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2023 IEEE International Ultrasonics Symposium, IUS 2023

作者： Salari, Soorena Rasoulian, Amirhossein Rivaz, Hassan Xiao, Yiming Concordia University Department of Computer Science and Software Engineering MontrealQC Canada Concordia University Department of Electrical and Computer Engineering MontrealQC Canada

ISBN: (纸本)9798350346459

Early surgical treatment of brain tumors is crucial in reducing patient mortality rates. However, brain tissue deformation (called brain shift) occurs during the surgery, rendering pre-operative images invalid. As a cost-effective and portable tool, intra-operative ultrasound (iUS) can track brain shift, and accurate MRI-iUS registration techniques can update pre-surgical plans and facilitate the interpretation of iUS. This can boost surgical safety and outcomes by maximizing tumor removal while avoiding eloquent regions. However, manual assessment of MRI-iUS registration results in real-time is difficult and prone to errors due to the 3D nature of the data. Automatic algorithms that can quantify the quality of inter-modal medical image registration outcomes can be highly beneficial. Therefore, we propose a novel deep-learning (DL) based framework with the Swin UNETR to automatically assess 3D-patch-wise dense error maps for MRI-iUS registration in iUS-guided brain tumor resection and show its performance with real clinical data for the first time. © 2023 IEEE.

关键词： Grading

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Design of an Efficient and Provable Secure Key Exchange Protocol for HTTP Cookies

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computers, Materials & Continua 2024年第7期80卷 263-280页

作者： Waseem Akram Khalid Mahmood Hafiz Burhan ul Haq Muhammad Asif Shehzad Ashraf Chaudhry Taeshik Shon Graduate School of Engineering Science and Technology National Yunlin University of Science and TechnologyYunlin64002TaiwanChina Future Technology Research Center National Yunlin University of Science and TechnologyYunlin64002TaiwanChina Department of Computer Science Lahore Garrison UniversityLahore54920Pakistan Department of Computer Science and Information Technology College of EngineeringAbu Dhabi UniversityAbu Dhabi69911United Arab Emirates Department of Software Engineering Faculty of Engineering and ArchitectureNisantasi UniversityIstanbul34398Turkey Department of Cybersecurity Ajou UniversitySuwon16499Republic of Korea

Cookies are considered a fundamental means of web application services for authenticating various Hypertext Transfer Protocol(HTTP)requests andmaintains the states of clients’information over the *** cookies are exploited to carry client patterns observed by a *** client patterns facilitate the particular client’s future visit to the corresponding ***,security and privacy are the primary concerns owing to the value of information over public channels and the storage of client information on the *** protocols have been introduced that maintain HTTP cookies,but many of those fail to achieve the required security,or require a lot of resource *** this article,we have introduced a lightweight Elliptic Curve Cryptographic(ECC)based protocol for authenticating client and server transactions to maintain the privacy and security of HTTP *** proposed protocol uses a secret key embedded within a *** proposed protocol ismore efficient and lightweight than related protocols because of its reduced computation,storage,and communication ***,the analysis presented in this paper confirms that proposed protocol resists various known attacks.

关键词： Cookies authentication protocol impersonation attack ECC

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ResMHA-Net:Enhancing Glioma Segmentation and Survival Prediction Using a Novel Deep Learning Framework

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computers, Materials & Continua 2024年第10期81卷 885-909页

作者： Novsheena Rasool Javaid Iqbal Bhat Najib Ben Aoun Abdullah Alharthi Niyaz Ahmad Wani Vikram Chopra Muhammad Shahid Anwar Department of Computer Science School of Engineering and TechnologyIslamic University of Science and TechnologyAwantipora192122India Faculty of Computing and Technology Al-Baha UniversityAlaqiq65779-7738Saudi Arabia Research Groups in Intelligent Machines National School of Engineers of SfaxUniversity of SfaxSfax3038Tunisia Department of Electrical Engineering College of EngineeringKing Khalid UniversityAbha61421Saudi Arabia Department of Computer Science and Engineering Thapar Institute of Engineering and TechnologyPatiala147004Punjab Department of Electrical and Instrumentation Engineering Thapar Institute of Engineering and TechnologyPatiala147004Punjab Department of AI and Software Gachon UniversitySeongnam-si13120Republic of Korea

