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19th IEEE Annual Consumer Communications and Networking Conference, CCNC 2022

作者： Wang, Xin Calderon, Juan Khoshavi, Navid Jaimes, Luis G. Florida Polytechnic University Department of Computer Science LakelandFL33805 United States Universidad Santo Tomás Department of Electronic Engineering Colombia Bethune Cookman University Computer Science & Engineering Department United States

ISBN: (纸本)9781665431620

According to the world report in 2019 about vision health presented by the World Health Organization (WHO), there are 2.2 billion people in the world with some kind of visual impairment. Furthermore, in a recent National Health Interview Survey report, 25.5 million adult Americans 18 and older reported experiencing vision loss. Of these 25.5 million American adults, 15.3 million women and 10.1 million men report experiencing significant vision loss. As a result, this population is constantly at risk of a fall and its consequences. This paper presents the first module of our fall prevention system for visually impaired people. The module corresponds to a system of floor and path recognition in outdoor environments. At the core of the system is a Mask R-CNN trained with around 40.000 outdoor images. The proposed approach has reached a performance in a combination of training and testing of 92%, using a combined set of indoor and outdoor environment images. © 2022 IEEE.

关键词： Floors

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MCNN: a multi-level CNN model for the classification of brain tumors in IoT-healthcare system

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Journal of Ambient Intelligence and Humanized Computing 2023年第5期14卷 4695-4706页

作者： Haq, Amin ul Li, Jian Ping Kumar, Rajesh Ali, Zafar Khan, Inayat Uddin, M. Irfan Agbley, Bless Lord Y. Sichuan Chengdu611731 China University of Electronic Science and Technology of China Huzhou313001 China School of Computer Science and Engineering Southeast University Nanjing210096 China Department of Computer Science University of Buner Buner19290 Pakistan Institute of Computing Kohat University of Science and Technology Kohat26000 Pakistan

The classification of brain tumors is significantly important for diagnosing and treating brain tumors in IoT healthcare systems. In this work, we have proposed a robust classification model for brain tumors employing deep learning techniques. In the design of the proposed method, an improved Convolutional neural network is used to classify Meningioma, Glioma, and Pituitary types of brain tumors. To test the multi-level convolutional neural network model, brain magnetic resonance image data is utilized. The MCNN model classification results were improved using data augmentation and transfer learning methods. In addition, hold-out and performance evaluation metrics have been employed in the proposed MCNN model. The experimental results show that the proposed model obtained higher outcomes than the state-of-the-art techniques and achieved 99.89% classification accuracy. Due to the higher results of the proposed approach, we recommend it for the identification of brain cancer in IoT-healthcare systems. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Convolutional neural networks

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A Generalized Anti-windup Approach for Internal Model Control

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IFAC-PapersOnLine 2024年第25期58卷 96-101页

作者： Ambrose A. Adegbege Kolawole S. Ogunba Opeyemi S. Owolabi Electrical and Computer Engineering The College of New Jersey Ewing NJ08628 USA Department of Electronic and Electrical Engineering Obafemi Awolowo University Ile-Ife Nigeria

In this paper, we develop a generalized anti-windup synthesis procedure for saturating internal model control (IMC). Within this framework, the anti-windup design problem reduces to a search over a class of left coprime factorization of the linear internal model controller. An appropriate anti-windup is constructed by solving a set of linear matrix inequalities. As compared to other static anti-windup constructions in the literature, the IMC anti-windup is always feasible with guaranteed closed-loop stability and performance. Using a simulation example, we benchmark the behaviour of the constructed anti-windup with existing state-of-the-art methods.

关键词： Anti-windup Internal Model Control Constrained Control

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A Mechanism for Improving the Spectral Efficiency in mu-MIMO for 5G and beyond Networks 19

A Mechanism for Improving the Spectral Efficiency in mu-MIMO...

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19th ACM International Symposium on Mobility Management and Wireless Access, MobiWac 2021

作者： Barri, Eirini Bouras, Christos Kokkinos, Vasileios Koukouvela, Aspasia Department of Computer Engineering and Informatics University of Patras Patras Greece

ISBN: (纸本)9781450390798

The ultimate challenge that arises in 6G and 5G and beyond networks is how the mobile networks of the future will be able to cope with the constantly increasing number of devices. In Multiuser Multiple-Input and Multiple-Output (mu-MIMO), the base station basically serves many users at the same time using the same frequency. The topic considered in this paper is the spectral performance in Downlink mu-MIMO. This paper's goal is to improve the achieved spectral efficiency of the communication system, as well as the achieved reliability of the communication link. An algorithm based on downlink scheduling and the resource allocation is proposed to achieve maximum spectral use of the system. Considering user's demands, this paper's mechanism is able to allocate the potential user of the queue to the "best antenna"based on its demands and distance. That provokes a larger number of devices that can be supported, always according to the specifications stated in IEEE 802.11ax. © 2021 ACM.

