rTSR: When Do Relative Performance Metrics Capture Relative Performance?

2019 ◽  
Author(s):  
Paul Ma ◽  
Jee-Eun Shin ◽  
Charles C. Y. Wang
Keyword(s):  
Performance Metrics ◽  
Relative Performance

scholarly journals Dual Feed, Single Element Antenna for WiMAX MIMO Application

2008 ◽  
Vol 2008 ◽  
pp. 1-5 ◽  
Author(s):  
Frank M. Caimi ◽  
Mark Mongomery
Keyword(s):  
Correlation Coefficient ◽  
Performance Metrics ◽  
Measured Data ◽  
Antenna Pattern ◽  
Relative Performance ◽  
Equal Length ◽  
Impedance Match ◽  
Single Element ◽  
Pattern Correlation ◽  
Operating Bandwidth

A novel u-shaped single element antenna having two feed ports is compared with two equal length monopoles separated by a distance equivalent to the width. A discussion of relative performance metrics is provided for MIMO applications, and measured data is given for comparison. Good impedance match and isolation of greater than  dB are observed over the operating bandwidth from 2.3 to 2.39 GHz. The antenna patterns are highly uncorrelated, as illustrated by computation of the antenna pattern correlation coefficient for the two comparison monopoles.

scholarly journals Benchmarking Transposable Element Annotation Methods for Creation of a Streamlined, Comprehensive Pipeline

2019 ◽  
Author(s):  
Shujun Ou ◽  
Weija Su ◽  
Yi Liao ◽  
Kapeel Chougule ◽  
Doreen Ware ◽  
...  
Keyword(s):  
Transposable Elements ◽  
Transposable Element ◽  
Open Source ◽  
Performance Metrics ◽  
De Novo ◽  
Relative Performance ◽  
Sequencing Technology ◽  
High Quality ◽  
Link Type ◽  
Assembly Algorithms

AbstractSequencing technology and assembly algorithms have matured to the point that high-quality de novo assembly is possible for large, repetitive genomes. Current assemblies traverse transposable elements (TEs) and allow for annotation of TEs. There are numerous methods for each class of elements with unknown relative performance metrics. We benchmarked existing programs based on a curated library of rice TEs. Using the most robust programs, we created a comprehensive pipeline called Extensive de-novo TE Annotator (EDTA) that produces a condensed TE library for annotations of structurally intact and fragmented elements. EDTA is open-source and freely available: https://github.com/oushujun/EDTA.

Relative performance of religious and ethical investment funds

2020 ◽  
Vol 11 (6) ◽  
pp. 1227-1244 ◽  
Author(s):  
Esther Castro ◽  
M. Kabir Hassan ◽  
Jose Francisco Rubio ◽  
Zairihan Abdul Halim
Keyword(s):  
Mutual Funds ◽  
Performance Metrics ◽  
Relative Performance ◽  
Data Envelopment ◽  
Ethical Investment ◽  
Socially Responsible ◽  
Investment Funds ◽  
Content Type ◽  
Asset Pricing Models ◽  
The Cost

Purpose This paper updates the literature regarding the performance of constrained US mutual funds by looking at the relative performance of Christian mutual funds, socially responsible funds and Islamic funds. This paper aims to rank the performance of religious and ethical investment funds. Design/methodology/approach This study uses monthly returns from 2005 to 2015 to perform traditional asset pricing models as well as data envelopment analysis to determine rank. Findings Islamic mutual funds outperform socially responsible funds, which then outperform Christian-based mutual funds; these results are also consistent during the latest 2007-2008 crisis period. The results are robust to different performance metrics and benchmarks. Moreover, this paper reports a significant amount of money “left on the table” by investing in constraint funds and disregarding the sin industry which shows an ethical dilemma for investors. Practical implications Investors who seek to invest morally/ethically can be informed of the cost of doing so. They can also compare portfolio with others that have similar holdings and constraints. Originality/value This paper not only includes Christian mutual funds in the research but also provides the performance of all constrained assets. It also compares religious funds with “SIN” industry, and thus quantifies the cost of “doing right.”

