A brain computer interface (BCI) system uses a technique known calibration, that takes 20 to 30 minutes to accomplish. For the objective of creating a reliable decoder, the calibration process is challenging and expen...
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ISBN:
(数字)9798350394634
ISBN:
(纸本)9798350394641
A brain computer interface (BCI) system uses a technique known calibration, that takes 20 to 30 minutes to accomplish. For the objective of creating a reliable decoder, the calibration process is challenging and expensive. In order to address the drawbacks of the current system, a spectral-spatial technique has been suggested. The motor imagery (MI) data set, comprising 15 electroencephalography (EEG) signals and fourteen test subjects, is taken into consideration. The two modules are designed to extract characteristics and process data. An artificial neural network (ANN) is used to independently train and test the suggested spectral-spatial algorithm. Based on it, a variety of machine learning techniques, including random forest (RF), neural networks (NN), and XGboost, are used to classify the data, that is then sent to the hidden layer (Lth layer). The obtained results indicates 2% of improvement in comparison with existing methodology.
Given a flow network with variable suppliers and fixed consumers, the minimax flow problem consists in minimizing the maximum flow between nodes, subject to flow conservation and capacity constraints. We solve this pr...
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Federated Learning (FL) represents a popular distributed learning architecture that facilitates data privacy by enabling clients (e.g., mobile devices) to train a FL model collaboratively without data sharing. Existin...
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ISBN:
(数字)9798350378412
ISBN:
(纸本)9798350378429
Federated Learning (FL) represents a popular distributed learning architecture that facilitates data privacy by enabling clients (e.g., mobile devices) to train a FL model collaboratively without data sharing. Existing efforts mainly focus on accuracy, delay and energy consumption over a rather stable network with certain clients, with less emphasis on the impact of frequent decision-making processes during model training. Inspired by this, this paper considers a dynamic FL network with uncertain participation of clients, while we jointly optimize client selection and communication resource allocation to achieve a balance between energy cost and FL model accuracy, as proved to be NP-hard. To facilitate timely model training, we propose a prediction-based two-stage asynchronous programming mechanism, which decouples the problem in two subproblems, corresponding to two stages. In particular, the former stage determines some long-term clients which are more stable to join in prior to practical model training process, by estimating the online probability of clients. Then, the latter stage can be implemented by involving some temporary clients as backups when long-term ones are not able to show up. Such a well-designed mechanism offers a unique veiw on FL, while enabling a responsive and cost-effective decision-making process. Comprehensive simulations regarding both IID and non-IID data distributions on MNIST and CIFAR-10 datasets can prove our commendable performance on time efficiency, energy cost and accuracy.
We introduce a goal-aware extension of responsibility-sensitive safety (RSS), a recent methodology for rule-based safety guarantee for automated driving systems (ADS). Making RSS rules guarantee goal achievement—in a...
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ISBN:
(数字)9798350348811
ISBN:
(纸本)9798350348828
We introduce a goal-aware extension of responsibility-sensitive safety (RSS), a recent methodology for rule-based safety guarantee for automated driving systems (ADS). Making RSS rules guarantee goal achievement—in addition to collision avoidance as in the original RSS—requires complex planning over long sequences of manoeuvres. To deal with the complexity, we introduce a compositional reasoning framework based on program logic, in which one can systematically develop RSS rules for smaller subscenarios and combine them to obtain RSS rules for bigger scenarios. As the basis of the framework, we introduce a program logic dFHL that accommodates continuous dynamics and safety conditions. Our framework presents a dFHL-based workflow for deriving goal-aware RSS rules; we discuss its software support, too. We conducted experimental evaluation using RSS rules in a safety architecture. Its results show that goal-aware RSS is indeed effective in realising both collision avoidance and goal achievement.
The CFETs can provide high-performance characteristics with significant area reduction for Å technology nodes. However, mobilities between n/p FETs need to be considered for the performance balance of CMOS. This ...
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ISBN:
(数字)9798350391633
ISBN:
(纸本)9798350391640
The CFETs can provide high-performance characteristics with significant area reduction for Å technology nodes. However, mobilities between n/p FETs need to be considered for the performance balance of CMOS. This paper introduces heterogeneous and hetero-orientational CFETs using wafer bonding and layer-transfer techniques.
This paper conducts a comprehensive analysis of electrical generator performance using Finite Element Analysis (FEA), with a specific emphasis on the role of coil numbers in influencing generator efficiency and functi...
This paper conducts a comprehensive analysis of electrical generator performance using Finite Element Analysis (FEA), with a specific emphasis on the role of coil numbers in influencing generator efficiency and functionality. In the context of modern energy systems, where efficient power generation is paramount, this research aims to elucidate the relationship between the number of coils within a generator and its overall performance, including power output and electromagnetic behavior. Through systematic FEA simulations that vary coil numbers while keeping other parameters constant, this study provides valuable insights into the trade-offs associated with increased coil numbers and enhanced efficiency. These findings have significant implications for optimizing generator designs across various applications, from renewable energy systems to industrial power generation, ultimately advancing our understanding of generator dynamics and contributing to more sustainable and efficient power generation technologies.
Food waste is a serious problem that occurs in various countries. Indonesia is a country that produces food waste, the second largest after Saudi Arabia. Currently, there are several communities who care about the iss...
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Edge computing is characterised by a varying workload intensity that has a strong effect in the applications performance and their resource requirements. Thus, in order to maintain a sustainable performance a resource...
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Existing Deep Learning (DL) frameworks typically do not provide ready-to-use solutions for robotics, where very specific learning, reasoning, and embodiment problems exist. Their relatively steep learning curve and th...
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We experimentally report on a real-time self-guided method to search for maximal CHSH violations between two observers sharing polarization entangled photon pairs using uncalibrated piezoelectric fiber squeezers as po...
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ISBN:
(纸本)9781957171258
We experimentally report on a real-time self-guided method to search for maximal CHSH violations between two observers sharing polarization entangled photon pairs using uncalibrated piezoelectric fiber squeezers as polarization controllers.
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