO2) was used as a solid base catalyst for the depolymerization of polycarbonate (PC) via methanolysis in the presence of tetrahydrofuran (THF) as a solvent. NaAlO2 was highly active for the reaction, and the performance was comparable to that of soluble strong base SrO and much higher than those of MgO and CaO. By the reaction over the catalyst, a highly pure and crystalline bisphenol A (BPA) was obtained. Among tested organic solvents, THF was the best in aiding PC methanolysis over NaAlO2 due to the polarity similar to PC according to Hansen solubility parameters (HSPs). At 60 °C, 98.1% PC conversion and 96.8% BPA yield were achieved within just 2 h. NaAlO2 was reusable without any severe catalyst deactivation in at least four runs. The mechanistic study revealed that the reaction proceeded via the methoxide pathway, with THF aiding the dissolution of PC. The reaction over NaAlO2 possessed a low apparent activation energy (Ea) of 75.1 kJ mol-1, which is the lowest ever reported so far for the reaction over solid catalysts. © 2024 The Authors. Published by American Chemical Society.

关键词： Sodium Aluminate

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Hoax Classification in Imbalanced Datasets Based on Indonesian News Title using RoBERTa 3

Hoax Classification in Imbalanced Datasets Based on Indonesi...

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3rd International Conference on Artificial Intelligence and Data sciences, AiDAS 2022

作者： Muliono, Yohan Gaol, Ford Lumban Soewito, Benfano Warnars, Harco Leslie Hendric Spits School of Computer Science Bina Nusantara University Binus Graduate Program - Doctor of Computer Science Computer Science Department Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program - Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (数字)9781665491648

ISBN: (纸本)9781665491648

Hoaxes are something that can not be avoided, especially in Indonesia, where the literacy rate in Indonesia is quite low, they are easy to believe in news without doing fact check. The worst thing is that news that is trusted by the public may not be read completely through the entire content. They believe, from the title alone could already covers the entire content of the news. Media in the other side, are also competing to make controversial titles so that their traffic is improved. The research that will be carried out by us is where we can classify a news whether it is a fact or a hoax from the title alone. The RoBERTa (A Robustly Optimized BERT Pretraining Approach) model will be used in this study, because in several previous studies RoBERTa has proven to be good for classification. The accuracy achieved in this study also reached 99.52% with an accuracy validation of 93.84% which shows that even with an imbalanced dataset the classification shows a promising result by using the RoBERTa model which data is balanced using the undersampling method. © 2022 IEEE.

关键词： Classification (of information)

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A Visual Interpretation-Based Self-improved Classification System Using Virtual Adversarial Training 9th

A Visual Interpretation-Based Self-improved Classification S...

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

作者： Jiang, Shuai Kamei, Sayaka Li, Chen Hou, Shengzhe Morimoto, Yasuhiko Graduate School of Advanced Science and Engineering Hiroshima University Hiroshima Japan Graduate School of Informatics Nagoya University Nagoya Japan College of Computer Science and Engineering Shandong University of Science and Technology Qingdao China

ISBN: (纸本)9783031466731

The successful application of large pre-trained models such as BERT in natural language processing has attracted more attention from researchers. Since the BERT typically acts as an end-to-end black box, classification systems based on it usually have difficulty in interpretation and low robustness. This paper proposes a visual interpretation-based self-improving classification model with a combination of virtual adversarial training (VAT) and BERT models to address the above problems. Specifically, a fine-tuned BERT model is used as a classifier to classify the sentiment of the text. Then, the predicted sentiment classification labels are used as part of the input of another BERT for spam classification via a semi-supervised training manner using VAT. Additionally, visualization techniques, including visualizing the importance of words and normalizing the attention head matrix, are employed to analyze the relevance of each component to classification accuracy. Moreover, brand-new features will be found in the visual analysis, and classification performance will be improved. Experimental results on Twitter’s tweet dataset demonstrate the effectiveness of the proposed model on the classification task. Furthermore, the ablation study results illustrate the effect of different components of the proposed model on the classification results. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Classification (of information)

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Moving target detection from the roadside by millimeter-wave radar

Moving target detection from the roadside by millimeter-wave...

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2024 International Symposium on Antennas and Propagation, ISAP 2024

作者： Moriyama, Toshifumi Matsumoto, Sora Chang, Yang-Lang Graduate School of Engineering Nagasaki University Nagasaki Japan College of Electrical Engineering and Computer Science National Taipei University of Technology Taipei Taiwan

ISBN: (纸本)9798350364774

In this study, we investigate a traffic monitoring method to detect passing cars, bikes, and humans from roadsides using millimeter-wave radar during road work. Because a road worker is one of the most dangerous occupations, the number of people trying to get this type of job is decreasing. To give a safety work condition and reduce road accidents with respect to the road works, a millimeter-wave radar is one of the candidates for infrastructure sensors that can be expected to offer robust detection performance regardless of the surrounding environment. Then, we applied millimeter-wave radar to traffic monitoring during road work. We examine that the radar detects passing cars, bikes, and humans, and estimates their direction with two corner reflectors from the roadside. These experiments were carried out, and the results are presented in this paper. © 2024 IEEE.

关键词： Roadsides

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