Gliomas are aggressive brain tumors known for their heterogeneity,unclear borders,and diverse locations on Magnetic Resonance Imaging(MRI)*** factors present significant challenges for MRI-based segmentation,a crucial step for effective treatment planning and monitoring of glioma *** study proposes a novel deep learning framework,ResNet Multi-Head Attention U-Net(ResMHA-Net),to address these challenges and enhance glioma segmentation ***-Net leverages the strengths of both residual blocks from the ResNet architecture and multi-head attention *** powerful combination empowers the network to prioritize informative regions within the 3D MRI data and capture long-range *** doing so,ResMHANet effectively segments intricate glioma sub-regions and reduces the impact of uncertain tumor *** rigorously trained and validated ResMHA-Net on the BraTS 2018,2019,2020 and 2021 ***,ResMHA-Net achieved superior segmentation accuracy on the BraTS 2021 dataset compared to the previous years,demonstrating its remarkable adaptability and robustness across diverse ***,we collected the predicted masks obtained from three datasets to enhance survival prediction,effectively augmenting the dataset *** features were then extracted from these predicted masks and,along with clinical data,were used to train a novel ensemble learning-based machine learning model for survival *** model employs a voting mechanism aggregating predictions from multiple models,leading to significant improvements over existing *** ensemble approach capitalizes on the strengths of various models,resulting in more accurate and reliable predictions for patient ***,we achieved an impressive accuracy of 73%for overall survival(OS)prediction.

关键词： Glioma MRI segmentation multihead attention survival prediction deep learning

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Streamlining plant disease diagnosis with convolutional neural networks and edge devices

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Neural Computing and Applications 2024年第29期36卷 18445-18477页

作者： Ahamed, Md. Faysal Salam, Abdus Nahiduzzaman, Md. Abdullah-Al-Wadud, M. Islam, S. M. Riazul Department of Computer Science and Engineering Rajshahi University of Engineering & ampTechnology Rajshahi6204 Bangladesh Department of Electrical and Computer Engineering Rajshahi University of Engineering & ampTechnology Rajshahi6204 Bangladesh Department of Electrical Engineering Qatar University Doha Qatar Department of Software Engineering College of Computer and Information Sciences King Saud University Riyadh11543 Saudi Arabia School of Natural and Computing Sciences University of Aberdeen AberdeenAB24 3FX United Kingdom

In addressing labor-intensive process of manual plant disease detection, this article introduces an innovative solution—the lightweight parallel depthwise separable convolutional neural network (PDSCNN) coupled with a hybrid ridge regression extreme learning machine classifier. This combined approach automates plant disease classification, significantly expediting the learning process and reducing computational complexity. The PDSCNN model excels in feature capture, boasting a mere 9 layers and 0.053 million parameters, resulting in exceptional computational efficiency. On top of that, the classification performances of traditional ELM increased by introducing a hybrid ridge ELM model. Its accelerated operations, reduced memory usage, and optimized parallel processing render it lightweight and ideal for edge devices. The proposed framework exhibits remarkable efficacy, showcasing a precision of 95.76%, a recall of 89.29%, an F1-score of 91.25%, an accuracy of 94.22%, and an AUC of 99.72%. Moreover, training and testing times clock in at just 0.2314 and 0.0259 s, respectively. A comparative analysis against state-of-the-art transfer learning methods underscores its real-time analytical prowess. To demonstrate real-world applicability, we successfully validated our model on the Jetson Nano hardware, making it suitable for resource-constrained settings. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Computational efficiency

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Mapping Explicit and Implicit Discourse Relations between the RST-DT and the PDTB 3.0

Mapping Explicit and Implicit Discourse Relations between th...

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2023 International Conference Recent Advances in Natural Language Processing: Large Language Models for Natural Language Processing, RANLP 2023

作者： Costa, Nelson Filipe Sheikh, Nadia Kosseim, Leila Laboratory Department of Computer Science and Software Engineering Concordia University MontréalQC Canada

ISBN: (纸本)9789544520922

In this paper we propose a first empirical mapping between the RST-DT and the PDTB 3.0. We provide an original algorithm which allows the mapping of 6,510 (80.0%) explicit and implicit discourse relations between the overlapping articles of the RST-DT and PDTB 3.0 discourse annotated corpora. Results of the mapping show that while it is easier to align segments of implicit discourse relations, the mapping obtained between the aligned explicit discourse relations is more unambiguous. © 2023 Incoma Ltd. All rights reserved.

