Automating MySQL Database Complexity Estimation Based on Quantitative Metrics

2021 ◽  
pp. 378-386
Author(s):  
Igor Kotsyuba ◽  
Pavel Bezkorovaynyi ◽  
Julia Silko ◽  
Alexey Shikov
Keyword(s):  
Quantitative Metrics ◽  
Complexity Estimation

scholarly journals Canada as a Case Study for Balanced Presentation to Address Controversy on Emission Reduction Policies

2021 ◽  
Vol 13 (14) ◽  
pp. 7909
Author(s):  
Robert V. Parsons
Keyword(s):  
Emission Reduction ◽  
Environmental Issues ◽  
Trade Show ◽  
Quantitative Metrics ◽  
Carbon Taxation ◽  
Canadian Provinces ◽  
Method Analysis ◽  
A Current

Controversy is common on environmental issues, with carbon taxation in Canada a current example. This paper uses Canada as a case study for analysis based around balanced presentation, a technique developed some time ago, yet largely forgotten. Using the method, analysis is shifted away from the point of controversy to a broader quantitative question, with comparative data employed from official government sources. Simple quantitative analysis is applied to evaluate emission trends of individual Canadian provinces, with quantitative metrics to identify and confirm the application of relevant emission reduction policies by individual jurisdictions. From 2005 through 2019, three provinces show consistent downward emission trends, two show consistent upward trends, and the remaining five have no trends, showing relatively “flat” profiles. The results clarify, in terms of diverse emission reduction policies, where successes have occurred, and where deficiencies or ambiguities have existed. Neither carbon taxation nor related cap-and-trade show any association with long-term reductions in overall emissions. One policy does stand out as being associated with long-term reductions, namely grid decarbonization. The results suggest a possible need within Canada to rethink emission reduction policies. The method may be relevant as a model for other countries to consider as well.

Intersectional Invisibility: Race, Gender, Sexuality, and the Erasure of Sexual Minority Women in US Asylum Law

2021 ◽  
pp. 1-30
Author(s):  
Roxana Akbari ◽  
Stefan Vogler
Keyword(s):  
Sexual Minority ◽  
Minority Women ◽  
Social Difference ◽  
Regulatory Structure ◽  
Sexual Minority Women ◽  
Empirical Examination ◽  
Sexual Minority Men ◽  
Asylum Law ◽  
Quantitative Metrics ◽  
Minority Men

Advocates have long observed that sexual minority women are treated less favorably than sexual minority men under US asylum law. However, there has been little empirical examination of these claims in a US context. We offer the first systematic comparative empirical analysis of 199 asylum decisions for cisgender sexual minorities. Using quantitative metrics to contextualize in-depth qualitative analysis, we show that even when cisgender sexual minority men and women face very similar types of violence, women’s claims are adjudicated differently. This is particularly stark in courts’ treatment of sexual violence but is also evident in determinations of generalized persecution and individuals’ sexualities. When women attempt to use laws that are structured around straight, white, Western male perspectives and experiences, their pathways are limited and sometimes nonexistent. Although the flexibility in this area of asylum law has allowed many types of new claims, these changes have mostly benefited those assigned male at birth, and this surface malleability has ultimately worked to maintain law as a regulatory structure. Even with seemingly progressive changes in asylum law, the law itself continues to uphold race, gender, and sexuality as durable social structures and does little to ameliorate inequalities along these axes of social difference.

scholarly journals Frequency-domain loss function for deep exposure correction of dark images

2021 ◽  
Author(s):  
Ojasvi Yadav ◽  
Koustav Ghosal ◽  
Sebastian Lutz ◽  
Aljosa Smolic
Keyword(s):  
Loss Function ◽  
Correct Choice ◽  
Frequency Space ◽  
Multi Scale ◽  
Quantitative Metrics ◽  
Image Translation ◽  
Domain Loss ◽  
In The Wild ◽  
End To End ◽  
Classical Image

AbstractWe address the problem of exposure correction of dark, blurry and noisy images captured in low-light conditions in the wild. Classical image-denoising filters work well in the frequency space but are constrained by several factors such as the correct choice of thresholds and frequency estimates. On the other hand, traditional deep networks are trained end to end in the RGB space by formulating this task as an image translation problem. However, that is done without any explicit constraints on the inherent noise of the dark images and thus produces noisy and blurry outputs. To this end, we propose a DCT/FFT-based multi-scale loss function, which when combined with traditional losses, trains a network to translate the important features for visually pleasing output. Our loss function is end to end differentiable, scale-agnostic and generic; i.e., it can be applied to both RAW and JPEG images in most existing frameworks without additional overhead. Using this loss function, we report significant improvements over the state of the art using quantitative metrics and subjective tests.

