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An Explainable Artificial Intelligence model in the assessment of Brain MRI Lesions in Multiple Sclerosis using Amplitude Modulation – Frequency Modulation multi-scale feature sets

An Explainable Artificial Intelligence model in the assessme...

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International Conference on Digital Signal Processing (DSP)

作者： Andria Nicolaou Antonis Kakas Constantinos S. Pattichis Marios S. Pattichis Kevin Fotso Christos P. Loizou Marios Pantzaris Department of Computer Science University of Cyprus Nicosia Cyprus Department of Electrical Engineering and Computer Engineering University of New Mexico USA Department of Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus Cyprus Institute of Neurology and Genetics Nicosia Cyprus

The objective of this study was to implement an explainable artificial intelligence (AI) model with embedded rules to assess Multiple Sclerosis (MS) disease evolution based on brain Magnetic Resonance Imaging (MRI) multi-scale lesion evaluation. Amplitude Modulation-Frequency Modulation (AM-FM) features were extracted from manually segmented brain MS lesions obtained using MRI and were labeled with the Expanded Disability Status Scale (EDSS). Machine learning models were used to classify the MS subjects with a benign course of the disease and subjects with advanced accumulating disability. Rules were extracted from the selected model with high accuracy and then were modified to perform argumentation-based reasoning. It is demonstrated that the proposed explainable AI modeling can distinguish MS subjects and give meaningful information to track the progression of the disease. Future research will examine more subjects and add new feature sets and models.

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Examine the Impact of Visual Content when Used in Mixed Media Applications 15

Examine the Impact of Visual Content when Used in Mixed Medi...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Rajiv Gandhi, N. Goyal, Shitij Pattanaik, Ashutosh Tamkhade, Jayashree Kuppuraj, T. Pandey, Noopor Prince Shri Venkateshwara Padmavathy Engineering College Department of Civil Engineering Chennai127 India Quantum University Research Center Quantum University India School of Engineering and Technology Mechaical Engineering Karnataka Bangalore India E&TC Vishwakarma Institute of Information Technology Pune India Karpagam Academy of Higher Education Department of Computer Applications Coimbatore641 021 India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India

ISBN: (纸本)9798350370249

Visible content in mixed media programs may have a large effect on its customers. By combining both visible and auditory elements, it permits users to have an extra immersive revel in terms of eating the content. Visible content material consisting of pics, films, diagrams, and so forth. It can all be used to in addition enhance enjoyment while used as a complement or number one source of records. Visuals can simplify complicated ideas and provide a less complicated way to navigate through products or services. It may be specifically useful in academic contexts. Moreover, visible content material can be used to increase Engagement via telling a story or thrillingly providing information. It helps create a connection between the consumer and the content material and makes the revel extra memorable. In the end, visuals can encourage user interplay with interactive elements along with buttons, menus, and bureaucracy, all of which can decorate the user experience. The use of visual content in combined media applications may have a full-size effect on the person's enjoyment. Through the incorporation of visuals, customers can benefit from a higher knowledge of the context and cause of the utility, in addition to an immersive experience that similarly complements the content material offered. © 2024 IEEE.

关键词： FORTH (programming language)

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Single photon flux imaging with sub-pixel resolution by motion compensation 17

Single photon flux imaging with sub-pixel resolution by moti...

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Advanced Photon Counting Techniques XVII 2023

作者： Laurenzis, Martin Bacher, Emmanuel Seets, Trevor Ingle, Atul Velten, Andreas Christnacher, Frank French-German Research Institute of Saint-Louis 5 Rue du General Cassagnou Saint-Louis68301 France Department of Electrical and Computer Engineering University of Wisconsin-Madison MadisonWI53706 United States Department of Computer Science Portland State University PortlandOR97201 United States Department of Biostatistics and Medical Informatics University of Wisconsin-Madison MadisonWI53706 United States

ISBN: (纸本)9781510661387

Single photon counting avalanche diodes (SPADs) are versatile sensors for active and time-correlated measurements such as ranging and fluorescence imaging. These detectors also have great potential for passive or uncorrelated imaging. Recently, it was demonstrated that passive imaging of photon flux is possible by determining the mean photon arrival time. For ambient light illumination, timestamp data can be interpreted as a metric for the photon impingement rate. Various applications have been investigated including high-dynamic-range imaging, single-photon imaging, and capture of fast-moving objects or dynamic scenes. However, the appearance of noise and motion blur requires sophisticated signal processing that enables sub-pixel resolution imaging and reconstruction of the scene by motion compensation. In this paper, we present new results on the evaluation of global scene motion. In our approach, motion is intentionally generated by a rotating wedge prism, resulting in continuous global motion on a circular path. We have studied scenes with different optical contrast. © 2023 SPIE.