关键词： Mapping

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Social Media Competitive Analysis: A Case Study of Laptop Brands 4

Social Media Competitive Analysis: A Case Study of Laptop Br...

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4th International Conference on Computing, Mathematics and engineering Technologies, iCoMET 2023

作者： Hassan, Taimoor Ahmed, Abrar Anwar, Mehmood Gilani, Muhammad Basit Ali Qureshi, Muaz Ahmad University of Central Punjab Department of Software Engineering Lahore Pakistan The University of Lahore Department of Software Engineering Lahore Pakistan University of Central Punjab Department of Computer Science Lahore Pakistan The Islamia University of Bahawalpur Department of Computer Science Bahawalpur Pakistan

ISBN: (纸本)9798350335316

Most enterprises adopted social media for marketing purposes. Traditional media resources about one decade ago are now a day's costly and less productive than social media. Companies that are using social media like Facebook to provide different services and therefore to interact with customers, users produce a valuable content which is available on Facebook free of cost. To enhance market capitalization, expand value and effectiveness analyze competitor business strengths and value. Businesses must monitor social media sites of their own to see customer's response on their products and their competitor's social media to analyze behavior of customers. To help Enterprises to evaluate social media large amount of user generated content into knowledgeable information, decision making and future planning and targets. In this article case study, we are presenting is based on text mining to analyze content on Facebook in the well know top Five laptop brands named HP, Dell, Microsoft Surface, Toshiba, and Lenovo. The outcome showed the power, analysis of social media and text mining value to enhance business from the data available on social media freely. There are also some suggestions and recommendations to help organizations to plan and develop their strategy for social media to enhance business. © 2023 IEEE.

关键词： Sentiment analysis

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Future Intelligent Autonomous Robots, Ethical by Design. Lessons Learned from Autonomous Cars Ethics 14

Future Intelligent Autonomous Robots, Ethical by Design. Les...

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14th International Conference on Society and Information Technologies, ICSIT 2023

作者： Dodig-Crnkovic, Gordana Holstein, Tobias Pelliccione, Patrizio Thavarasa, Jathoosh Division of Computer Science and Software Engineering Mälardalen University Västerås Sweden Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden Department of Information Engineering Computer Science and Mathematics University of l'Aquila L'Aquila Italy Software Engineering Efrei Paris Villejuif France

ISBN: (纸本)9781950492701

The "ethical by design" approach involves examining all stages of a lifecycle of technology to ensure that they are ethically justifiable and socially sustainable. Building on our work on the ethics of autonomous intelligent robocars, and studies of the literature on the ethics of robotics, we propose for robot applications a set of values and ethical principles including safety, security, privacy, transparency, and explainability, accountability, fairness, human control, well-being, autonomy and freedom, and sustainability. This may help stakeholders in the field of intelligent autonomous robotics to connect ethical principles with their applications. Most ethical considerations we identified in our work on autonomous cars are relevant to all AI-powered robots, but robots require additional examination depending on their application domain, such as social robots (care robots, personal companions, robots used in education, health care, elderly care, education, entertainment, chat-bots), industrial robots, etcetera. Thus, existing ethical frameworks need to be applied in a context-sensitive way, by assessments in interdisciplinary, multi-competent teams through multi-criteria analysis. Furthermore, we argue for the need for continuous development of ethical principles, guidelines, and regulations, informed by the progress of technologies and involving relevant stakeholders. This implies designing the socio-technical system as an intelligent learning ecology. © 2023 Proceedings ICSIT, International Conference on Society and Information Technologies. All rights reserved.