关键词： Spectrum efficiency

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A Blockchain-based electronic Voting System: EtherVote

arXiv

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arXiv 2023年

作者： Spanos, Achilleas Kantzavelou, Ioanna Department of Informatics and Computer Engineering University of West Attica Athens Greece

The development of an electronic voting system that would replace traditional election procedures is a research topic of great interest for many years. Blockchain technology could provide some guarantees and fulfill strong requirements for electronic voting platforms, such as transparency, immutability, and confidentiality. From time to time research is conducted to address problems in voting systems. Many research works attempt to implement secure and reliable voting systems, which address known security, anonymity, and fraud issues that might threaten such systems. This paper presents a proposal of a secure electronic voting system, the EtherVote, using the Ethereum Blockchain network that focuses deeply on the field of identification of eligible citizens. The proposed system will be entirely based on Blockchain without any central authority servers or databases, thus improving security, privacy, and election cost. Limitations, problems, and solutions are discussed, in order to make the proposed electronic voting system ideal and ready to use for national elections. © 2023, CC BY-NC-ND.

关键词： Smart contract

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Enhancing Covertness in Hybrid Active-Passive STAR-RIS-based RSMA Systems

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IEEE Transactions on Vehicular Technology 2025年

作者： Nguyen, Lan Anh Vu, Thai-Hoc Kim, Sunghwan University of Ulsan Department of Electrical Electronic and Computer Engineering Korea Republic of Kyonggi University School of Electronic Engineering Korea Republic of

This study proposes an efficient approach for the robust covertness of hybrid active-passive simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-based rate splitting multiple access (RSMA) systems. Under Rician fading channels, we first derive the closed-form expression for the detection error probability (DEP) that an eavesdropper monitors proximate users' covert information, then establish the approximated optimal DEP for the worst-case scenario, and finally treat it as a strict constraint for system security design. Specifically, the non-convex optimization problem of determining the power allocation (PA) resource to maximize the covert rate is tackled by transforming it into two tractable sub-optimization problems. We exploit the analyses of the developed DEP to derive closed-form solutions for the PA coefficients in each sub-problem, which are solved using an iterative algorithm with relatively low computational complexity. Extending this for the general case of double covert signal transmission, we also formulate and address the problem of jointly optimizing the resource power and rate allocation to maximize the minimal transmission rates among users. Besides the efficacy of the proposed approaches, some key findings can be achieved as follows: 1) RSMA achieves a higher DEP than NOMA;2) Optimizing the PA resource boosts the achievable covert rate up to 1.3 bits/s/Hz for all STAR-RIS modes when the transmit power is larger than 20 dBm;and 3) Using hybrid mode helps flexibly adjust the number of STAR-RIS elements to gain the best performance with active mode at high transmission power and passive mode at lower power. © 1967-2012 IEEE.

关键词： Convex optimization

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High accuracy, fully reconfigurable DAQ system for sensing temperature 33

High accuracy, fully reconfigurable DAQ system for sensing t...

引用

33rd International Scientific Conference electronics, ET 2024

作者： Gatev, Vasil D. Mollov, Valentin S. Petrov, Panayot L. Manoeva, Mariana D. Technical University of Sofia Faculty of Computer Systems and Technologies Department of Computer Systems 8 Kliment Ohridski blvd. Sofia1000 Bulgaria Technical University of Sofia Faculty of Electronic Engineering and Technologies Department of Electronics 8 Kliment Ohridski blvd. Sofia1000 Bulgaria

ISBN: (纸本)9798350376449

The FPGA configurable integrated circuits (ICs) are a valid alternative to the common microcontroller solutions for application-specific (ASIC) embedded applications. The FPGAs are applied in the prototype step, before the ASIC synthesis, for end-user devices targeted to real-time applications. Nowadays IoT solutions with post-processing on cloud-based server technology, makes the dedicated DAQ device an important component in the system. The FPGAs are the appropriate basis for such device, where the data acquisition of analog values and its transfer to digital representation must be achieved with high-speed, high-resolution, low power consumption and effective optimization of the IC resources. © 2024 IEEE.