关键词： Avalanche diodes

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Air Quality Improvement and Optimisation Using Machine Learning Technique 2

Air Quality Improvement and Optimisation Using Machine Learn...

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2nd IEEE International Conference on Advances in Computing, Communication and Applied informatics, ACCAI 2023

作者： Veeranjaneyulu, Rayavarapu Boopathi, Sampath Kumari, R. Krishna Vidyarthi, Anurag Isaac, J. Samson Jaiganesh, V. Pace Institute of Technology & Sciences Department of Computer Science Engineering Andhra Pradesh Ongole523272 India Muthayammal Engineering College Department of Mechanical Engineering Tamil Nadu Namakkal637408 India College of Engineering and Technology Srm Institute of Science and Technology Department of Career Development Centre Tamil Nadu Kattankulathur603203 India Graphic Era Deemed to Be University Department of Electronics & Communication Engineering Uttarakhand Dehradun248002 India Karunya Institute of Technology and Sciences Department of Biomedical Engineering Tamil Nadu Coimbatore641114 India Bharath Institute of Higher Education and Research Department of Mechanical Engineering Tamil Nadu Chennai600063 India

ISBN: (纸本)9798350315905

Due to the increased use of automobiles, the manufacturing industry, and the emission of pollutants from other human activities, air pollution has risen above the expected safety level. Accurate estimating of the air quality index(AQI) is essential for effective pollution control. In this research, an AQI prediction ANFIS network model was created utilizing an already-existing data set. In this instance, the ANFIS system compares the performances of the back propagation neural network model, hybrid models, the Gaussian-BNN model, and the Gaussian-hybrid BNN model. Based on the actual raw data set, it was noted that the R and IA values of the Gaussian hybrid model are 0.9899. The ANFIS gauss-hybrid model might therefore be used to predict the most accurate model data. © 2023 IEEE.

关键词： Quality control

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Traffic Sign Recognition Using Convolutional Neural Networks with Transfer Learning for Advanced Driving Assistance Systems (ADAS) 6th

Traffic Sign Recognition Using Convolutional Neural Networks...

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6th International Conference on Advanced informatics for Computing research, ICAICR 2023

作者： Tiwari, Aditya Upadhyay, Arsh Patel, Neel Goel, Parth Department of Computer Science and Engineering Devang Patel Institute of Advance Technology and Research Charotar University of Science and Technology Changa Gujarat Anand388421 India

ISBN: (纸本)9783031840616

Traffic Sign recognition is a crucial part of current systems of transportation and Advanced Driving Assistance Systems (ADAS). The safe operation of an autonomous vehicle and the effective management of road infrastructure depend on a traffic sign recognition system. Existing techniques to traffic sign identification often face difficulties to classify the traffic signs accurately and resulting in lower reliability in identifying critical traffic signs. This limitation compromises road safety and prevents ADAS from reaching its maximum potential. The research focuses to classify the Indian traffic signs using transfer learning with a pre-trained model. The pre-trained convolutional neural networks (CNNs) such as ResNet50, Xception, DenseNet121, and EfficientNetB5 are used to develop the convolutional and pooling layers that are used in the proposed framework. In order to help with accurate classification of traffic indicators, fully-connected layers as well as an output layer have also been developed. The proposed method is thoroughly tested using the Kaggle Indian Traffic Signal Prediction dataset, which contains 85 distinct types of traffic signals regularly noticed on Indian highways. The test outcomes show that ResNet50 outperformed among the four pre-trained CNNs, with an impressive testing accuracy of 86.47% and a training accuracy of 89.91%. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Advanced driver assistance systems

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The influence of coordinated behavior on toxicity

arXiv

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arXiv 2023年

作者： Loru, Edoardo Cinelli, Matteo Tesconi, Maurizio Quattrociocchi, Walter Department of Computer Control and Management Engineering Sapienza University of Rome Italy Department of Computer Science Sapienza University of Rome Italy Institute of Informatics and Telematics National Research Council