scholarly journals Evaluating Metrics Applied to the Medical Science Liaison (MSL) Role: A Survey-Based Study of Canadian MSL Leaders

2021 ◽  
Author(s):  
Munaza Saleem ◽  
Lisa Cesario ◽  
Lisa Wilcox ◽  
Marsha Haynes ◽  
Simon Collin ◽  
...  
Keyword(s):  
Health Care ◽  
Health Care Professional ◽  
Online Survey ◽  
Medical Science ◽  
Specialty Care ◽  
Product Lifecycle ◽  
The Past ◽  
Data Analyses ◽  
Quantitative Metrics ◽  
Frequency Of Use

Abstract Introduction Metrics utilized within the Medical Science Liaison (MSL) role are plentiful and traditionally quantitative. We sought to understand the current use and value of metrics applied to the MSL role, including the use of qualitative metrics. Methods We developed a list of 70 MSL leaders working in Canada, spanning 29 companies. Invitations were emailed Jun 16, 2020 and the 25-question online survey was open for 3 weeks. Questions were designed to assess demographics as well as how and why metrics are applied to the MSL role. Data analyses were descriptive. Results Responses were received from 44 leaders (63%). Of the 42 eligible, 45% had ≤ 2 years of experience as MSL leaders and 86% supported specialty care products over many phases of the product lifecycle. A majority (69%) agreed or strongly agreed that metrics are critical to understanding whether an MSL is delivering value, and 98% had used metrics in the past year. The most common reason to use metrics was ‘to show value/impact of MSLs to leadership’ (66%). The most frequently used metric was ‘number of health-care professional (HCP) interactions’, despite this being seen as having moderate value. Quantitative metrics were used more often than qualitative, although qualitative were more often highly valued. Conclusion The data collected show a lack of agreement between the frequency of use for some metrics and their value in demonstrating the contribution of an MSL. Overall, MSL leaders in our study felt qualitative metrics were a better means of showing the true impact of MSLs.

Relevant Biophysical Parameters Discrimination along Corticospinal Tract in Patients with Stroke Using Convolutional Neural Networks

2021 ◽  
Vol 51 ◽  
pp. 95-103
Author(s):  
Abderrazek Zeraii ◽  
Amine Ben Slama ◽  
Lazhar Rmili ◽  
Cyrine Drissi ◽  
Mokhtar Mars ◽  
...  
Keyword(s):  
Motor Neurons ◽  
Corticospinal Tract ◽  
Diffusion Tensor ◽  
Biophysical Parameters ◽  
Spinal Motor Neurons ◽  
Fiber Tracts ◽  
Subacute Stroke ◽  
Quantitative Metrics ◽  
White Matter Fiber Tracts

Stroke remains the leading source of long-term disability. As the only direct descending motor pathway, the corticospinal tract (CST) is the primary pathway to innervate spinal motor neurons and one of the most well studied tracts in human neuroanatomy. Its clinical significance can be demonstrated in many distinguished traumatic situations and diseases such as stroke. Along‐tract statistics analysis enables the extraction of quantitative diffusion metrics along specific white matter fiber tracts. Besides quantitative metrics derived from classical diffusion tensor imaging (DTI), such as fractional anisotropy and diffusivities. In this study, we extracted DTI derived quantitative microstructural diffusion metrics along the CST tract in patients with moderate to severe subacute stroke. Respectively DTI metric of individual patient's fiber tract was then plotted. This approach may be useful for future studies that may compare in two different time (acute and chronic). The contribution of this work presents a totally computerized method of DTI image recognition based on conventional neural network (CNN) in order to supply quantitative appraisal of clinical characteristics. The obtained results have achieved an important classification (Accuracy=94.12%) when applying the CNN. The proposed methodology enables us to assess the classification of the used DTI images database within a reduced processing time. Experimental results prove the success of the proposed rating system for a suitable analysis of microstructural diffusion when compared to previous work.

