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2022 2nd Conference on High Performance Computing and Communication engineering, HPCCE 2022

作者： Jin, Qinchao Yang, Peihao Wang, Tiantian Wu, Xianghu Wang, Kechao School of Computer Science and Technology Harbin Institute of Technology Harbin China School of Information Engineering Harbin University Harbin China

ISBN: (纸本)9781510663374

With the development and application of model-based systems engineering (MBSE), it is more and more accepted and valued in the aerospace field, and system modeling language (SysML), as the most popular model language for MBSE, has become more and more important for the correctness and safety verification of its models. SysML views are described from different angles of the development system in MBSE, and it is very important to verify the relationship between each view, so this article summarizes how to extend its model verification part based on the open source project Papyrus, and successfully extends the correlation validation between various views of SysML. © 2023 SPIE.

关键词： Modeling languages

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An authenticated spectrum acquirement and transmission of encrypted images over fusion centre

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Multimedia Tools and Applications 2024年 1-24页

作者： V, Thanikaiselvan Y, PiyaDessi S, Renuga devi Shanthini, S. Suba Mahalingam, Hemalatha S, Aashiq Banu R, Dhivya V.M, Padmapriya Amirtharajan, Rengarajan School of Electronics Engineering Vellore Institute of Technology Vellore Vellore India School of Information Technology Vellore Institute of Technology Vellore India Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah22254 Saudi Arabia System Engineering Department Military Technological College Muscat Oman Department of Electronics and Communication Engineering Mepco Schlenk Engineering College Tamilnadu Sivakasi626005 India Department of Computer Sciences Marquette University MilwaukeeWI53233 United States School of Electrical & amp Electronics Engineering SASTRA Deemed University 613 401 Thanjavur India

These days, spectrum insufficiency is the most common issue. If the number of smartphone users who access the radio spectrum grows, the radio spectrum becomes increasingly scarce. Certain types of technology equipment are designed to work only within a specific spectrum range, and there is rivalry in specifications for various other applications. As a result, this paper effectively exploits a licensed user’s unused spectrum to reduce the crowded spectrum and eradicate the Radio spectrum shortage. Licensed primary users (PUs) and secondary users (SUs) would be accepted into a Fusion Centre (FC) based on a spectrum framework with authentication. The approved PUs begin by updating their information to FC1;thenceforth, encryption is performed on the information uploaded to FC1. This information from FC1 is stored in Cloud Storage after encryption using the Blowfish algorithm & De-oxy DNA, a fast encryption algorithm. Following that, FC2, connected to the same cloud environment, downloads the PU data uploaded. The spectrum is then allocated to the authenticated SU linked to FC2 based on signal conditions and priority. This proposed method also avoids any delay in the network and encryption by acquiring a fast encryption algorithm, making the system faster and avoiding the Primary User Emulation (PUE) attack. Later, the time taken for the Tiny Encryption Algorithm (TEA) and the Blowfish/DNA algorithm are compared to validate the run time for different input images. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Authentication

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AI-Based Primary Diagnosis of Ocular Health via Smartphone 17

AI-Based Primary Diagnosis of Ocular Health via Smartphone

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17th International Conference on Signal Processing and Communication Systems, ICSPCS 2024

作者： Hammoud, Houssam Al Aref, Mohammad Yaman Al Jabouli, Mayar Hammoud, Mohamad Shehieb, Wessam Arshad, Kamran Ajman Univeristy College of Engineering and Information Technology Department of Biomedical Engineering Ajman United Arab Emirates Ajman Univeristy College of Engineering and Information Technology Department of Electrical and Computer Engineering Ajman United Arab Emirates Ajman University Artificial Intelligence Research Centre Ajman United Arab Emirates

ISBN: (纸本)9798350389630

Traditional diagnostic methods such as Fundus cameras and slit-lamps that are used for diagnosing various ocular diseases are often limited by their cost and accessibility which hinders timely intervention especially in rural areas and indigent societies with limited resources. While the current research is mostly focused on classification of single diseases or expensive setups, the proposed work aims to address these limitations by developing a cost-effective and user-friendly system for primary diagnosis of various ocular diseases, including Diabetic Retinopathy, Age-Related Macular Degeneration and Glaucoma. The proposed work utilizes a smartphone, cloud-based deep learning model, and a 3D printed multi-lens holder for fundus imaging. This research leverages open-source datasets for model training and testing, added to new sets of images that were collected throughout this work for validation. The new set tested the quality of the captured images in actual setup and verified accurate classification. Based on the results, the system has been successfully implemented and the overall classification accuracy of the multi-classification ResNet-50 model is 74%. Preliminary results demonstrate the potential of this approach for multi-classification of ocular diseases, marking a significant advancement in portable ocular health primary diagnostics. © 2024 IEEE.