关键词： Application specific integrated circuits

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Hybrid-RIS Empowered UAV-Assisted ISAC Systems: Transfer Learning-based DRL

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IEEE Transactions on Communications 2025年

作者： Saikia, Prajwalita Jee, Anand Singh, Keshav Huang, Wan-Jen Boulogeorgos, Alexandros-Apostolos A. Tsiftsis, Theodoros A. National Sun Yat-sen University Institute of Communications Engineering Kaohsiung Taiwan Indian Institute of Technology Delhi Department of Electrical Engineering New Delhi110016 India University of Western Macedonia Department of Electrical and Computer Engineering Kozani50131 Greece University of Thessaly Department of Informatics and Telecommunications Lamia35100 Greece University of Nottingham Ningbo China Department of Electrical and Electronic Engineering Ningbo315100 China

In this paper, we consider a novel hybrid reconfigurable intelligent surface (HRIS) consisting of active as well as passive reflecting elements mounted on unmanned aerial vehicle (UAV). The aim is to improve air-to-ground communication by assisting multiple users, while detecting several low mobility targets. We formulate a sum-rate optimization problem that accounts for statistical channel estimation errors (SCEEs) to concurrently fine-tune both active and passive phase-shift matrices, UAV trajectory, and transmit beamformer for integrated sensing and communication (ISAC). Subsequently, we introduce a transfer learning based approach combining with deep deterministic policy gradient (DDPG) to enhance the overall data rate while minimizing the time it takes for users to transmit data. Additionally, we present an alternating optimization (AO) algorithm that employs a repetitive method to address the combinatorial nonconvex optimization problem and offers a solution that is very close to optimal. Finally, we showcase the superiority of the proposed scheme through Monte Carlo simulations. Also, we have compared the performance with perfect channel state information (CSI) counterpart. The outcomes of simulations confirm the theoretical analysis and demonstrate the efficiency of the proposed framework. Additionally, the results reveal the advantages of incorporating HRIS aided UAV assisted ISAC in improving the quality of both communication and sensing performance. © 1972-2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Detecting cultural identity via robotic sensor data to understand differences during human-robot interaction

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Advanced Robotics 2023年第22期37卷 1446-1459页

作者： Lee, Jinjae Bennett, Casey C. Stanojevic, Cedomir Kim, Seongcheol Henkel, Zachary Baugus, Kenna Piatt, Jennifer A. Bethel, Cindy Sabanovic, Selma Department of Intelligence Computing Hanyang University Seoul Korea Republic of Department of Computing & Digital Media DePaul University ChicagoIL United States Department of Parks Recreation & Tourism Management Clemson University ClemsonSC United States Department of Computer Science and Engineering Mississippi State University Starkville StarkvilleMS United States School of Public Health Indiana University BloomingtonIN United States School of Informatics Computing and Engineering Indiana University BloomingtonIN United States

Socially-assistive robots (SARs) have significant potential to help manage chronic diseases (e.g. dementia, depression, diabetes) in spaces where people live, averse to clinic-based care. However, the challenge is designing SARs so that they perform appropriate interactions with people who have different characteristics, such as age, gender, and cultural identity. Those characteristics impact how human behaviors are performed as well as user expectations of robot responses. Although cross-cultural studies with robots have been conducted to understand differing population characteristics, they have mainly focused on statistical comparisons of groups. In this study, we utilize deep learning (DL) and machine learning (ML) models to evaluate whether cultural differences show up in robotic sensor data during human-robot interaction (HRI). To do so, a SAR was distributed to user's homes for three weeks in the US and Korea (25 participants), while collecting data on the human activity and the surrounding environment through on-board sensor devices. DL models based on that data were able to predict the user’s cultural identity with roughly 95% accuracy. Such findings have potential implications for the design and development of culturally-adaptive SARs to provide services across diverse cultural locales and multi-cultural environments where users’ cultural background cannot be assumed a priori. © 2023 Informa UK Limited, trading as Taylor & Francis Group and The Robotics Society of Japan.

关键词： Human robot interaction

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SafePaint: Anti-forensic Image Inpainting with Domain Adaptation

arXiv

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arXiv 2024年

作者： Chen, Dunyun Wu, Xiaoshuai Liao, Xin Chen, Shiwei College of Computer Science and Electronic Engineering Hunan University Changsha China Department of Electrical Electronic and Information Engineering University of Bologna Emilia-Romagna Italy

Existing image inpainting methods have achieved remarkable accomplishments in generating visually appealing results, often accompanied by a trend toward creating more intricate structural textures. However, while these models excel at creating more realistic image content, they often leave noticeable traces of tampering, posing a significant threat to security. In this work, we take the anti-forensic capabilities into consideration, firstly proposing an end-to-end training framework for anti-forensic image inpainting named SafePaint. Specifically, we innovatively formulated image inpainting as two major tasks: semantically plausible content completion and region-wise optimization. The former is similar to current inpainting methods that aim to restore the missing regions of corrupted images. The latter, through domain adaptation, endeavors to reconcile the discrepancies between the inpainted region and the unaltered area to achieve anti-forensic goals. Through comprehensive theoretical analysis, we validate the effectiveness of domain adaptation for anti-forensic performance. Furthermore, we meticulously crafted a region-wise separated attention (RWSA) module, which not only aligns with our objective of anti-forensics but also enhances the performance of the model. Extensive qualitative and quantitative evaluations show our approach achieves comparable results to existing image inpainting methods while offering anti-forensic capabilities not available in other methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Digital forensics

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