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IEEE Transactions on Intelligent Vehicles 2024年第9期9卷 1-13页

作者： Samii, Amirhossein Bekiaris-Liberis, Nikolaos Department of Electrical & Computer Engineering Technical University of Crete Chania Greece

We construct a predictor-feedback cooperative adaptive cruise control (CACC) design with integral action, which achieves simultaneous compensation of long, actuation and communication delays, for platoons of heterogeneous vehicles whose dynamics are described by a third-order linear system with input delay. The key ingredients in our design are an underlying predictor-feedback law that achieves actuation delay compensation and an integral term of the difference between the delayed (by an amount equal to the respective communication delay) and current speed of the preceding vehicle. The latter, essentially, creates a virtual spacing variable, which can be regulated utilizing only delayed position and speed measurements from the preceding vehicle. We establish individual vehicle stability, string stability, and regulation for vehicular platoons, under the control design developed. The proofs rely on combining an input-output approach (in the frequency domain), with derivation of explicit solutions for the closed-loop systems, and they are enabled by the actuation and communication delays-compensating property of the design. We demonstrate numerically the control and model parameters' conditions of string stability, while we also present simulation results, in realistic scenarios, including a scenario in which the leading vehicle's trajectory is obtained from NGSIM data. All case studies confirm the effectiveness of the design developed. IEEE

关键词： Feedback

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Res-MGCA-SE: a lightweight convolutional neural network based on vision transformer for medical image classification

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Neural Computing and Applications 2024年第28期36卷 17631-17644页

作者： Soleimani-Fard, Sina Ko, Seok-Bum Department of Electrical and Computer Engineering University of Saskatchewan SaskatoonSK Canada

This paper presents a lightweight and accurate convolution neural network (CNN) based on encoder in vision transformer structure, which uses multigroup convolution rather than multilayer perceptron and multiheaded self-attention. We propose a group convolution block called multigroup convolution attention (MGCA) and squeeze and excitation (SE). The MGCA includes two parts: three 1×1 convolutions concatenated along the channel dimension and depth-wise separable convolution. SE is used as a skip connection to provide long-range dependencies. MGCA-SE is introduced to reduce the number of parameters in state-of-the-art network in order to use fewer datasets for training CNN. Furthermore, we provide a lightweight network based on MGCA-SE in Resnet architecture called Resnet-multigroup convolution attention-squeeze and excitation (Res-MGCA-SE) in order to have early detection and treatment of medical images. Finally, Res-MGCA-SE is evaluated on lung cancer and Covid-19 chest X-ray and CT and images. According to our research findings, MGCA-SE can change convolutional layers in state-of-the-art networks and switch them to lightweight networks with properties comparable to heavy-weight networks. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Convolution

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Capturing multiple emotions from conversational data using fine tuned transformers

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International Journal of computers and Applications 2024年第12期46卷 1166-1178页

作者： Mudigonda, Krishna Siva Prasad Bulusu, Karthik Sri, Yashmitha Damera, Adithi Kode, Vignesh Department of Computer Science Engineering SRM-AP University Amaravati India

Emotion detection is one of the crucial topics of Natural Language Processing (NLP) in recent years, and now one of the biggest motivating factors in correct identification and interpretation of a wide range of emotional expressions in textual data. This research examines the use of Bidirectional Encoder Representations from Transformers (BERT), a trained transformer model for emotion detection in textual data. This analysis evaluates how good BERT is at identifying emotions such as surprise, anger, fear, happiness and sadness compared with ordinary machine learning as well as deep learning techniques. The addition of weighted emotions approach enhances the model performance and gives a deeper emotional context awareness making it more effective to deal with complicated emotional utterances. The purpose of the research is to develop a fine-tuned BERT model with a weighted emotion framework to enhance the accuracy of emotion classification in conversational text. The context is improving emotion recognition in scenarios where multiple emotions co-exist, addressing limitations in traditional models by capturing subtle and overlapping emotional expressions. In terms of training the methods multiple datasets are considered and also the research examines various models performance. The article further discusses possible application areas of BERT modified in light of NLP. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Emotion Recognition

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A high-capacity reversible data hiding with contrast enhancement and brightness preservation for medical images

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Multimedia Tools and Applications 2025年第8期84卷 5239-5264页

作者： Gandhi, Sonal Kumar, Rajeev Department of Computer Science and Engineering Delhi Technological University Delhi110042 India

The healthcare industry has witnessed an increase in the use of cloud storage, resulting in a significant demand for safeguarding medical records from potential attackers. In response to this challenge, reversible data hiding (RDH) has emerged as a lifesaver. The RDH ensures the concealment of private and confidential data with minimal loss to the cover image while offering opportunities for image enhancement. This paper introduces a new RDH method with contrast enhancement for medical images. The method aims to provide high embedding capacity (EC) while preserving brightness. To achieve this, the proposed method initially segments cover images into regions of interest (ROI) and non-regions of interest (NROI) and employs different embedding strategies based on the characteristics of each region, thereby enhancing embedding performance. Furthermore, a novel pre-processing technique is introduced for processing ROI pixels. This technique re-organizes and creates empty bins to provide enlarged EC with less distortion by capitalizing on the unique properties of medical images. Additionally, the proposed method embeds secret data in the NROI to further increase the EC. Experimental results show that the proposed method effectively preserves brightness (with 0.99 Relative Mean Brightness Error) while providing higher EC, exceeding the best-known methods by 20%. Furthermore, the method enhances contrast with minimal distortion in the output images. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Image segmentation

