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On-demand automated bus services: Opportunities and challenges

communications in Transportation Research 2024年第1期4卷 232-234页

作者： Huizhao Tu Maria Attard Ying Yang Karyn Scerri Adrian Muscat Hao Li College of Transportation Engineering Tongji UniversityShanghai200000China Institute for Climate Change and Sustainable Development University of MaltaMsidaMSD 2080Malta School of Management Shanghai UniversityShanghai200000China Department of Communications and Computer Engineering University of MaltaMsidaMSD 2080Malta

*** The on-demand automated bus(OAB)is a flexible,passenger-centric mobility service that uses small,electric,self-driving(mini)buses for public transport(Buics and Prayogo,2023).It is a typical integration of autonomous driving and shared *** associated with electrification,OAB's operation in the real world could contribute substantially to decarbonization *** transport sector has been one of the most difficult sectors to *** urgency to reduce CO_(2) emissions,however,has put significant pressure on governments to adopt and implement measures and technologies to address transport *** significant policy focus on electrification has seen large investments in the battery and vehicle industry,as well as the energy *** has also syphoned significant public funds to encourage people to shift toward ***,some of these pathways remain critical for *** et al.(2018)showed that the shift to electrification of the transport system will not be fast enough or sufficient to achieve effective reductions in CO_(2)***,electric vehicle uptake is still low in many countries across the world despite statements that point toward the“end”of internal combustion engine *** is therefore important to extend the discussion and efforts to include all elements of the transport system,including the much-needed modal shift to public *** could act as an important public transport mode with electrification and low carbon emissions.

关键词： driving automated services

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Metamaterial-Enabled Ultrawideband mmWave Antenna-in-Package Using Heterogeneously-Integrated Silicon IPD and HDI-PCB for B5G/ 6G Applications

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IEEE Journal on Emerging and Selected Topics in Circuits and Systems 2024年第1期14卷 7-18页

作者： Khiabani, Neda Chiang, Ching-Wen Liu, Nai-Chen Chen, Pai-Yen Kuan, Yen-Cheng Wu, Chung-Tse Michael Rutgers University Department of Electrical and Computer Engineering New BrunswickNJ08854 United States Nokia Bell Labs Murray HillNJ07974 United States National Yang Ming Chiao Tung University International College of Semiconductor Technology Hsinchu30010 Taiwan Industrial Technology Research Institute Information and Communications Research Laboratories Hsinchu County310401 Taiwan Institute of Communications Engineering National Yang Ming Chiao Tung University Hsinchu30010 Taiwan MediaTek Inc. Hsinchu30078 Taiwan University of Illinois at Chicago Department of Electrical and Computer Engineering ChicagoIL60607 United States

This work presents the design, creation, and testing of ultrawideband millimeter-wave (mmWave) antennas with a tightly coupled array (TCA) configuration. These antennas are made using metamaterial (MTM) designs and advanced high-density interconnect (HDI) antenna-in-package (AiP) technologies, ideal for beyond-5G (B5G) and 6G networks. The main elements of the MTM antenna array are constructed with silicon-based integrated passive device (IPD) technology and are flip-chip bonded to a multi-layered HDI-PCB that includes a resistive frequency selective surface (FSS). These array antennas are differentially fed through a coax-via system. The study presents two types of 5\times 5 finite arrays: a metal-insulator-metal (MIM) capacitor-based MTM bowtie array with a differential Voltage Standing Wave Ratio (VSWR) \le3.5 , operating from 16.2 to 100 GHz (excluding 18.26-18.68 GHz and 60.8-61.13 GHz), and an interdigital capacitor-based MTM bowtie array functioning from 18.85 to 100 GHz (excluding 41.52-42.25 GHz). Experimental validation of these prototypes confirms their performance, aligning well with simulated results in terms of bandwidth and radiation characteristics. © 2011 IEEE.

关键词： Frequency selective surfaces

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Modelling Cognitive Scores for Alzheimer’s Disease Progression Prediction Using Longitudinal MRI Data 4th

Modelling Cognitive Scores for Alzheimer’s Disease Progress...

