Nowadays, the risk estimators are to be applied based on the population characteristics of their country, which is termed as race attribute. There were specific tools to determine the risk of cardiovascular disease. A...
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New security concerns about the transmission of sensitive data over enormous networks of linked devices have arisen with the advent of the 6G era and the broad adoption of massive machine-type communication (MTC). The...
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As the global population ages, sarcopenia - age-related muscle decline - demands innovative solutions. This paper introduces GRIPPY, a VR grip controller that transforms basic handgrip exercises into immersive, gamifi...
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This study builds an effective forecasting model for time series based on significant improvements of the fuzzy clustering algorithm. Firstly, we use the universal set, which is the percentage change between two conse...
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Neutrosophic Sets and Systems (NSS) has become an important Journal for neutrosophic theory and its applications in uncertainty modeling and decision sciences. In 2023, NSS celebrated its 10th anniversary, marking a d...
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This study introduces some novel soliton solutions and other analytic wave solutions for the highly dispersive perturbed nonlinear Schrödinger equation with generalized nonlocal laws and sextic-power law refracti...
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To address the low-voltage, high-current requirements in hydrogen production applications, a virtual 48-pulse three-phase rectifier is proposed, and achieves the equivalent performance of four parallel 12-pulse rectif...
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We present a third version of the PraK system designed around an effective text-image and image-image search model. The system integrates sub-image search options for localized context search for CLIP and image color/...
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In this paper, we introduce EMD-Based Hyperbolic Diffusion Distance (EMD-HDD), a new method for constructing a meaningful distance metric for hierarchical data with latent hierarchical structure. Our method relies on ...
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ISBN:
(数字)9798350368741
ISBN:
(纸本)9798350368758
In this paper, we introduce EMD-Based Hyperbolic Diffusion Distance (EMD-HDD), a new method for constructing a meaningful distance metric for hierarchical data with latent hierarchical structure. Our method relies on hyperbolic geometry, diffusion geometry, and the Earth Mover’s Distance (EMD). Specifically, our method embeds data points into a product manifold of hyperbolic spaces, allowing us to recover the hidden hierarchical structure encoded by the mutual relationships between features. We demonstrate the effectiveness of EMD-HDD through experiments on five hyperspectral imaging datasets, showcasing its capability to capture and reveal the intrinsic hierarchical structures inherent in such data.
The convergence of blockchain technology and artificial intelligence (AI) presents a promising solution for enhancing safety within the Internet of Vehicles (IoV) ecosystem. This paper introduces the "Blockchain-...
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The convergence of blockchain technology and artificial intelligence (AI) presents a promising solution for enhancing safety within the Internet of Vehicles (IoV) ecosystem. This paper introduces the "Blockchain-Based Collision Avoidance with AI for Vehicles" (BCA-CAR) algorithm, which aims to provide advanced and intelligent collision avoidance capabilities in IoV. BCA-CAR combines the security and data integrity features of blockchain with the real-time decision-making capabilities of AI to prevent collisions and improve road safety. The algorithm consists of five key phases: Data Collection and Processing, AI Collision Risk Assessment, Decision and Smart Contract Execution, Data Validation and Trust (Blockchain Integration), and Learning and Improvement. In the Data Collection and Processing phase, data from vehicle sensors, cameras, V2V and V2I communication, and external infrastructure is collected and preprocessed. The AI Collision Risk Assessment phase utilizes machine learning models to analyze real-time data and predict collision risks. In the Decision and Smart Contract Execution phase, smart contracts on the blockchain automate collision avoidance actions. The Data Validation and Trust phase ensures the authenticity and integrity of data through blockchain technology. Finally, the Learning and Improvement phase leverages historical collision data to enhance predictive models and overall system performance. BCA-CAR's primary objective is to enhance safety by preventing collisions, ensuring data trustworthiness, and providing intelligent collision avoidance capabilities. This innovative algorithm has the potential to revolutionize road safety in the era of IoV by reducing accidents, improving traffic management, and enhancing the security and privacy of vehicular communication. The findings highlight that Support Vector Regression (SVR) demonstrates strong predictive accuracy and adaptability within the Internet of Vehicles (IoV), offering a reliable modeli
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