This article presents a flexible and efficient methodology to optimize stack-up for multilayer printed circuit boards (PCBs) with enormous search space and various design constraints. PCB stack-up optimization is cruc...
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Deadlock resolution strategies based on siphon control are widely *** computational efficiency largely depends on siphon ***-integer programming(MIP)can be utilized for the computation of an emptiable siphon in a Petr...
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Deadlock resolution strategies based on siphon control are widely *** computational efficiency largely depends on siphon ***-integer programming(MIP)can be utilized for the computation of an emptiable siphon in a Petri net(PN).Based on it,deadlock resolution strategies can be designed without requiring complete siphon enumeration that has exponential *** to this reason,various MIP methods are proposed for various subclasses of *** work proposes an innovative MIP method to compute an emptiable minimal siphon(EMS)for a subclass of PNs named S^(4)*** particular,many particular structural characteristics of EMS in S4 PR are formalized as constraints,which greatly reduces the solution *** results show that the proposed MIP method has higher computational ***,the proposed method allows one to determine the liveness of an ordinary S^(4)PR.
In this paper, we propose a multi-input multi-output controller for optimal control of nonlinear energy storage, using deep reinforcement learning (DRL) algorithm. This controller provides the frequency support in an ...
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With the emergence of AI for good, there has been an increasing interest in building computer vision data-driven deep learning inclusive AI solutions. Sign language Recognition (SLR) has gained attention recently. It ...
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With the emergence of AI for good, there has been an increasing interest in building computer vision data-driven deep learning inclusive AI solutions. Sign language Recognition (SLR) has gained attention recently. It is an essential component of a sign-to-text translation system to support the deaf and hard-of-hearing population. This paper presents a computer VISIOn data-driven deep learning framework for Sign Language video Recognition (VisoSLR). VisioSLR provides a precise measurement of translating signs for developing an end-to-end computational translation system. Considering the scarcity of sign language datasets, which hinders the development of an accurate recognition model, we evaluate the performance of our framework by fine-tuning the very well-known YOLO models, which are built from a signs-unrelated collection of images and videos, using a small-sized sign language dataset. Gathering a sign language dataset for signs training would involve an enormous amount of time to collect and annotate videos in different environmental setups and multiple signers, in addition to the training time of a model. Numerical evaluations of VisioSLR show that our framework recognizes signs with a mean average precision of 97.4%, 97.1%, and 95.5% and 11, 12, and 12 milliseconds of recognition time on YOLOv8m, YOLOv9m, and YOLOv11m, respectively.
Artificial Intelligence (AI) approaches have been incorporated into modern learning environments and softwareengineering (SE) courses and curricula for several years. However, with the significant rise in popularity ...
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Peer review is an integral part of academic publication and is necessary to maintain high standards and novelty of published research. Despite its importance, peer reviewers are rarely provided incentives, leading to ...
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ISBN:
(数字)9781665410205
ISBN:
(纸本)9781665410212
Peer review is an integral part of academic publication and is necessary to maintain high standards and novelty of published research. Despite its importance, peer reviewers are rarely provided incentives, leading to journals having difficulty finding reviewers inclined to accept invitations and submit reviews on time. This paper proposes a Blockchain-based Anonymous Reviewer Incentive Token (BARIT) to incentivize peer reviewers. BARIT introduces flexible incentive schemes to provide both recognition and tangible benefits for the reviewers' contribution while preserving the anonymity of reviewers. Using blockchain technology to record reward tokens ensures their permanence and acceptance across different publishers. Incentive models are designed to encourage the involvement of researchers as reviewers, reduce reviewer refusal rates, and prompt the timely submission of review reports.
This paper examines the use of supervised machine learning to construct a digital twin model replicating a physical plant. An inverted pendulum simulation has been used as a case study.A comparative study was conducte...
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ISBN:
(数字)9781665464543
ISBN:
(纸本)9781665464550
This paper examines the use of supervised machine learning to construct a digital twin model replicating a physical plant. An inverted pendulum simulation has been used as a case study.A comparative study was conducted on single-step and multistep Dense models, Convolutional Neural Network (CNN), Recurrent Neural Net (RNN), and a Residual Neural Net (RNN2) models to investigate the most appropriate model for replicating the plant *** study found that single-step models were consistently more accurate than multi-step models due to single-step model’s iterative nature. Whereas, multi-step models were better at revealing prediction patterns and identifying causes for large deviations. The best-performing model was the RNN2 model, however, signs of overfitting were observed. In general, all models were able to take into account minor random actuation, however, large changes such as the pendulum falling over caused the models to behave sporadically.
The availability of technology and the expansive nature of the internet have created a surge in the demand for online learning. Despite so many advantages, there are some existing drawbacks related to online learning....
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Few-shot learning can potentially learn the target knowledge in extremely few data regimes. Existing few-shot medical image segmentation methods fail to consider the global anatomy correlation between the support and ...
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New storage requirements, analysis, and visualization of Big Data, which includes structured, semi-structured, and unstructured data, have caused the developers in the past decade to begin preferring Big Data database...
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