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4th EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing, BDCC 2021

作者： Thushara, A. UshaDevi Amma, C. John, Ansamma Victor, Lida Mary Department of Computer Science and Engineering TKM College of Engineering APJ Abdul Kalam Technological University Kerala Thiruvananthapuram India Department of Electronics and Communications Engineering Amrita Vishwa Vidyapeetham Kerala Vallikavu India

ISBN: (纸本)9783031076534

Alzheimer’s disease (AD) is a progressive neurological illness that causes memory and cognitive impairment. Many research works are going on to diagnose the disease at an early stage as there are no supplements or medications to decrease the risk of AD. Cognitive tests such as Mini-Mental State Examination (MMSE) and Alzheimer’s Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) are used to measure the level and progression of cognitive impairment, as well as to track an individual’s cognitive changes over time, making it a useful tool for documenting a patient’s reaction to treatment. These examinations are biased against people with hearing or vision problems and those with a poor level of education due to linguistic and mathematical examination components. The proposed study uses regression models such as ridge, lasso and elastic net to estimate cognitive scores using longitudinal MRI data from Alzheimer’s Disease Neuroimaging Initiative (ADNI). Compared to ridge and lasso models, elastic net model achieves promising performance in cognitive score prediction and helps to identify the important biomarkers for AD. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Regression analysis

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A Novel Approach to Feature Extraction in MI - Based BCI Systems 8

A Novel Approach to Feature Extraction in MI - Based BCI Sys...

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8th IEEE International Conference on Computational System and Information Technology for Sustainable Solutions, CSITSS 2024

作者： Arun Kumar, S. Anand, L. Kannur, Anil School of Computing Srm Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Kattankulathur India School of Computing Srm Institute of Science and Technology Department of Networking and Communications Tamil Nadu Kattankulathur India BLDEA'S V.P. Dr. P.G. Halakatti College of Engineering and Technology Department of Computer Science and Engineering Vijayapura India

ISBN: (纸本)9798331505462

Brain-computer interfaces based on motor imagery (MI-BCI) enable communication between the brain and the outside world. It accomplishes this by capturing and examining the EEG data generated when a person visualizes moving a certain limb. Based on this investigation;to enhance categorization precision, we enhance the attribute extraction process. Once the EEG signals have been pre-processed and deconstructed into distinct bands of frequencies, we apply similar spatial algorithms for every sub-band. After that, we use Blind Source Separation (BSS) and spatial filter techniques to extract attributes directly from the sources of the brain instead of only from channels. Ultimately, by choosing the most relevant attributes as inputs for the categorization stage, we distinguish between the envisioned movements. To assess our recommended approach, we utilized data set IVa from the BCI competition III. The outcomes from diverse experiments indicate that the system achieves an average accuracy of 98.8%, with 100% sensitivity across all subjects. These results illustrate that the suggested approach effectively improves MI-based BCI. © 2024 IEEE.

关键词： Blind source separation

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IoT Authentication Protocols: Classification, Trend and Opportunities

IEEE Transactions on Sustainable Computing

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IEEE Transactions on Sustainable Computing 2024年第3期10卷 515-533页

作者： N.alsheavi, Amar Hawbani, Ammar Wang, Xingfu Othman, Wajdy Zhao, Liang Liu, Zhi Alsamhi, Saeed Hamood Al-Qaness, Mohammed A. A. University of Science and Technology of China School of Computer Science and Technology Anhui Hefei230027 China Shenyang Aerospace University School of Computer Science Shenyang110136 China Nankai University Haihe Laboratory of ITAI School of Cyber Science Tianjin300459 China The University of Electro-Communications Department of Computer and Network Engineering Tokyo Japan University of Galway Insight Centre for Data Analytics Galway Ireland IBB University Faculty of Engineering Ibb Yemen Zhejiang Normal University College of Physics and Electronic Information Engineering Jinhua321004 China Zhejiang Institute of Optoelectronics Jinhua321004 China

This paper reviews three main aspects of authentication protocols of Internet of Things (IoT): classifications and limitations, current trends, and opportunities. First, we explore the significance of IoT authentication protocols in ensuring secure communication and the protection of transmitted and received data, focusing on the classifications and associated limitations. Second, we discuss the latest developments and trends, such as using blockchain technology and machine learning to enhance authentication protocols. Third, we highlight the future opportunities, including the development of human-centric authentication designs and improved platform interoperability. At the end of this paper, we provided some insights gained for the new researcher, offering analyses of the trends and challenges in this field, giving recommendations for improving IoT authentication protocols, and emphasizing the need for further research and cooperation to develop advanced security solutions. © 2016 IEEE.

