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International Workshop on Quality of Multimedia Experience, QoMEx

作者： Mitra Amiri Steven Le Moan Christian Herglotz Dept. of Computer Science ColorLab Norwegian University of Science and Technology (NTNU) Gjøvik Norway Chair of Computer Engineering Brandenburgisch-Technische Universität Cottbus-Senftenberg Cottbus Germany

ISBN: (数字)9798350361582

ISBN: (纸本)9798350361599

What the human visual system can perceive is strongly limited by the capacity of our working memory and attention. Such limitations result in the human observer’s inability to perceive large-scale changes in a stimulus, a phenomenon known as change blindness. In this paper, we started with the premise that this phenomenon can be exploited in video coding, especially HDR-video compression where the bitrate is high. We designed an HDR-video encoding approach that relies on spatially and temporally varying quantization parameters within the framework of HEVC video encoding. In the absence of a reliable change blindness prediction model, to extract compression candidate regions (CCR) we used an existing saliency prediction algorithm. We explored different configurations and carried out a subjective study to test our hypothesis. While our methodology did not lead to significantly superior performance in terms of the ratio between perceived quality and bitrate, we were able to determine potential flaws in our methodology, such as the employed saliency model for CCR prediction (chosen for computational efficiency, but eventually not sufficiently accurate), as well as a very strong subjective bias due to observers priming themselves early on in the experiment about the type of artifacts they should look for, thus creating a scenario with little ecological validity.

关键词： Accuracy Biological system modeling Semantics Bit rate Blindness Predictive models Observers

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Synergistic Skin Cancer Classification: Vision Transformer alongside MobileNetV2

Synergistic Skin Cancer Classification: Vision Transformer a...

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Intelligent Technologies (CONIT), International Conference on

作者： M Ranjith Kumar S Priyanga Janani Srinivasan Anusha Veda Chatiyode Jerome Santiago P Revathi School of Computer Science and Engineering Vellore Institute of Technology Chennai India Dept. of Computer Science and Engg. Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India Dept. of Computer Science and Engg. C. Abdul Hakeem College of Engg. and Tech. Melvisharam Vellore India

ISBN: (数字)9798350349900

ISBN: (纸本)9798350349917

Skin cancer is one of the most common types of cancer in the world, and it poses major health risks due to its ability to spread quickly and metastasize. Early and accurate identification is crucial for treatment success and improved patient outcomes. This proposed work combines the MobileNetV2 and Vision Transformer (ViT) architectures to create a hybrid automated skin cancer classification technique. This technique aims to increase the accuracy and efficiency of dermatological diagnosis tools by combining MobileNetV2’s effective feature extraction capabilities with ViT’s self-attention mechanism. After testing on the HAM10000 dataset, this hybrid model outperformed individual models with a remarkable $96.3 \%$ classification accuracy. Not only did the integration of ViT and MobileNetV2 improve the classification accuracy but it also demonstrated how various deep-learning architectures work together to tackle complex image analysis tasks. Classifying skin cancers is critical to the medical industry because it allows for the early diagnosis of various dermatological disorders, allowing prompt intervention and treatment. These benefits can eventually improve patient outcomes and save lives in huge numbers. The findings of this research highlight the potential of deep learning to transform dermatological diagnostics and open the door to creating systems that will significantly impact clinical practice by detecting skin cancer with greater accuracy and efficiency.

关键词： Deep learning computer vision Accuracy Computational modeling computer architecture Transforms Transformers

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Integrative Technologies for Real-Time Crowd Management: A Case Study of the Hajj 18

Integrative Technologies for Real-Time Crowd Management: A C...

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18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Almutairi, Mishaal M. Apostolopoulou, Dimitra Stupples, David Sen, Adnan Ahmed Abi Yamin, Mohammad Halikias, George City University of London School of Science and Technology Dept. of Electrical and Electronic Engg. London United Kingdom Islamic University Deanship of Information Technology Madinah Saudi Arabia The Australian National University School of Computing College of Engineering and Computer Science Canberra Australia University of Athens Department of Mathematics Greece

ISBN: (纸本)9789380544519

Crowd management is a very complex process, which requires the integration of many technologies together to create a reliable tool in crowd flow control. The historical events resulting from stampedes are the greatest evidence of the need for an effective solution. Relying on one method is not a reliable solution in such critical systems that require real-time response. The purpose of this research is to develop a smart framework that uses Artificial Intelligence (AI) and other technologies to control and manage crowds. The methodology involved conducting literature review and using a case study of Hajj event to develop a Python-based solution for running the framework. The findings shows that the framework is effective in crowd management, but it would be improved using advanced machine learning techniques. The proposed approach will help government agencies and other bodies to focus on adopting modern levels of technology in crowd management. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： artificial intelligence crowd management Hajj privacy security

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A Quick Heuristic Algorithm for Enforcing the Liveness of S3PR Petri Nets 22

A Quick Heuristic Algorithm for Enforcing the Liveness of S3...