In the intricate landscape of social media, genuine content dissemination may be altered by a number of threats. Coordinated Behavior (CB), defined as orchestrated efforts by entities to deceive or mislead users about their identity and intentions, emerges as a tactic to exploit or manipulate online discourse. This study delves into the relationship between CB and toxic conversation on X (formerly known as Twitter). Using a dataset of 11 million tweets from 1 million users preceding the 2019 UK general election, we show that users displaying CB typically disseminate less harmful content, irrespective of political affiliation. However, distinct toxicity patterns emerge among different coordinated cohorts. Compared to their non-CB counterparts, CB participants show marginally higher toxicity levels only when considering their original posts. We further show the effects of CB-driven toxic content on non-CB users, gauging its impact based on political leanings. Our findings suggest that CB only has a limited impact on the toxicity of digital discourse. Please cite published version: https://***/10.1016/***.2024.100289 © 2023, CC BY.

关键词： Tweets

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Sub-diffraction limited direct diode Laser patterning of methacrylic polymer thin films doped with silver nanoparticles 18

Sub-diffraction limited direct diode Laser patterning of met...

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Laser-based Micro- and Nanoprocessing XVIII 2024

作者： Sinani, Alexandra Karachousos-Spiliotakopoulos, Konstantinos Tangoulis, Vassilis Manouras, Theodoros Angelakos, Evangelos Riziotis, Christos Theoretical and Physical Chemistry Institute National Hellenic Research Foundation Athens11635 Greece Department of Informatics and Computer Engineering University of West Attica Egaleo12243 Greece Laboratory of Inorganic Chemistry Department of Chemistry University of Patras Patras26504 Greece Institute of Electronic Structure and Laser FORTH Heraklion71110 Greece Opticon ABEE Peloponnesus Tripoli22100 Greece Defence & Security Research Institute University of Nicosia Nicosia2417 Cyprus

ISBN: (纸本)9781510670068

High quality poly(methyl methacrylate) (PMMA) thin nanocomposite films doped with different concentration of silver (Ag) nanoparticles are demonstrated. SEM and TEM confirmed the presence of Ag-PMMA nanocomposites with excellent dispersion of Ag nanoparticles into the PMMA matrix and nanoparticles with an average size of 9 nm. By using a direct Laser writing system with a continuous wave 405 nm diode Laser source the films were exposed, allowing the formation of hole-like or linear patterns in the sub 200nm regime, using a 280nm FWHM sized laser spot, demonstrating, for the first time, the potential for sub-diffraction limit laser processing in such 2-material composite systems. © 2024 SPIE.

关键词： Silver nanoparticles

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A Lightweight and Robust Access Control Protocol for IoT-based e-Healthcare Network

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IEEE Transactions on Mobile Computing 2025年

作者： Ghaffar, Zahid Kuo, Wen-Chung Mahmood, Khalid Tariq, Tayyaba Shamshad, Salman Das, Ashok Kumar Alenazi, Mohammed J.F. National Yunlin University of Science and Technology Graduate School of Engineering Science and Technology Douliu64002 Taiwan National Yunlin University of Science and Technology Department of Computer Science and Information Engineering Douliu64002 Taiwan National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan The University of Lahore Department of Software Engineering Lahore54590 Pakistan International Institute of Information Technology Center for Security Theory and Algorithmic Research Hyderabad500 032 India Korea University Department of Computer Science and Engineering College of Informatics 145 Anam-ro Seongbuk-gu Seoul02841 Korea Republic of King Saud University College of Computer and Information Sciences Department of Computer Engineering Riyadh Saudi Arabia