关键词： Authentication Protocol

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Task Reverse Offloading with Deep Reinforcement Learning in Multi-Access Edge Computing 9

Task Reverse Offloading with Deep Reinforcement Learning in ...

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9th International Conference on computer and Communication engineering, ICCCE 2023

作者： Saeed, Mamoon M. Saeed, Rashid A. Mokhtar, Rania A. Khalifa, Othman O. Ahmed, Zeinab E. Barakat, Mohammed Elnaim, Areeg Ali Faculty of Engineering Department of Communications and Electronics Engineering Yemen Taif University College of Computers and Information Technology Department of Computer Engineering P.O. Box 11099 Taif21944 Saudi Arabia International Islamic University Malaysia Department of Electrical and Computer Engineering Malaysia Libyan Center for Engineering Research and Information Technology Bani Waleed Libya International Islamic University Malaysia Electrical and Computer Engineering Dept. Malaysia University of Gezira Computer Engineering Dept. Sudan Alneelain University College of Engineering Khartoum Sudan

ISBN: (纸本)9798350325218

The Multi-access Edge Computing (MEC) technology's quick development greatly benefits the Collaborative Mobile Infrastructure System (CMIS). To combine the data and produce tasks, crowd-sensing data will be transferred to the MEC server in CMIS. Nevertheless, if there are too many devices, it becomes extremely difficult for MEC to decide appropriately based on the data from the devices and infrastructure. This study builds a framework for reverse offloading that carefully balances the relationship between task completion time and user mobile energy consumption. Moreover, to decrease system use generally, an adaptive optimal reverse offloading method based on Deep Q-Network is created (DQN). The results of the simulations demonstrate that the suggested approach may successfully minimize energy consumption and work latency when compared to full local and fixed offloading techniques. © 2023 IEEE.

关键词： Reinforcement learning

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Image Segmentation for Improved Lossless Screen Content Compression 48

Image Segmentation for Improved Lossless Screen Content Comp...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Uddehal, Shabhrish Reddy Strutz, Tilo Och, Hannah Kaup, André Coburg University Department of Electrical Engineering and Computer Science Coburg Germany Friedrich-Alexander University Multimedia Communications and Signal Processing Erlangen Germany

ISBN: (纸本)9781728163277

In recent years, it has been found that screen content images (SCI) can be effectively compressed based on appropriate probability modelling and suitable entropy coding methods such as arithmetic coding. The key objective is determining the best probability distribution for each pixel position. This strategy works particularly well for images with synthetic (textual) content. However, usually screen content images not only consist of synthetic but also pictorial (natural) regions. These images require diverse models of probability distributions to be optimally compressed. One way to achieve this goal is to separate synthetic and natural regions. This paper proposes a segmentation method that identifies natural regions enabling better adaptive treatment. It supplements a compression method known as Soft Context Formation (SCF) and operates as a pre-processing step. If at least one natural segment is found within the SCI, it is split into two subimages (natural and synthetic parts) and the process of modelling and coding is performed separately for both. For SCIs with natural regions, the proposed method achieves a bit-rate reduction of up to 11.6% and 1.52% with respect to HEVC and the previous version of the SCF. © 2023 IEEE.

