Nonlinearity modeling for online estimation of industrial cooling fan speed subject to model uncertainties and state-dependent measurement noise by Peng Chao-Chung, Tsai Min-Che, Chen Tsai-Ying

“…This article presents an online speed estimation method for cooling fans in resource-limited embedded systems, considering modeling uncertainties and measurement noise. …”
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Adaptive Multiclient Network-on-Chip Memory Core: Hardware Architecture, Software Abstraction Layer, and Application Exploration by Diana Göhringer, Lukas Meder, Stephan Werner, Oliver Oey, Jürgen Becker, Michael Hübner

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Developing a TinyML Image Classifier in an Hour by Riccardo Berta, Ali Dabbous, Luca Lazzaroni, Danilo Pietro Pau, Francesco Bellotti

“…., accuracy) and embedded systems (e.g., memory footprint, latency, and energy consumption). …”
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Evaluation of Machine Learning Algorithms for NB-IoT Module Energy Consumption Estimation Based on Radio Channel Quality by Dusan Bortnik, Vladimir Nikic, Srdjan Sobot, Dejan Vukobratovic, Ivan Mezei, Milan Lukic

“…Using these features, we tested 11 machine learning models for energy consumption estimation, assessing their performance and memory footprint, both of which are critical factors for resource-constrained embedded systems. Our best models achieved up to 93.8% of fit with measured values, with memory footprints below 100 KB, some as low as 3 KB. …”
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Formal Verification Method for Configuration of Integrated Modular Avionics System Using MARTE by Lisong Wang, Miaofang Chen, Jun Hu

“…In this paper, we focus on modelling and verification of configuration information of IMA/ARINC653 system based on MARTE (Modelling and Analysis for Real-time and Embedded Systems). Firstly, we define semantic mapping from key concepts of configuration (such as modules, partitions, memory, process, and communications) to components of MARTE element and propose a method for model transformation between XML-formatted configuration information and MARTE models. …”
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Noncontact Palm Vein ROI Extraction Based on Improved Lightweight HRnet in Complex Backgrounds by Fen Dai, Ziyang Wang, Xiangqun Zou, Rongwen Zhang, Xiaoling Deng

“…To reduce the computation time and model size for ultimate deploying in low-cost embedded systems, this improved HRnet was designed to be lightweight by reconstructing the residual block structure and adopting depth-separable convolution, which greatly reduced the model size and improved the inference speed of network forward propagation. …”
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Model of an automated control system for the positioning of radio signal transmission/reception devices by Bohdan Boriak, Alina Yanko, Oleksandr Laktionov

“…The objective of this research is to develop automated antenna positioning systems using embedded systems. This article provides an example of the system's operation, where the controller performs antenna positioning tasks with high accuracy for directional antennas, such as Yagi–Uda antennas, ensuring that the azimuth position control error does not exceed 15 degrees. …”
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Designing an internet of things laboratory to improve student understanding of secure IoT systems by A. Ravishankar Rao, Angela Elias-Medina

“…We describe our design for an embedded systems course taught at the graduate level for engineering and computer science students. …”
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Neural network quantification for solar radiation prediction: An approach for low power devices by Brenda Alejandra Villamizar-Medina, Angelo Joseph Soto Vergel, Byron Medina-Delgado, Darwin Orlando Cardozo-Sarmiento, Dinael Guevara-Ibarra, Oriana Alexandra Lopez-Bustamante

“…However, the proliferation of low-power smart devices, such as embedded systems and mobile devices, necessitates exploring methodologies for implementing ANN on systems with limited computational resources. …”
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Design of generic vedic ALU using reversible logic by Kanchan S. Tiwari

“…The proposed Generic low-power Vedic ALU using reversible logic opens up new opportunities for energy-efficient computing applications, such as portable devices, embedded systems, and Internet of Things (IoT) devices. …”
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Progressive Bitwidth Assignment Approaches for Efficient Capsule Networks Quantization by Mohsen Raji, Amir Ghazizadeh Ahsaei, Kimia Soroush, Behnam Ghavami

“…By using progressive bitwidth assignment and post-training quantization, this work optimizes CapsNets for efficient, real-time visual processing on resource-constrained edge devices, enabling applications in IoT, mobile platforms, and embedded systems.…”
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The Recent Technologies to Curb the Second-Wave of COVID-19 Pandemic by M. Poongodi, Mohit Malviya, Mounir Hamdi, Hafiz Tayyab Rauf, Seifedine Kadry, Orawit Thinnukool

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Design of low-carbon planning model for vehicle path based on adaptive multi-strategy ant colony optimization algorithm by Qi Guo, Rui Li, Changjiang Zheng, Gwanggil Jeon

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