Framework for rare event detection using Artificial Neural Network based context free grammar

2020 ◽  
Vol 39 (6) ◽  
pp. 8463-8475
Author(s):  
Palanivel Srinivasan ◽  
Manivannan Doraipandian
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Event Detection ◽  
Performance Metrics ◽  
Rare Events ◽  
Rare Event ◽  
Video Stream ◽  
Context Free Grammar ◽  
Artificial Neural ◽  
Context Free

Rare event detections are performed using spatial domain and frequency domain-based procedures. Omnipresent surveillance camera footages are increasing exponentially due course the time. Monitoring all the events manually is an insignificant and more time-consuming process. Therefore, an automated rare event detection contrivance is required to make this process manageable. In this work, a Context-Free Grammar (CFG) is developed for detecting rare events from a video stream and Artificial Neural Network (ANN) is used to train CFG. A set of dedicated algorithms are used to perform frame split process, edge detection, background subtraction and convert the processed data into CFG. The developed CFG is converted into nodes and edges to form a graph. The graph is given to the input layer of an ANN to classify normal and rare event classes. Graph derived from CFG using input video stream is used to train ANN Further the performance of developed Artificial Neural Network Based Context-Free Grammar – Rare Event Detection (ACFG-RED) is compared with other existing techniques and performance metrics such as accuracy, precision, sensitivity, recall, average processing time and average processing power are used for performance estimation and analyzed. Better performance metrics values have been observed for the ANN-CFG model compared with other techniques. The developed model will provide a better solution in detecting rare events using video streams.

Education and the Relation to the Outside: A Little Real Reality

2015 ◽  
Vol 9 (3) ◽  
pp. 273-300 ◽  
Author(s):  
David Savat ◽  
Greg Thompson
Keyword(s):  
Performance Metrics ◽  
Online Courses ◽  
Massive Open Online Courses ◽  
Educational Institutions ◽  
Special Issue ◽  
Massive Open Online ◽  
Transformative Teaching ◽  
Control Society ◽  
Brave New World ◽  
Radical Transformation

One of the more dominant themes around the use of Deleuze and Guattari's work, including in this special issue, is a focus on the radical transformation that educational institutions are undergoing, and which applies to administrator, student and educator alike. This is a transformation that finds its expression through teaching analytics, transformative teaching, massive open online courses (MOOCs) and updateable performance metrics alike. These techniques and practices, as an expression of control society, constitute the new sorts of machines that frame and inhabit our educational institutions. As Deleuze and Guattari's work posits, on some level these are precisely the machines that many people in their day-to-day work as educators, students and administrators assemble and maintain, that is, desire. The meta-model of schizoanalysis is ideally placed to analyse this profound shift that is occurring in society, felt closely in the so-called knowledge sector where a brave new world of continuous education and motivation is instituting itself.

Classification of methods for generating pseudo-CT from MRI images for MRI-alone RT

2017 ◽  
Vol 1 (3) ◽  
pp. 54
Author(s):  
BOUKELLOUZ Wafa ◽  
MOUSSAOUI Abdelouahab
Keyword(s):  
Performance Metrics ◽  
Radiation Treatment ◽  
Hybrid Methods ◽  
Dose Calculation ◽  
Absolute Error ◽  
Ct Images ◽  
General Technique ◽  
Therapy Field ◽  
The Brain

Background: Since the last decades, research have been oriented towards an MRI-alone radiation treatment planning (RTP), where MRI is used as the primary modality for imaging, delineation and dose calculation by assigning to it the needed electron density (ED) information. The idea is to create a computed tomography (CT) image or so-called pseudo-CT from MRI data. In this paper, we review and classify methods for creating pseudo-CT images from MRI data. Each class of methods is explained and a group of works in the literature is presented in detail with statistical performance. We discuss the advantages, drawbacks and limitations of each class of methods. Methods: We classified most recent works in deriving a pseudo-CT from MR images into four classes: segmentation-based, intensity-based, atlas-based and hybrid methods. We based the classification on the general technique applied in the approach. Results: Most of research focused on the brain and the pelvis regions. The mean absolute error (MAE) ranged from 80 HU to 137 HU and from 36.4 HU to 74 HU for the brain and pelvis, respectively. In addition, an interest in the Dixon MR sequence is increasing since it has the advantage of producing multiple contrast images with a single acquisition. Conclusion: Radiation therapy field is emerging towards the generalization of MRI-only RT thanks to the advances in techniques for generation of pseudo-CT images. However, a benchmark is needed to set in common performance metrics to assess the quality of the generated pseudo-CT and judge on the efficiency of a certain method.

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