It has been revealed that in the conditions of small-scale production of discrete-analog filters on switched capacitors and ADC-drivers, it is most advisable to design high-speed operational amplifiers (OAs) based on ...
It has been revealed that in the conditions of small-scale production of discrete-analog filters on switched capacitors and ADC-drivers, it is most advisable to design high-speed operational amplifiers (OAs) based on the CBJT technological route and the MH2XA031 array chip, which allows operation in conditions of low temperatures and exposure to radiation. It has been established that most commercially produced $O A s$ provide an average value of the slew rate (SR, up to $200 \div 300 \mathrm{~V} / \mu \mathrm{s}$). This is largely due to the limitations of the technologies used, and most importantly, to the irrational design of circuits. We study the maximum performance parameters of a CBJT OA with one integrating capacitor, which ensures the stability of the $O A$, and a differentiating transient correction circuit, which is implemented by connecting additional small capacitors to the original circuit. In this case, the $S R$ of the $O A$ increases by more than 500 times (up to $4000 \mathrm{~V} / \mu \mathrm{s}$).
—The computing continuum, a novel paradigm that extends beyond the current silos of cloud and edge computing, can enable the seamless and dynamic deployment of applications across diverse infrastructures. By utilizin...
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Batteries are a central component of many complex systems, including mobile devices, sensors, electric vehicles, etc. Keeping the battery working in normal conditions avoids dangerous hazards for the user or the syste...
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ISBN:
(数字)9798331528010
ISBN:
(纸本)9798331528027
Batteries are a central component of many complex systems, including mobile devices, sensors, electric vehicles, etc. Keeping the battery working in normal conditions avoids dangerous hazards for the user or the system itself and helps extend the device’s life. The battery temperature is one of the most delicate aspects of these devices since some dangerous scenarios, like thermal runaway, could occur due to variable conditions. This paper uses a battery model of an electric vehicle from the automotive area as a case study to simulate the thermal response to normal usage. Then, thermal fault scenarios are modeled within equivalent circuital device descriptions and analyzed regarding state-of-charge, temperature, and voltage output. The findings presented offer a valuable starting point for improving the design phase of the batteries in multiple fields by testing fault scenarios already during simulation.
Sleep covers approximately one-third of life, providing the necessary recovery to fundamental body functions. Sleep deprivation and poor sleep quality cause several side effects in everyday life; among others, the eff...
Sleep covers approximately one-third of life, providing the necessary recovery to fundamental body functions. Sleep deprivation and poor sleep quality cause several side effects in everyday life; among others, the efficiency of the immune system progressively decreases, enhancing the arise of pathologies. Therefore, the evaluation of sleep quality is crucial for providing information about personal health status. However, a uniform and robust method for the assessment of sleep quality is still missing. In this preliminary study, Obstructive Sleep Apneas (OSAs), sleep macro pattern and sleep micro pattern are identified and then combined to provide a comprehensive sleep evaluation. For this purpose, a subset of physiological variables (HR, HRV, SpO 2 , body movements) is derived from Polysomnography (PSG) and exploited for the development of rule-based algorithms. This reduced parameter set is selected considering further implementations on wearable off-the-shelf commercial devices.
Enriching the robot representation of the operational environment is a challenging task that aims at bridging the gap between low-level sensor readings and high-level semantic understanding. Having a rich representati...
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In a recent paper it has been shown that the existence, for a MIMO nonlinear system, of normal forms with a special structure that proves to be useful in the design of feedback laws is implied by an assumption introdu...
In a recent paper it has been shown that the existence, for a MIMO nonlinear system, of normal forms with a special structure that proves to be useful in the design of feedback laws is implied by an assumption introduced a long time ago by Hirschorn in his work on systems invertibility. In this paper, we provide an alternative viewpoint and prove that a necessary and sufficient condition for the existence of such kind of normal forms can be identified in a special feature of the so-called maximal controlled invariant distribution algorithm.
This paper presents a novel methodology for closed-loop system identification of unstable nonlinear systems using the Koopman operator with Extended Dynamic Mode Decomposition with control (EDMDc). The study highlight...
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ISBN:
(数字)9798331505400
ISBN:
(纸本)9798331505417
This paper presents a novel methodology for closed-loop system identification of unstable nonlinear systems using the Koopman operator with Extended Dynamic Mode Decomposition with control (EDMDc). The study highlights the critical role of selecting appropriate observable functions to develop accurate and efficient Koopman models. We demonstrate that the resulting Koopman models exhibit excellent fitting and validation properties and retain the stabilizability of the original nonlinear systems. These models are verified through time and frequency responses under closed-loop control using a Linear Quadratic Regulator (LQR), confirming their effectiveness. Future work will extend this framework to more complex systems and incorporate machine learning techniques to refine the selection of observable functions. This approach aims further to enhance the adaptability and robustness of Koopman-based control strategies.
We propose kernel-based approaches for the construction of a single-step and multi-step predictor of the velocity form of nonlinear (NL) systems, which describes the time-difference dynamics of the corresponding NL sy...
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Colorectal cancer is the third most diagnosed cancer in the world, but it has a higher mortality rate in men compared to women. However, we are not close to understanding how and why sex influences the outcome of the ...
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Modern vehicular networks encounter a multitude of computation-intensive tasks that have unique processing topologies represented by graph structures. The integration of edge computing and vehicular networks has provi...
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ISBN:
(数字)9781728190549
ISBN:
(纸本)9781728190556
Modern vehicular networks encounter a multitude of computation-intensive tasks that have unique processing topologies represented by graph structures. The integration of edge computing and vehicular networks has provided a unique platform for handling these tasks at the network edge. However, the complex structure of these tasks makes their scheduling and execution challenging. This paper proposes a Vehicular Computing-assisted Edge Network (VCEN) architecture, where graph tasks are scheduled over a Vehicle-Edge Collaborative Cloud (VECC) for parallel execution. Our goal is to obtain feasible mappings between task components and computing nodes in the VECC while minimizing task execution latency and energy consumption. We show that achieving this goal requires solving an NP-hard optimization problem with complex constraints related to task structure and VECC topology. We then propose a fast and lightweight approach for graph task scheduling over VECC that comprises two key phases. In the former phase, we introduce a preprocessing algorithm that reduces the graph task's dimensionality by merging important components and cutting redundant edges. In the latter phase, we deploy a cost-reduction-preferred mapping algorithm to obtain feasible mappings between task components and VECC. Through simulations, we demonstrate our superior performance in different network settings.
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