As a kind of grid-forming control method that can effectively provide virtual inertia for the power grid, the virtual synchronous generator (VSG) control has received increasing attention in recent years. However, the...
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Student performance prediction helps the educational stakeholders to take proactive decisions and make interventions,for the improvement of quality of education and to meet the dynamic needs of *** selection of featur...
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Student performance prediction helps the educational stakeholders to take proactive decisions and make interventions,for the improvement of quality of education and to meet the dynamic needs of *** selection of features for student’s performance prediction not only plays significant role in increasing prediction accuracy,but also helps in building the strategic plans for the improvement of students’academic *** are different feature selection algorithms for predicting the performance of students,however the studies reported in the literature claim that there are different pros and cons of existing feature selection algorithms in selection of optimal *** this paper,a hybrid feature selection framework(using feature-fusion)is designed to identify the significant features and associated features with target class,to predict the performance of *** main goal of the proposed hybrid feature selection is not only to improve the prediction accuracy,but also to identify optimal features for building productive strategies for the improvement in students’academic *** key difference between proposed hybrid feature selection framework and existing hybrid feature selection framework,is two level feature fusion technique,with the utilization of cosine-based ***,according to the results reported in existing literature,cosine similarity is considered as the best similarity measure among existing similarity *** proposed hybrid feature selection is validated on four benchmark datasets with variations in number of features and number of *** validated results confirm that the proposed hybrid feature selection framework performs better than the existing hybrid feature selection framework,existing feature selection algorithms in terms of accuracy,f-measure,recall,and *** reported in presented paper show that the proposed approach gives more than 90%accuracy on benchmark dataset that is better tha
The packet classification is a fundamental process in provisioning security and quality of service for many intelligent network-embedded systems running in the Internet of Things(IoT).In recent years,researchers have ...
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The packet classification is a fundamental process in provisioning security and quality of service for many intelligent network-embedded systems running in the Internet of Things(IoT).In recent years,researchers have tried to develop hardware-based solutions for the classification of Internet *** to higher throughput and shorter delays,these solutions are considered as a major key to improving the quality of *** of these efforts have attempted to implement a software algorithm on the FPGA to reduce the processing time and enhance the *** proposed architectures,however,cannot reach a compromise among power consumption,memory usage,and throughput *** view of this,the architecture proposed in this paper contains a pipelinebased micro-core that is used in network processors to classify *** this end,three architectures have been implemented using the proposed *** first architecture performs parallel classification based on header *** second one classifies packets in a serial *** last architecture is the pipeline-based classifier,which can increase performance by nine *** proposed architectures have been implemented on an FPGA *** results are indicative of a reduction in memory usage as well as an increase in speedup and *** architecture has a power consumption of is 1.294w,and its throughput with a frequency of 233 MHz exceeds 147 Gbps.
The structure andmechanismof thehuman visual system contain rich treasures,and surprising effects can be achieved by simulating the human visual *** this article,starting from the human visual system,we compare and di...
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The structure andmechanismof thehuman visual system contain rich treasures,and surprising effects can be achieved by simulating the human visual *** this article,starting from the human visual system,we compare and discuss the discrepancies between the human visual system and traditional machine vision *** the wide variety and large volume of visual information,the use of nonvon Neumann structured,flexible neuromorphic vision sensors can effectively compensate for the limitations of traditional machine vision systems based on the von Neumann ***,this article addresses the emulation of retinal functionality and provides an overview of the principles and circuit implementation methods of non-von Neumann computing ***,in terms of mimicking the retinal surface structure,this article introduces the fabrication approach for flexible sensor ***,this article analyzes the challenges currently faced by non-von Neumann flexible neuromorphic vision sensors and offers a perspective on their future development.
PV systems using horizontal single axis trackers (SATs) generate more energy than PV systems on fixed racking. The most common method of positioning a SAT minimizes the angle of incidence between the PV and the sun wh...
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Linear feature extraction at the presence of nonlinear dependencies among the data is a fundamental challenge in unsupervised learning. We propose using a Gram-Schmidt (GS) type orthogonalization process over function...
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This paper focuses on the maintenance deficiencies of disaster resilient infrastructure on behalf of engineers that contributed to the impacts of Hurricane Katrina, Fukushima, and the 2023 Hawaii Wildfires. These disa...
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Introduction: Rehabilitation for conditions affecting mobility, such as stroke, muscle atrophy, and others, poses significant challenges in traditional physiotherapy practices. Engaging patients in enjoyable exercises...
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In this paper, stochastic optimal control problems in continuous time and space are considered. In recent years, such problems have received renewed attention from the lens of reinforcement learning (RL) which is also...
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