关键词： Intelligent robots

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Arm PSA-Certified IoT Chip Security: A Case Study

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Tsinghua science and Technology 2023年第2期28卷 244-257页

作者： Fei Chen Duming Luo Jianqiang Li Victor C.M.Leung Shiqi Li Junfeng Fan College of Computer Science and Software Engineering Shenzhen UniversityShenzhen 518060China Department of Electrical and Computer Engineering the University of British ColumbiaVancouverBC V6T 1Z4Canada Open Security Research Inc.Shenzhen 518000China

With the large scale adoption of Internet of Things(IoT)applications in people’s lives and industrial manufacturing processes,IoT security has become an important problem *** security significantly relies on the security of the underlying hardware chip,which often contains critical information,such as encryption *** understand existing IoT chip security,this study analyzes the security of an IoT security chip that has obtained an Arm Platform Security Architecture(PSA)Level 2 *** analysis shows that the chip leaks part of the encryption key and presents a considerable security ***,we use commodity equipment to collect electromagnetic traces of the *** a statistical T-test,we find that the target chip has physical leakage during the AES encryption *** further use correlation analysis to locate the detailed encryption interval in the collected electromagnetic trace for the Advanced Encryption Standard(AES)encryption *** the basis of the intermediate value correlation analysis,we recover half of the 16-byte AES encryption *** repeat the process for three different tests;in all the tests,we obtain the same result,and we recover around 8 bytes of the 16-byte AES encryption ***,experimental results indicate that despite the Arm PSA Level 2 certification,the target security chip still suffers from physical *** layer application developers should impose strong security mechanisms in addition to those of the chip itself to ensure IoT application security.

关键词： Internet of Things(IoT)security chip Arm Platform Security Architecture(PSA)certification electromagnetic side-channel attack Advanced Encryption Standard(AES)encryption key leakage

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A Cloud-Based 3D Digital Twin for Arabic Sign Language Alphabet Using Machine Learning Object Detection Model 15

A Cloud-Based 3D Digital Twin for Arabic Sign Language Alpha...

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15th International Conference on Innovations in Information Technology, IIT 2023

作者： Abduljabbar, Mohammed Gochoo, Munkhjargal Sultan, Mohamad T. Batnasan, Ganzorig Otgonbold, Munkh-Erdene Berengueres, Jose Alnajjar, Fady Rasheed, Ashika Abdul Alshamsi, Ahmed Alsaedi, Naser United Arab Emirates University Department of Computer Science and Software Engineering United Arab Emirates

ISBN: (纸本)9798350382396

People with hearing loss or hard hearing struggle with daily life activities as sign language is not widely known by the public. There are many attempts to use technology to help assist hearing loss individuals. However, most proposed solutions are standalone applications or require special hardware like a wearable glove. Our goal is to leverage cloud computing and artificial intelligence (AI) to provide a solution that is portable and does not require any special hardware. We created a lightweight 3D model and rendered it on the browser along with another lightweight object detection model for Arabic Sign Language (ArSL) for real-Time detection. Our contribution is primarily based on integrating our novel functional lightweight 3D avatar model and a lightweight ArSL alphabet detection model, which is trained on public ArSL21L dataset, that are suitable to be given as a cloud service. Prototypes of the 3D digital twin avatar model and AI model are publicly offered for the research community on GitHub. We will be working on a full-scale real-Time cloud-based communication system in ArSL. © 2023 IEEE.

关键词： Object detection

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On Bounding the Behavior of a Neuron 36th

On Bounding the Behavior of a Neuron

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36th International Florida Artificial Intelligence Research Society Conference, FLAIRS-36 2023

作者： Borowski, Richard Choi, Arthur Computer Science Department College of Computing and Software Engineering Kennesaw State University United States

A neuron with binary inputs and a binary output represents a Boolean function. Our goal is to extract this Boolean function into a tractable representation that will facilitate the explanation and formal verification of a neuron's behavior. Unfortunately, extracting a neuron's Boolean function is in general an NP-hard problem. However, it was recently shown that prime im-plicants of this Boolean function can be enumerated efficiently, with only polynomial time delay. Building on this result, we propose a best-first search algorithm that is able to incrementally tighten inner and outer bounds of a neuron's Boolean function. These bounds correspond to truncated prime-implicant covers of the Boolean function. We provide two case studies that highlight our ability to bound the behavior of a neuron. © 2023 by the authors. All rights reserved.

关键词： Boolean functions

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