作者：
Alsharif, MaramRawat, Danda B.
Department of Electrical Engineering & Computer Science WashingtonDC20059 United States
Machine learning based Intrusion detection (ML-IDS) has been long enforced for the protection of the IoT against malicious attacks. Researchers focused on improving ensemble intrusion detection methods in order to boo...
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Increasing the life span and efficiency of Multiprocessor System on Chip(MPSoC)by reducing power and energy utilization has become a critical chip design challenge for multiprocessor *** the advancement of technology,...
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Increasing the life span and efficiency of Multiprocessor System on Chip(MPSoC)by reducing power and energy utilization has become a critical chip design challenge for multiprocessor *** the advancement of technology,the performance management of central processing unit(CPU)is *** densities and thermal effects are quickly increasing in multi-core embedded technologies due to shrinking of chip *** energy consumption reaches a threshold that creates a delay in complementary metal oxide semiconductor(CMOS)circuits and reduces the speed by 10%–15%because excessive on-chip temperature shortens the chip’s life *** this paper,we address the scheduling&energy utilization problem by introducing and evaluating an optimal energy-aware earliest deadline first scheduling(EA-EDF)based technique formultiprocessor environments with task migration that enhances the performance and efficiency in multiprocessor systemon-chip while lowering energy and power *** selection of core andmigration of tasks prevents the system from reaching itsmaximumenergy utilization while effectively using the dynamic power management(DPM)*** in the execution of tasks the temperature and utilization factor(u_(i))on-chip increases that dissipate more *** proposed approach migrates such tasks to the core that produces less heat and consumes less power by distributing the load on other cores to lower the temperature and optimizes the duration of idle and sleep times across multiple *** performance of the EA-EDF algorithm was evaluated by an extensive set of experiments,where excellent results were reported when compared to other current techniques,the efficacy of the proposed methodology reduces the power and energy consumption by 4.3%–4.7%on a utilization of 6%,36%&46%at 520&624 MHz operating frequency when particularly in comparison to other energy-aware methods for *** are running and accurately scheduled to make an energy-efficient
We consider the domain adaptation problem in the context of label shift, where the label distributions between source and target domain differ, but the conditional distributions of features given the label are the sam...
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When developing and implementing ethical Artificial Intelligence (AI) in industrial settings, various viewpoints on building trustworthy AI emerge. This research emphasizes these differences and provides suggestions t...
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To reduce system complexity and bridge the interface between electronic and photonic circuits,there is a high demand for a non-volatile memory that can be accessed both electrically and ***,practical solutions are sti...
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To reduce system complexity and bridge the interface between electronic and photonic circuits,there is a high demand for a non-volatile memory that can be accessed both electrically and ***,practical solutions are still lacking when considering the potential for large-scale complementary metal-oxide semiconductor compatible ***,we present an experimental demonstration of a non-volatile photonic-electronic memory based on a 3-dimensional monolithic integrated ferroelectric-silicon ring *** successfully demonstrate programming and erasing the memory using both electrical and optical methods,assisted by optical-to-electrical-to-optical *** memory cell exhibits a high optical extinction ratio of 6.6 dB at a low working voltage of 5 V and an endurance of 4×10^(4) ***,the multi-level storage capability is analyzed in detail,revealing stable performance with a raw bit-error-rate smaller than 5.9×10^(−2).This ground-breaking work could be a key technology enabler for future hybrid electronic-photonic systems,targeting a wide range of applications such as photonic interconnect,high-speed data communication,and neuromorphic computing.
Conformal prediction is an uncertainty quantification method that constructs a prediction set for a previously unseen datum, ensuring the true label is included with a predetermined coverage probability. Adaptive conf...
Continual learning is referred to as machine learning model's ability to learn a sequence of tasks or data over time without forgetting previously learned knowledge. In particular, we focus on domain incremental l...
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In this paper a distributed exponential discrete-time sliding mode (DEDSM) protocol is designed for achieving the formation of Quadcopter swarm. The concept of leader-follower formation of discrete multi-agent system ...
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This paper investigates the performance of a frequency-sweeping steering notch beam implemented with a simple two-element antenna array operating within the frequency range of 238 to 248 GHz. We assess the performance...
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The automatic localization of the left ventricle(LV)in short-axis magnetic resonance(MR)images is a required step to process cardiac images using convolutional neural networks for the extraction of a region of interes...
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The automatic localization of the left ventricle(LV)in short-axis magnetic resonance(MR)images is a required step to process cardiac images using convolutional neural networks for the extraction of a region of interest(ROI).The precise extraction of the LV’s ROI from cardiac MRI images is crucial for detecting heart disorders via cardiac segmentation or ***,this task appears to be intricate due to the diversities in the size and shape of the LV and the scattering of surrounding tissues across different ***,this study proposed a region-based convolutional network(Faster R-CNN)for the LV localization from short-axis cardiac MRI images using a region proposal network(RPN)integrated with deep feature classification and *** was trained using images with corresponding bounding boxes(labels)around the LV,and various experiments were applied to select the appropriate layers and set the suitable *** experimental findings showthat the proposed modelwas adequate,with accuracy,precision,recall,and F1 score values of 0.91,0.94,0.95,and 0.95,*** model also allows the cropping of the detected area of LV,which is vital in reducing the computational cost and time during segmentation and classification ***,itwould be an ideal model and clinically applicable for diagnosing cardiac diseases.
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