关键词： Smartphones

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Medical Reports Simplification Using Large Language Models 23th

Medical Reports Simplification Using Large Language Models

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23rd International Conference on Intelligent Systems Design and Applications, ISDA 2023

作者： Almezhghwi, Khaled Hassan, Morad Ali Ghadedo, Adel Belhaj, Fairouz Shwehdi, Rabei Electrical and Electronics Engineering College of Electronics Technology Tripoli Tripoli Libya Computer Science Bani Waleed University Bani Waleed Libya Computer Science College of Electronics Technology Tripoli Tripoli Libya Computer Information Systems Higher Institute of Science and Technology Tripoli Libya Electrical and Electronics Engineering College of Electronics Technology Tripoli Tripoli Libya

ISBN: (纸本)9783031648120

Making medical reports easily understandable for a wider audience is a significant endeavor, and the recent advancements in deep learning and large language models offer a promising solution. In our research, we have introduced a fine-tuned Text-to-Text Transformer (T5) model to efficiently summarize these medical reports. Our model is trained and assessed on the publicly accessible Indiana Dataset. To gauge its effectiveness, we employ the ROUGE metrics. The outcomes we've achieved hold promise for the potential of this approach in enhancing medical report summarization. By harnessing the power of cutting-edge technology, we aim to make medical information more accessible and comprehensible to everyone. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Deep learning

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Optimal Task Allocation for Battery-Assisted and Price-Aware Mobile Edge Computing

IEEE Networking Letters

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IEEE Networking Letters 2023年第4期5卷 199-203页

作者： Deng, Tao You, Lei Yu, Zhanwei Yuan, Di Soochow University School of Computer Science and Technology Suzhou215006 China Technical University of Denmark Department of Engineering Technology Ballerup2750 Denmark Uppsala University Department of Information Technology Uppsala751 05 Sweden

In this letter, we propose a battery-assisted approach to improve energy efficiency for mobile edge computing (MEC) networks by utilizing the space-time-varying characteristics of electricity price. We formulate a price-aware task allocation problem (PATA) that jointly considers the cost for task computation, the cost of task offloading, and the cost of battery degradation. PATA is seemingly a mixed integer non-linear programming problem. By a graph-based reformulation, solving PATA is mapped to finding minimum cost flows or convex cost flows in the graph. This discovery reveals that the global optimum of PATA is obtained in polynomial time. Performance evaluation manifests that the proposed approach significantly outperforms other approaches. © 2019 IEEE.

关键词： Integer programming

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GRU and GAN for aspect based Web Service Classification 21

GRU and GAN for aspect based Web Service Classification

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21st OITS International Conference on information technology, OCIT 2023

作者： Sridevi, S. Karpagam, G.R. Vinoth Kumar, B. Arasi, Ezhil Vellore Institute of Technology School of Computer Science and Engineering Vellore632014 India PSG College of Technology Department of Computer Science and Engineering Coimbatore641004 India PSG College of Technology Department of Information Technology Coimbatore641004 India

ISBN: (纸本)9798350358230

With the advent of the "Programmable Web"paradigm, the World Wide Web is transitioning into a "Web of Services,"where data and services may be successfully reused across applications. Service discovery is a major obstacle for the creation of service-based applications because of the vast diversity and scope of public Web services. The restricted availability of frameworks for intelligent categorization and service management actually makes this scenario more difficult. The strategy provided in this research extends service similarity characterization by morphological analysis and machine learning techniques for extracting the functional semantics of real-world Web services to support fruitful classification. To capture the functional diversity of the services, at present a deep learning model namely Gated Recurrent Unit (GRU) model performs well. However, the GRU model lacks in extracting the sparse features tags between functional values. For that a recently a Generative Adversarial Networks (GAN) has been used. The objective of using GAN is to extract abstract tag between the sparse features to enhance the classification accuracy. The efficacy of proposed research is verified with other existing works. © 2023 IEEE.

关键词： Generative adversarial networks

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Lung Cancer Identification from CT Scans using a Soft-attention enabled Deep Transfer Learning Model 3

Lung Cancer Identification from CT Scans using a Soft-attent...

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3rd International Conference on Intelligent Systems, Advanced Computing, and Communication, ISACC 2025

作者： Dev, Shubhro Roy, Pragyadipta Sinha Chakraborty, Neelotpal Chakraborty, cNeelotpal Sarkar, Ram Rajiv Gandhi Institute of Petroleum Technology Department of Computer Science & Engineering Uttar Pradesh 229305 India KIIT University Department of Computer Science & Engineering Bhubaneswar751024 India RCC Institute of Information Technology Department of Computer Science & Engineering Kolkata700015 India Jadavpur University Department of Computer Science & Engineering Kolkata700032 India

ISBN: (纸本)9798331523893

Being a major contributor to the global mortality, lung cancer, owing to its fatality, calls for early and efficient diagnosis. This requires the employment of efficient computer aided diagnostics for determining the computed tomography (CT) scans as indicating lung cancer or not. Most such systems leverage the high efficiency of deep learning models to identify the lung cancer type from an input CT scan. In this work, a deep transfer learning model equipped with a soft attention block is framed to classify CT scans as either lung cancer affected or normal. Public datasets such as IQ-OTH/NCCD along with LIDC-IDRI are adopted for evaluation of the proposed technique which scored accuracies of 99.55% and 95.41% respectively, that are comparable with those of some recent standard techniques. © 2025 IEEE.

