This paper presents an advanced localization method for autonomous vehicles using an adaptive Kalman filter integrated with LiDAR-aided GNSS/IMU systems, addressing the challenges of GNSS reliability and precision in ...
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This paper provides a comparative analysis of the physical layer (PHY) characteristics of DECT-2020 NR and LTE-M, two critical standards for IoT communication. DECT-2020 NR, developed by ETSI, is intended for industri...
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A well-defined and well-designed experimentation process is crucial for meaningful research outcomes. This paper introduces a framework aimed at streamlining the experimentation process in networking testbeds, consist...
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The connection between approximate computations and artificial intelligence arises from employing algorithms and methodologies as exemplars for trained models across machine learning, neural networks, reinforcement le...
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Human emotions are unpredictable as they change very frequently. Human emotions areinvoluntary mental states of feelings and are accompanied by physiological changes. Emotions which can be detected through the facial ...
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Low-voltage flip-flops that operate reliably in a low-voltage regime are crucial for extending battery life in energy-constrained IoT applications. Minimizing dynamic power consumption is also vital for reducing overa...
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In this paper, we explore the design and operations of an inter-satellite data relay network, which includes Low Earth Orbit (LEO), Medium Earth Orbit (MEO), and Geo-stationary Orbit (GEO) satellites. Due to the diffe...
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A primary aim of Coarse-Grained Reconfigurable Arrays (CGRAs), compared to FPGAs, is to maximize the portion of the die used for computational resources, while minimizing the complexity of control and steering logic, ...
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This study has proposed a novel technique for performing object detection and image classification with a Convolutional Neural Network (CNN) architecture. Nevertheless, employing a 2D CNN architecture to identify a lo...
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A novel signal denoising method is proposed based on variational mode decomposition (VMD) and Anderson-Darling statistics. The VMD method expands a signal into its frequency components, i.e., time series corresponding...
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