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22nd International Symposium INFOTEH-JAHORINA, INFOTEH 2023

作者： Karatkevich, Andrei Grobelna, Iwona Agh University of Science and Technology Dept. of Applied Computer Science Kraków Poland University of Zielona Góra Autom. Control Electronics and Electr. Eng. Zielona Góra Poland

ISBN: (纸本)9781665475464

The optimal deadlock avoiding, deadlock recovery, as well as deadlock detection in Petri nets are the NP-hard problems. For this reason, heuristic algorithms for finding the approximate solutions of such problems are of a great interest. In the paper a heuristic method of deadlock recovery for the S3PR nets, which are often used for modelling of manufacturing systems, is proposed. The method is based on the idea of resetting the process instances in the S3PR nets and a heuristic for breaking the cycles in the wait-for graphs. The method does not require any time consuming operations such as construction of the reachability graph, explicit detecting of all reachable deadlocks or all elementary cycles in a wait-for graph, hence it is quick. The simple recovery transitions are added to the net providing recovery from both global and local deadlocks. © 2023 IEEE.

关键词： Petri nets

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Smart DeFi Lending: Intelligent NFT-Backed Loans Framework for Risk Management in DeFi Platforms

Smart DeFi Lending: Intelligent NFT-Backed Loans Framework f...

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IEEE UP Section Conference on Electrical computer and Electronics (UPCON)

作者： Keyaba Gohil Krisha Darji Ayushi Shah Rajesh Gupta Sudeep Tanwar Sahil Sawhney Dept. of Computer Sci. and Engg. Inst. of Technology Nirma University Ahmedabad India Dept. of Computer Sci. and Engg. Model Inst. of Engg. & Tech. J&K India

ISBN: (数字)9798350378726

ISBN: (纸本)9798350378733

There has been a major change in the financial environment with the recent transition of traditional banking systems towards Decentralized Finance (DeFi). A decentralized alternative that includes DeFi, lessens conventional financial institutions’ drawbacks and improves privacy, transparency, transaction speed, and worldwide accessibility. The work presented here shows an Intelligent NFT-Backed Loans Framework for valuing and managing risk in the DeFi ecosystem. The architecture uses blockchain technology, smart contracts, and artificial intelligence to assure transaction security and integrity. In DeFi, we use Google Colaboratory to build a framework and evaluate its performance across five crossvalidation folds. With a maximum accuracy of 87.35 %, the framework demonstrates its efficacy and consistency over a wide range of data subsets. Using performance evaluation over 5 cross folds for training and validation data, this model enhances loan transaction security by identifying benign nodes for efficient valuation and compliance. Performance evaluation for DeFi extends to training and validation accuracy and loss over 5 folds, and also testing accuracy for 5 folds. This methodology maintains the integrity and security of NFT-backed loans by detecting unauthorized nodes on Proof of Stake permissionless blockchains.

关键词： Training Performance evaluation Proof of stake Privacy Accuracy Smart contracts Finance Decentralized applications Risk management Testing

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Newton-Euler Modeling of Robot Dynamics Using Geometric Algebra

Newton-Euler Modeling of Robot Dynamics Using Geometric Alge...

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International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Eduardo Bayro-Corrochano Daniel Alvarado-Mejia Institute of Automatic Control and Robotics Poznan University of Technology Dept. Electrical Engineering and Computer Science CINVESTAV Guadalajara Mexico

ISBN: (数字)9798350362343

ISBN: (纸本)9798350362350

In this work, we present the modeling of the dynamics of a robot manipulator using the Newton-Euler algorithm in the conformal algebra framework. The modeling of the dynamics of robot manipulators is currently done using the Euler-Lagrange formulation which is a batch type of computation. In contrast, in this paper, we propose a recursive algorithm for the modeling of the dynamics of robot manipulators using the Newton-Euler algorithm in the conformal geometric algebra framework.

关键词： Algebra Heuristic algorithms Computational modeling Optimal control Motors Real-time systems Mathematical models

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Enhancing Segmentation of Abdominal Aortic Aneurysms in CT Images

Enhancing Segmentation of Abdominal Aortic Aneurysms in CT I...

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2023 International Conference on Data Science and Network Security, ICDSNS 2023

作者： Saleem Javeed, Abdul Veeresh, K.M. Ganesh, V.N. Lavanya, Chunduri Parameshachari, B.D. Gst Gitam University Bengaluru Campus Dept. of Cse Bengaluru India Sjbit Dept. of Cse Bengaluru India Mangalore Institute of Technology and Engineering Department of Ece Moodabidri India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Vaadeswaram India Nitte Meenakshi Institute of Technology Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350301595

This study concentrates on a potential strategy for improving Abdominal aortic aneurysms (AAAs) segmentation in CT imaging. The study's dataset included 19 CT images of healthy AAAs acquired from different patients. Ground-truth segmentations that matched the training data were also included. For enhanced accuracy while segmenting AAA, the suggested technique integrates pre-processing, deep learning segmentation, and post-processing into a cohesive workflow. Convolutional neural networks (CNNs) are trained for deep learning segmentation using a U-Net architecture, and noise in input pictures is removed during pre-processing. This differs from the conventional habit of employing linear regression for image segmentation. The results were measured using the dice similarity coefficient, sensitivity, specificity, accuracy, recall, and F1 score. With a DSC of 0.81, sensitivity of 0.89, specificity of 0.97, accuracy of 0.86, recall of 0.89, and F1 score of 0.86, the suggested approach was proven to be successful in segmenting AAAs in CT images. The technique has shown potential in clinical settings for improving AAA diagnosis and treatment planning. © 2023 IEEE.