Internet of Things (IoT) devices are crucial components in e-healthcare networks. It enables remote patient health monitoring and facilitates seamless communication among medical sensors, wearable devices, and healthcare providers through public communication channels. Despite these advantages, the use of public communication among medical sensors in e-healthcare networks introduces critical challenges, such as vulnerability to impersonation, physical capture, and ephemeral secret leakage, particularly in resource-constrained environments. In recent years, various access control protocols have been developed to mitigate these risks. However, these protocols often fail to ensure robust security while incurring significant communication and computation overhead. To overcome these limitations, we propose a lightweight and robust access control protocol for IoT-based e-healthcare networks using chaotic maps. We propose a novel protocol that integrates a PUF-based mechanism to mitigate the challenges of physical tampering and cloning attacks in e-healthcare networks. It leverages the inherent uniqueness of PUF and enhances security through the high-entropy properties of chaotic maps. We analyze the proposed protocol informally, which confirms that it significantly bolsters efficiency and security. We also validate the security using the Random or Real (RoR) model. Moreover, we verify the security of the proposed protocol using Scyther. These analyses highlight that the proposed protocol offers robust resistance to numerous attacks, such as impersonation, physical capture, and ephemeral secret leakage. Moreover, we also compare it with existing and relevant protocols. The comparative analysis showcases its superior performance. Notably, the proposed authentication protocol significantly reduces 46.84% computational overhead and decreases 31.30% communication overhead, underscoring its enhanced performance and resource efficiency. © 2002-2012 IEEE.

关键词： Authentication

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Distributed Secret Securing in Discrete-Event Systems

Distributed Secret Securing in Discrete-Event Systems

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American Control Conference (ACC)

作者： Shoma Matsui Kai Cai Karen Rudie Department of Electrical and Computer Engineering Ingenuity Labs Research Institute Queen's University Kingston Canada Department of Core Informatics Osaka Metropolitan University Osaka Japan

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

In this paper, we study a security problem of protecting secrets in distributed systems. Specifically, we employ discrete-event systems to describe the structure and behaviour of distributed systems, in which global secret information is separated into pieces and stored in local component agents. The goal is to prevent such secrets from being exposed to intruders by imposing appropriate protection measures. This problem is formulated as to ensure that at least one piece of every distributed global secret is secured by a required number of protections, while the overall cost to apply protections is minimum. We first characterize the solvability of this security problem by providing a necessary and sufficient condition, and then develop an algorithm to compute a solution based on the supervisory control theory of discrete-event systems. Finally, we illustrate the effectiveness of our solution with an example system comprising distributed databases.

关键词： Sufficient conditions Costs Distributed databases Supervisory control Discrete-event systems Security Protection

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Assessment of Post-Disaster Concerns using Social Network Analysis and Machine Learning: A Study of 2018 Palu Disaster

Assessment of Post-Disaster Concerns using Social Network An...

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International Conference on Information and Communication Technologies for Disaster Management (ICT-DM)

作者： Tyanita Puti Marindah Wardhani Subhajyoti Samaddar Hirokazu Tatano Zulkifli Tahir Sudip Roy Department of Informatics Faculty of Engineering Universitas Hasanuddin Makassar Indonesia Disaster Prevention Research Institute Kyoto University Kyoto Japan Centre of Excellence in Disaster Mitigation and Management (CoEDMM) Department of Computer Science and Engineering Indian Institute of Technology Roorkee India

ISBN: (数字)9798350367928

ISBN: (纸本)9798350367935

Post-disaster needs assessment plays a critical role in developing emergency response programs and disaster preparedness. An assessment of needs identifies possible interventions or assistance and the necessary resources for emergency responses. This emergency need assessment assists stakeholders in defining possible response options, evaluating the priorities of needs of affected communities, and determining what support will be required immediately. The prevalent use of social media in Indonesia highlights its significance as a crucial means of acquiring prompt, effortless, individualized, and geo-specific information regarding the demands and requirements of communities impacted by a calamity. This study aims to analyze the tweets posted by local communities affected by the 2018 Central Sulawesi earthquakes, tsunami, and liquefaction using the Social Network Analysis (SNA) method based on machine learning and natural language processing. Through this analysis, we intend to observe the spatial interaction and relationship among the affected areas of communities for the needs and concerns after the disaster to enhance the relief operation. We found that social media users, government, and humanitarian organizations effectively shared information during the disaster. This study also underlined that the behavioral responses of individuals to disasters were not limited to the disaster-stricken areas but extended far beyond them. This action suggests that they were willing to exhibit a more empathetic, benevolent, and philanthropic demeanor in the face of such traumatic events.

关键词： Social networking (online) Disasters Government Information sharing Machine learning Tsunami Natural language processing Stakeholders Open data Videos

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