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MFR-CNN: A modified faster R-CNN approach based on bounding box and reliable score for cloth image retrieval

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Multimedia Tools and Applications 2024年 1-29页

作者： Kaur, Navneet Pandey, Shreelekha Kalra, Nidhi Department of Computer Science and Engineering Thapar Institute of Engineering & ampTechnology Punjab Patiala147004 India School of Computer Science and Engineering RV University South Karnataka Bangalore560059 India

Today, machine learning is used in a broad variety of applications. Convolution neural networks (CNN), in particular, are widely used to analyze visual data. The fashion industry is catching up to the growing usage of machine learning in a variety of fields throughout the world. The proposed model named MFR-CNN, which is a modified Faster R-CNN approach, has been presented in this manuscript. The effectiveness of an algorithm is validated on cloth attributes by established datasets such as the Deep Fashion dataset and the Fashion Landmark dataset, alongside a new dataset created for the same manually. The proposed model detects clothes using bounding boxes and further classifies them. Apart from this, retrieval functionality has also been added. The effectiveness of the proposed model is evident through the learning rate analysis done for the modules present in the same. On the metrics of accuracy, execution time, and total loss, the model proposed here is contrast with existing techniques named R-CNN, Fast R-CNN, and Faster R-CNN. It is found that MFR-CNN is 50% more accurate in contrast to R-CNN. Also, the accuracy of MFR-CNN is 30% and 7% more accurate than the Fast R-CNN and Faster R-CNN, respectively. Moreover, MFR-CNN is quite effective in contrast to other approaches as it takes less time for execution. It consumes 33 seconds less in contrast to R-CNN. Also, the time taken by the MFR-CNN is 17 seconds and 3 seconds less in comparison to Fast R-CNN and Faster R-CNN, respectively. From the experimental results it is being inferred that the MFR-CNN approach for detecting and classifying clothes is both efficient and effective. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Image retrieval

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III-nitride nanostructures: Selective area epitaxy, surface emitting lasers, and emerging photodetectors

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Semiconductors and Semimetals 2024年 116卷 1-23页

作者： Zhao, Songrui Department of Electrical and Computer Engineering McGill University MontrealQC Canada

ISBN: (纸本)9780443296888

III-nitride nanowires have emerged as an important semiconductor device technology development platform, leveraging the unique physical properties of III-nitride semiconductors such as widely tunable bandgap energies, as well as the merits of semiconductor nanowires such as the large surface area to the bulk volume ratio. The past ten years have witnessed a lot of exciting developments on III-nitride nanowire photonic devices. With limited text, the intention of this book chapter is to describe some of the key advances related to the III-nitride nanowire epitaxy, lasers, and photodetectors in the past few years. The prospect of III-nitride nanowire photonic devices in the next decade and beyond is also discussed, and they are expected to be the game changers for various applications such as display, imaging, and information processing, to just name a few. © 2024

关键词： Photonic devices

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Antenna Optimization using Machine Learning Algorithms and their Applications: A Review

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Journal of engineering Science and Technology Review 2024年第2期17卷 128-144页

作者： Pandey, Anil Kumar Singh, M.P. Department Of Computer Science & Engineering National Institute Of Technology Patna India

Antenna optimization using machine learning is a rapidly evolving field that leverages the power of artificial intelligence to design and improve antenna systems. Antenna optimization is a process of modifying antenna parameters to achieve desired performance metrics, such as gain, bandwidth, radiation pattern, and impedance matching. This paper presents a review of the most advanced development in antenna design and optimization by using machine learning techniques. The aim of this survey is to focus on different machine learning optimization techniques and their optimization capability with efficiency challenges. A deep outline from literature survey on optimization of antennas using machine learning are presented and listing various optimization algorithms and procedures that are applied to produce desired antenna characteristics and specifications. Firstly, a brief introduction of machine learning and its algorithms, later a quick explanation of antenna optimization process followed by an arranged introduction of different types of printed antenna designs using machine learning algorithm are reported. The methods emphasized in this survey have probably an effect on the imminent advancement of antennas for a variety of wireless applications. © (2024), (International Hellenic University – School of Science). All Rights Reserved.