关键词： Image segmentation

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PCB Based Modulated Scatter with Enhanced Modulation dept.

PCB Based Modulated Scatter with Enhanced Modulation Depth

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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2023

作者： Crocker, Dylan A. Donnell, Kristen M. Amazon Web Services Inc. SeattleWA98109 United States Missouri University of Science and Technology Microwave Sensing Lab. Dept. of Electrical and Computer Engineering RollaMO65409 United States

ISBN: (纸本)9781665442282

The modulated scatterer technique (MST) has shown promise for applications in microwave imaging, electric field mapping, and materials characterization. Traditionally, MST scatterers are dipoles centrally loaded with an element capable of modulation (e.g., a PIN diode). By modulating the load element state, the scattered fields are also modulated. However, due to the small size of such scatterers, it can be difficult to reliably detect the response. Increasing the modulation dept. (MD) of the scattered signal may improve detectability. This paper presents simulations and measurements of PCB-based MST elements that, through reactive loading, are designed to be electrically invisible during the reverse bias state of the modulated element (a PIN diode in this case) while producing detectable scattering during the forward bias state. The results show a significant (> 90%) improvement in the MD of the scattered signal when compared to a traditional MST scatterer. © 2023 IEEE.

关键词： Polychlorinated biphenyls

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Moving Robots in Unknown Environments Using Potential Field Graphs 2

Moving Robots in Unknown Environments Using Potential Field ...

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2nd International Conference on Advanced Research in Computing, ICARC 2022

作者： Panagoda, Mithila Lokuliyanage, Minuli Senarath, Amadi Nisansala, N.K.V.M. Nethmini Rajapakshe, R.W.A.D.U. Rajapaksha, U.U. Samantha Jayawardena, Chandimal Sri Lanka Institute of Information Technology Dept. of Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Dept. of Information Technology Malabe Sri Lanka Sri Lanka Institute of Information Technology Deprt. of Computer System and Engineering Malabe Sri Lanka

ISBN: (纸本)9781665407410

The purpose of this research paper is to introduce a new navigation algorithm for Robot Operating System (ROS) based robots which will allow complete autonomous traversal in any given indoor environment. Turtle bot3 burger bot is the sample robot chosen for this project. This will be equipped with a Light Detection and Ranging (LIDAR) scanner with the default settings, ultrasound, Intel Real Sense camera, etc. Environment information gathered via these sensors will be sent into a remote computer for processing since the raspberry pie micro-controller with the turtle bot burger is not enough to carry out a high computation-intensive task. Once the information is received series of tasks will be carried out by the remote personal computer before executing the newly developed navigation algorithm. The data from the LIDAR scanner help to generate a 2-dimensional(2D) potential field graph. Then it will later be used for path planning by navigation algorithm. Furthermore, the Real sense camera is used for object boundary detection to produce more accurate data for the navigation algorithm. Once all the data proceed, data will return to the robot, where the navigation algorithm will start execution in parallel with a recovery behavior algorithm and scan algorithm. The recovery behavior algorithm is responsible for guiding the robot to face away from an obstacle in an event where the predetermined path is obstructed. Furthermore, it is responsible for maintaining accurate data in the cost map. Subsequently, the scanning algorithm will be used to generate maps. © 2022 IEEE.

关键词： Cameras

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Post-Quantum Secure UE-to-UE Communications

arXiv

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arXiv 2024年

作者： Hoque, Sanzida Aydeger, Abdullah Zeydan, Engin Dept. of Electrical Engineering and Computer Science Florida Institute of Technology MelbourneFL United States Barcelona08860 Spain

The rapid development of quantum computing poses a significant threat to the security of current cryptographic systems, including those used in User Equipment (UE) for mobile communications. Conventional cryptographic algorithms such as Rivest-Shamir-Adleman (RSA) and Elliptic curve cryptography (ECC) are vulnerable to quantum computing attacks, which could jeopardize the confidentiality, integrity, and availability of sensitive data transmitted by UEs. This demo paper proposes the integration of Post-Quantum Cryptography (PQC) in TLS for UE Communication to mitigate the risks of quantum attacks. We present our setup and explain each of the components used. We also provide the entire workflow of the demo for other researchers to replicate the same setup. By addressing the implementation of PQC within a 5G network to secure UE-to-UE communication, this research aims to pave the way for developing quantum-resistant mobile devices and securing the future of wireless communications. © 2024, CC BY.

关键词： Quantum computers

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