关键词： lossless coding probability distribution screen content images segmentation soft context formation

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Cryptographic Ledger for Cyber Security in Smart Grid 2

Cryptographic Ledger for Cyber Security in Smart Grid

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2nd International Conference on Edge Computing and Applications, ICECAA 2023

作者： Elanchezhiyan, E. Kalaiselvi, K. Banumathy, D. Srm Institute of Science and Technology Faculty of Engineering and Technology Department of Networking and Communications Tamilnadu Kattankulathur603203 India Paavai Engineering College Department of Computer Science and Engineering Tamilnadu Namakkal637018 India

ISBN: (纸本)9798350347579

In addition to the physical security of energy networks, cyber security is essential to protecting these systems as well. Cyber threats can stem from malicious hackers who have infiltrated the networks to gain unauthorized access to sensitive data, or from vulnerabilities within the systems themselves. It is increasingly important that smart grid companies invest in cyber security solutions, such as strong passwords, two-factor authentication, encryption, and regular software updates, to counteract these threats. Additionally, it is beneficial for organizations to create incident response plans that are tailored to their specific needs, and which define the chain of command and actions to take in the case of an incident. To details the usage of smart grids in various domains and places in an effective way and explains the efficient way of consuming power for smart ventilators by monitoring and providing cyber security against cyber-attacks. The distributed power from various regions is collected from the less predominant places and supplied to the smart ventilators through smart inverters. © 2023 IEEE.

关键词： Cybersecurity

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Enhancing Plant Recognition in Intelligent Agricultural Irrigation Systems Using Stable Diffusion and Lora Models with CFloss 17

Enhancing Plant Recognition in Intelligent Agricultural Irri...

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17th International Congress on Image and Signal Processing, BioMedical engineering and Informatics, CISP-BMEI 2024

作者： Lu, Yingzhu Tang, Chengyu Fan, Yawen Zhou, Qin Nanjing University of Posts and Telecommunications Department of Computer Science and Technology Nanjing China Nanjing Forestry University Department of Computer Science and Technology Nanjing China School of Communications and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China School of Information Science and Engineering East China University of Science and Technology Shanghai China

ISBN: (纸本)9798331507398

This paper proposes a novel approach to optimize the plant recognition function of intelligent agricultural irrigation system, utilizing Stable Diffusion model and Lora (Low-Rank Adaptation) model. Stable Diffusion model is a latent diffusion model that converts text into images, while Lora is a method of fine-tuning large models by reducing trainable parameters while maintaining model performance as much as possible. By combining the Stable Diffusion model and Lora model, this paper trains custom models for each plant species using a small amount of data and generates corresponding images of each variety to assist training, thus optimizing classification results. In addition, to address the issue of imbalanced data, this study also introduces Focal Loss to mitigate the impact of both class imbalance and difficulty in classification. Building upon Focal Loss, CFloss is created as the model's loss function. This method was tested on the OxfordFlower102 dataset used by the original model, and the results demonstrate that it effectively improves classification accuracy and significantly enhances the plant recognition function of the irrigation system. © 2024 IEEE.

关键词： Image classification

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Energy Consumption Minimization for Distributed Microservice-Aware Wireless Cellular Networks

Energy Consumption Minimization for Distributed Microservice...

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2023 IEEE/CIC International Conference on communications in China, ICCC 2023

作者： Shan, Yue Zhu, Qi Fu, Yaru Nanjing University of Posts and Telecommunications School of Communications and Information Engineering Nanjing China Department of Electronic Engineering and Computer Science Hong Kong Metropolitan University Hong Kong

ISBN: (纸本)9798350345384

This paper focuses on minimizing energy consumption by addressing the joint microservice (MS) placement and computing resource allocation problem in distributed MS-aware wireless cellular networks (DMS-WCNs). We propose a paradigm in which each large service is composed of several lightweight MSs distributed among different small base stations (SBSs) to perform individual functions. For an arbitrary service request, the macro base station (MBS) invokes the SBSs that have cached the necessary MSs to execute the corresponding computational tasks. Once the computation is completed, the SBSs send the results back to the MBS, which then integrates and delivers the final result to the user. Taking into account the practical considerations of users' service latency requirements and SBSs' limited caching and computing resources, we formulate the minimization problem. To solve it efficiently, we develop a two-stage approach. In the first stage, we derive the closed-form expression of the computing resource allocation policy with regard to the MS placement. In the second stage, we introduce the swapping-oriented algorithm to explore an improved MS placement strategy. The simulation results demonstrate that our proposed algorithm achieves close-to-optimal performance compared to the exhaustive algorithm and significantly outperforms the other benchmark strategies. © 2023 IEEE.

关键词： Energy utilization

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