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Shunt Active Power Filter based on P-Q Theory with Multilevel Inverters for Harmonic Current Compensation

A shunt active power filter based on P-Q theory combined with high pass filters (HPFs) for harmonic-current compensation was proposed in this paper and produces lower total harmonic distortion (THD) than the active power filters with DLHI.
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Average-reward model-free reinforcement learning: a systematic review and literature mapping

An updated review of work in model-free reinforcement learning is provided and it is extended to cover policy-iteration and function approximation methods (in addition to the value-iterated and tabular counterparts) to identify and discuss opportunities for future work.
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Tracking efficiency measurement of dynamic models on geometric particle filter using KLD-resampling

The efficiency of particle filter can be measure reliably enough using batch KLD-resampling, and dynamics models affect the efficiency of particles filter, but their performance depends mostly on the case by case situationally.
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Examining average and discounted reward optimality criteria in reinforcement learning

It is emphasized that average-reward RL methods possess the ingredient and mechanism for applying a family of discounting-free optimality criteria (Veinott, 1969) to RL.
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A Novel Knowledge-Compatibility Benchmarker for Semantic Segmentation

A knowledge-compatibility benchmarker, whose backbone is a regression machine, that takes as input a semantic annotation and the vision-based knowledge, then outputs an estimate of the corresponding averaged class-accuracy value, and introduces three types of feature vectors for regression.
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Automatic identification of acacia leaf diseases in plantation forests using wavelet energy and Shannon entropy

A method for automatic acacia leaf diseases identification through digital image processing using wavelet energy and Shannon entropy of sub-bands from the orthogonal discrete wavelet packet decomposition (DWPT), which indicates that the system is reliable to distinguish the leaf diseases.
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Structured support vector machine learning of conditional random fields

This research shows that a zero padding can resolve the missing values in the joint feature vector and proposed parameterized Conditional Random Fields model and learns the model by using Structured Support Vector Machine.
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A distributed, any-time robot architecture for robust manipulation

We present a robot system architecture for a mobile manipulator to perform grasping and manipulation tasks robustly. The system is distributed across multiple computers allowing for online update…

An integrated smart surveillance system for diseases monitoring in tropical plantation forests

This study proposes an integrated smart surveillance system for diseases monitoring in tropical plantation forests, called Dismon, an online and mobile application for monitoring and diseases identification in plantation forests by developing computer vision technology for disease identification through digital image processing.
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Utilizing Google Images for Training Classifiers in CRF-Based Semantic Segmentation

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