关键词： Microstrip antennas

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A lightweight authentication and authorization method in IoT-based medical care

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Multimedia Tools and Applications 2025年第12期84卷 11137-11176页

作者： Khajehzadeh, Laleh Barati, Hamid Barati, Ali Department of Computer Engineering Dezful Branch Islamic Azad University Dezful Iran

The Internet of Things has opened up new opportunities in healthcare systems. Wireless sensor nodes are used to collect and exchange health-related data in the Internet of Things. In this integration, data is transmitted to medical professionals through unsecured channels to enable them to monitor patients’ conditions in real-time. However, due to the high sensitivity of e-health records, there are key challenges such as security considerations, privacy, and authentication in data transmission in heterogeneous Internet of Things networks. This article examines the solution proposed by Masud and colleagues and points out the existing threats and vulnerabilities, such as node clone/replication attacks. To overcome these drawbacks, we propose an improved lightweight authentication protocol for a smart healthcare system. In the proposed protocol, the mutual authentication process consists of two steps. The doctor sends their information for authentication and the desired sensor node ID to the gateway for communication. After successful confirmation of authentication, the gateway node, in turn, sends a message to the sensor node to complete the authentication process. After confirming the authentication process, the node sends a message to the gateway to complete the authentication process and key agreement. Once the authentication process of the sensor node is confirmed, the gateway sends a message to the medical user based on their authentication along with the session key. The security of the proposed protocol is demonstrated through automatic validation of protocols using tools like ProVerif and internet security programs. Additionally, security features and performance analysis are compared to other schemes. The results show that the improved proposed protocol provides a higher level of security while ensuring computational and communication efficiency. It is also resistant to attacks such as mutual authentication, identity anonymity and untraceability, ensures data

关键词： Authentication

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Strain modified nano-scale Ge/Ge0.98Sn0.02 exotic pin photo-sensor array for IR sensing: theoretical reliability and experimental feasibility studies

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Optical and Quantum Electronics 2024年第12期56卷 1-20页

作者： Bhadra, Bias Chinara, Suchismita Kundu, Abhijit Department of Computer Science and Engineering Chaibasa Engineering College Jharkhand Chaibasa India Department of Computer Science and Engineering NIT Rourkela Odisha Rourkela India Department of Electronics and Communication Engineering Chaibasa Engineering College Jharkhand Chaibasa India

In this paper, the superiority of Ge/Ge0.98Sn0.02asymmetrical supper lattice structure based vertically doped nano-scale pin photo-sensor under operating wavelength of 1200 nm to 2200 nm is reported. The authors have developed non-linear Strain Modified Quantum-Corrected Drift–Diffusion (SMQCDD) model for analyzing the electrical and optical characteristics of the photo-sensor. The inclusion of a small amount of Sn (2%) into the pure Ge material creates in-plane bi-axial strain in the intrinsic region (i-region) of the device. This results in increases in the value of the out-plane mobility of the charge particles. As a result, the overall performance of the photo-sensor enhances significantly. The authors have used in-plane induced bi-axial strain to accelerate the out-plane mobility of the charge particles by incorporation of the exotic asymmetrical supper lattice structure in the i-region of the photo-sensor. The validation of the non-linear SMQCDD model is performed through comparison of the simulated data obtained from SMQCDD model with the experimental results under a-like thermal/structural/electrical conditions. Additionally, the authors have designed 3X2 array of photo-sensors and studied the photo-electrical characteristics at the said operating wavelength. The proposed device offers better performance in terms of quantum efficiency (0.619: single-type photo-sensor;0.708: array-type photo) and photo-responsivity (0.056 A/W: single-type photo-sensor;0.808 A/W:for array-type photo-sensor)at 1600 nm wavelength compared to its conventional flat Si counterpart. The developed exotic pin photo-sensor can be used as a sensing device for applications in optical communication and bio-medical systems. As far as the authors are aware, this is the first report on nano-scale Ge/Ge0.98Sn0.02exotic pin photo-sensor. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Nanocrystals

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Extractive text summarization on medical insights using fine-tuned transformers

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International Journal of computers and Applications 2024年第11期46卷 957-973页

作者： Prasad Mudigonda, Krishna Siva Lingineni, Nikitha Manisai, Y. Pennada, Manoj Gadde, Mallesh Sai Aluri, Revanth Department of Computer Science and Engineering SRM University AP Mangalagiri India

Text summarization is a fundamental Natural language processing task that plays a crucial role in efficiently condensing large textual documents into concise and clear summaries for human comprehension. The amount of data being generated in the medical domain nowadays requires substantial application of the current deep learning approaches such as transformers. The main goal of this research is to extract relevant summaries from the abstracts of the research articles published related to cancer, blood cancer, tinnitus, and Alzheimer's. As the domain-related data requires special attention, our approach uses a fine-tuned transformer model, to guarantee that the summaries produced are not only brief but also accurate. Moreover, as a part of this research, we have effectively collected the information from PubMed and also prepared the data for analysis. A comparative analysis of the Bidirectional and Auto-Regressive Transformers (BART), Text-to-Text Transfer Transformer (T5), Textrank, and Lexrank models on the dataset is carried out in this study to understand the medical insights effectively. The fine-tuned transformer's performance in comparison with other models brings out a newer dimension for future studies. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Distribution transformers

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