Efficient resource allocation for decentralized heterogeneous system using density estimation approach

This paper focuses on enhancing the mission duration by deploying secondary agents to coordinate with the primary agents to accomplish the mission with a minimal interruption. The interruption considered here is due to limited fuel carrying capability of primary agents. In this study, primary and secondary agents refer to unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs), respectively. Conventionally, UAVs are refueled with the fixed main charging stations which lead to interruption during the ongoing mission. In this work, we propose two-stage density estimation approach for efficiently distributing the swarm of UGVs to act as mobile refueling stations for UAVs. In the first stage, the optimal number of UGVs and their initial placement are computed. In the final stage, the UGVs minimize the average distance for the nearest UAVs to refuel. The performance of the proposed method is compared with the state of the art. The numerical simulation shows a better performance with the distributed UGVs than the state of the art.

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Efficient Greedy Learning of Gaussian Mixture Models

Neural Computation ◽

10.1162/089976603762553004 ◽

2003 ◽

Vol 15 (2) ◽

pp. 469-485 ◽

Cited By ~ 205

Author(s):

J. J. Verbeek ◽

N. Vlassis ◽

B. Kröse

Keyword(s):

Mixture Models ◽

Density Estimation ◽

Expectation Maximization ◽

State Of The Art ◽

Gaussian Mixture Models ◽

Gaussian Mixture ◽

Optimal Number ◽

Gaussian Mixtures ◽

Data Points ◽

Time Linear

This article concerns the greedy learning of gaussian mixtures. In the greedy approach, mixture components are inserted into the mixture one aftertheother.We propose a heuristic for searching for the optimal component to insert. In a randomized manner, a set of candidate new components is generated. For each of these candidates, we find the locally optimal new component and insert it into the existing mixture. The resulting algorithm resolves the sensitivity to initialization of state-of-the-art methods, like expectation maximization, and has running time linear in the number of data points and quadratic in the (final) number of mixture components. Due to its greedy nature, the algorithm can be particularly useful when the optimal number of mixture components is unknown. Experimental results comparing the proposed algorithm to other methods on density estimation and texture segmentation are provided.

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Review on the State-of-the-art Operation and Planning of Electric Vehicle Charging Stations in Electricity Distribution Systems

10.1109/ecce47101.2021.9595954 ◽

2021 ◽

Author(s):

Mehrdad Aghamohamadi ◽

Amin Mahmoudi ◽

John K. Ward ◽

Mohammed H. Haque

Keyword(s):

Electric Vehicle ◽

Distribution Systems ◽

State Of The Art ◽

The State ◽

Electricity Distribution ◽

Electric Vehicle Charging ◽

Vehicle Charging ◽

Charging Stations

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Shape retrieval using angle-wise contour variance

Journal of Electrical Engineering ◽

10.2478/jee-2021-0013 ◽

2021 ◽

Vol 72 (2) ◽

pp. 99-105

Author(s):

Mustafa Eren Yildirim ◽

Omer Faruk Ince ◽

Yucel Batu Salman ◽

Ibrahim Furkan Ince

Keyword(s):

Standard Deviation ◽

State Of The Art ◽

Average Distance ◽

The State ◽

Shape Retrieval ◽

Geometric Feature ◽

Retrieval Rate ◽

Multiple Intersections

Abstract In this study, we propose a geometric feature set for 2D shape retrieval. Conventional Hough feature gives the edge locations along with angle and creates Hough table if there are multiple intersections at borders. In this paper, a statistical way to represent the relation of repeating contours at each angle around the shape centroid is presented. The main contribution of this paper is to use the standard deviation of repeating contours. We calculate the angle between the shape centroid and each point on the contour. For each integer angle value, three features were extracted: the number of contour repetitions, the average distance of the points at that angle to the centroid, and the standard deviation of the points at the same angle. Thus, a 2D image was represented by a constant sized matrix, regardless of its size. In the case of similarity between two images, instead of merging features within a single expression, the algorithm picked the feature with the highest similarity rate for that comparison. We tested the proposed method on MPEG-7, Kimia99, ETH-80 datasets for a benchmark with the state-of-the-art. It outperformed most of the recent methods in terms of retrieval rate.

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Unsupervised Phonocardiogram Analysis With Distribution Density Based Variational Auto-Encoders

Frontiers in Medicine ◽

10.3389/fmed.2021.655084 ◽

2021 ◽

Vol 8 ◽

Author(s):

Shengchen Li ◽

Ke Tian

Keyword(s):

Density Estimation ◽

System Performance ◽

Distribution Density ◽

State Of The Art ◽

Gaussian Model ◽

The State ◽

Single Domain ◽

Latent Space ◽

Multiple Domains ◽

Pcg Signals

This paper proposes an unsupervised way for Phonocardiogram (PCG) analysis, which uses a revised auto encoder based on distribution density estimation in the latent space. Auto encoders especially Variational Auto-Encoders (VAEs) and its variant β−VAE are considered as one of the state-of-the-art methodologies for PCG analysis. VAE based models for PCG analysis assume that normal PCG signals can be represented by latent vectors that obey a normal Gaussian Model, which may not be necessary true in PCG analysis. This paper proposes two methods DBVAE and DBAE that are based on estimating the density of latent vectors in latent space to improve the performance of VAE based PCG analysis systems. Examining the system performance with PCG data from the a single domain and multiple domains, the proposed systems outperform the VAE based methods. The representation of normal PCG signals in the latent space is also investigated by calculating the kurtosis and skewness where DBAE introduces normal PCG representation following Gaussian-like models but DBVAE does not introduce normal PCG representation following Gaussian-like models.

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Practical Picture Processing

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100051700 ◽

1974 ◽

Vol 32 ◽

pp. 338-339

Author(s):

T. A. Welton

Keyword(s):

Radiation Damage ◽

Coherence Length ◽

Spatial Information ◽

State Of The Art ◽

Coherent Radiation ◽

The State ◽

Energy Spread ◽

Electron Micrograph ◽

Picture Processing ◽

Molecular Skeleton

Various authors have emphasized the spatial information resident in an electron micrograph taken with adequately coherent radiation. In view of the completion of at least one such instrument, this opportunity is taken to summarize the state of the art of processing such micrographs. We use the usual symbols for the aberration coefficients, and supplement these with £ and 6 for the transverse coherence length and the fractional energy spread respectively. He also assume a weak, biologically interesting sample, with principal interest lying in the molecular skeleton remaining after obvious hydrogen loss and other radiation damage has occurred.

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