Computed tomography image denoising based on multi dose CT image fusion and extended sparse techniques

2021 ◽  
Author(s):  
Anuyogam Venkataraman
Keyword(s):  
Computed Tomography ◽  
Image Fusion ◽  
Region Of Interest ◽  
Source Image ◽  
High Dose ◽  
Fusion Algorithm ◽  
Quantitative Metrics ◽  
Fused Image ◽  
Fusion Methods ◽  
Computed Tomography Image

With the increasing utilization of X-ray Computed Tomography (CT) in medical diagnosis, obtaining higher quality image with lower exposure to radiation is a highly challenging task in image processing. Sparse representation based image fusion is one of the sought after fusion techniques among the current researchers. A novel image fusion algorithm based on focused vector detection is proposed in this thesis. Firstly, the initial fused vector is acquired by combining common and innovative sparse components of multi-dosage ensemble using Joint Sparse PCA fusion method utilizing an overcomplete dictionary trained using high dose images of the same region of interest from different patients. And then, the strongly focused vector is obtained by determining the pixels of low dose and medium dose vectors which have high similarity with the pixels of the initial fused vector using certain quantitative metrics. Final fused image is obtained by denoising and simultaneously integrating the strongly focused vector, initial fused vector and source image vectors in joint sparse domain thereby preserving the edges and other critical information needed for diagnosis. This thesis demonstrates the effectiveness of the proposed algorithms when experimented on different images and the qualitative and quantitative results are compared with some of the widely used image fusion methods.

Overlooked current estimation biases arising from the Lagrangian Argo trajectory derivation method

2021 ◽  
Author(s):  
Tianyu Wang ◽  
Yan Du ◽  
Minyang Wang
Keyword(s):  
Ocean Model ◽  
Ocean Dynamics ◽  
Western Boundary ◽  
Boundary Current ◽  
Current Estimation ◽  
Quantitative Metrics ◽  
Circumpolar Current ◽  
Derivation Method ◽  
Jet Interactions ◽  
Reference Layer

AbstractAn Argo simulation system is used to provide synthetic Lagrangian trajectories based on the Estimating the Circulation and Climate of the Ocean model, Phase II (ECCO2). In combination with ambient Eulerian velocity at the reference layer (1000 m) from the model, quantitative metrics of the Lagrangian trajectory-derived velocities are computed. The result indicates that the biases induced by the derivation algorithm are strongly linked with ocean dynamics. In low latitudes, Ekman currents and vertically sheared geostrophic currents influence both the magnitude and the direction of the derivation velocity vectors. The maximal shear-induced biases exist near the equator with the amplitudes reaching up to about 1.2 cm s-1. The angles of the shear biases are pronounced in the low latitude oceans, ranging from -8° to 8°. Specifically, the study shows an overlooked bias from the float drifting motions that mainly occurs in the western boundary current and Antarctic circumpolar current (ACC) regions. In these regions, a recently reported horizontal acceleration measured via Lagrangian floats is significantly associated with the strong eddy-jet interactions. The acceleration could induce an overestimation of Eulerian current velocity magnitudes. For the common Argo floats with a 9-day float parking period, the derivation speed biases induced by velocity acceleration would be as large as 3 cm s-1, approximately 12% of the ambient velocity. It might have implications to map the mean mid-depth ocean currents from Argo trajectories, as well as understand the dynamics of eddy-jet interactions in the ocean.

ANALYSIS OF PARSING AND WEBSCRAPING TOOLS WITHIN THE FRAMEWORK DEVELOPMENT OF ARBITRATION INVESTMENT STRATEGY ON THE MARKET SPORT BETS

2021 ◽  
Vol 1 (2) ◽  
pp. 65-77
Author(s):  
T. E. Vildanov ◽  
◽  
N. S. Ivanov ◽  
Keyword(s):  
Data Extraction ◽  
Investment Strategy ◽  
Semistructured Data ◽  
Graphical Form ◽  
Great Demand ◽  
Rapid Extraction ◽  
Web Scraping ◽  
Quantitative Metrics ◽  
Framework Development ◽  
Number Of Iterations

This article explores both popular and newly invented tools for extracting data from sites and converting them into a form suitable for analysis. The paper compares the Python libraries, the key criterion of the compared tools is their performance. The results will be grouped by sites, tools used and number of iterations, and then presented in graphical form. The scientific novelty of the research lies in the field of application of data extraction tools: we will receive and transform semistructured data from the websites of bookmakers and betting exchanges. The article also describes new tools that are currently not in great demand in the field of parsing and web scraping. As a result of the study, quantitative metrics were obtained for all the tools used and the libraries that were most suitable for the rapid extraction and processing of information in large quantities were selected.

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