关键词： Deep learning

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Secrecy Capacity Analysis with Imperfect Channel State information and Varying Interference for 6G C-V2X Communication 10

Secrecy Capacity Analysis with Imperfect Channel State Infor...

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10th International Conference on Wireless Networks and Mobile Communications, WINCOM 2023

作者： Ayaz, Hina Abbas, Ghulam Abbas, Ziaul Haq Waqas, Muhammad Gik Institute of Engineering Sciences and Technology Facutly of Computer Science and Engineering Topi23460 Pakistan Research Center Topi23460 Pakistan University of Bahrain College of Information Technology Computer Engineering Department 32038 Bahrain

ISBN: (纸本)9798350329674

It has been observed that the use of radio-frequency fingerprinting (RF-FP) for location estimation (LE) of vehicles can significantly improve secrecy capacity (SC) for urban scenarios in 6th generation cellular vehicle-to-everything (6G C-V2X) communication. However, in most of the literature, interference is considered constant for simplicity. Thus, there is a need to investigate the impact of varying levels of interference and incomplete channel state information (CSI) on the performance of SC. This study examines the impact of shadowing and interference in the presence of heavy traffic and obstructions. We have proposed a technique that analyzes the effects of varying levels of interference for LE via RF-FP to improve SC with incomplete CSI. Simulation results demonstrate that interference has a significant impact on SC which depends on the distance and location of the eavesdropping vehicle. However, a decrease in SC is not solely caused by the increase in interference, since other factors, such as the speed and relative position of the illegitimate vehicles as well as incomplete CSI, can also significantly affect the SC performance, as demonstrated through simulations. © 2023 IEEE.

关键词： Vehicle to Everything

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A UAV-Based Remote Sensing Image Automatic Monitoring System Empowered by Artificial Intelligence

A UAV-Based Remote Sensing Image Automatic Monitoring System...

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2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems, IACIS 2024

作者： Liu, Tao Zhang, Bohan College of Computer Science and Technology Heilongjiang Institute of Technology Harbin China School of Information Engineering China University of Geosciences Wuhan Wuhan China State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan China

ISBN: (纸本)9798350360660

In this study, an automatic monitoring system based on convolutional neural network (CNN) is proposed to address the automation and accuracy of remote sensing image processing. With the maturity and wide application of remote sensing and UAV technologies, efficient and accurate image analysis methods have become particularly important. We developed this system through in-depth research on multiple stages of data preprocessing, feature extraction and model training. In the experimental stage, through the comparison experiments with Support Vector Machine (SVM) and Random Forest (RF) models, it is found that the CNN model has significant advantages in processing speed, anti-interference ability and accuracy. Especially in the processing of urban remote sensing images, CNN exhibits up to 90% accuracy, showing its wide applicability and excellent cross-domain application capability. Overall, this study not only successfully develops an efficient and accurate automatic monitoring system for remote sensing images, but also provides strong theoretical and experimental support for future optimization of CNN architecture in natural environments, improvement of real-time data processing capability, and extension to practical applications such as disaster monitoring and environmental protection. © 2024 IEEE.

关键词： Environmental monitoring

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On Detection of Hardware Trojan in Memristive Nanocrossbar-Based Circuits 3rd

On Detection of Hardware Trojan in Memristive Nanocrossbar-B...

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The 3rd International Conference on Frontiers in Computing and Systems (COMSYS 2022)

作者： Basu, Subhashree Ghoshal, Ranjit Kule, Malay Department of Information Technology St. Thomas’ College of Engineering and Technology Kidderpore Kolkata India Department of Computer Science and Technology Indian Institute of Engineering Science and Technology Shibpur India

ISBN: (纸本)9789819926794

Chip fabrication outsourcing can lead to malicious modifications by third-party companies and could pose a grave danger to the chip’s security and reliability. Such changes in the functionality of the IC or the addition of extra features is known as Hardware Trojan which cannot be detected by design-time verification and post-fabrication testing. Hence, methods of identification of Hardware Trojan are not only tedious but sometimes futile. Though some techniques have been designed, they are only for Trojan detection. There is as such no way to eliminate the Trojan. Not only that, but some of these methods also impart the chip unusable. In this paper, we study the insertion and detection of Trojan in a BCD square root circuit implemented in a memristive nanocrossbar. First, we insert the active and passive Trojan, and then we discuss the methods of identifying the Trojans therein. The experimental results obtained in our work are satisfactory and prove the correctness of the proposed method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Hardware security

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