Pearson's and Spearman's Correlation

Weaver, Kathleen F.; Morales, Vanessa; Dunn, Sarah L.; Godde, Kanya; Weaver, Pablo F.

doi:10.1002/9781119454205.ch10

Cited by 11 publications

(5 citation statements)

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“…Fisher’s exact test [ 17 ] was used to analyze differences in antibody detection from households and animal shelters with known COVID-19 infection status, and antibody detection in dogs and cats. Spearman’s correlation [ 18 ] was used to analyze the relationship between human COVID-19 case numbers and the detection of antibodies in dogs and cats. All statistical analyses were performed using IBM SPSS Statistics (version 24, New York, NY, USA).…”

Section: Methodsmentioning

confidence: 99%

Evidence of Exposure to SARS-CoV-2 in Dogs and Cats from Households and Animal Shelters in Korea

Bae

Tark

Moon

et al. 2022

Animals

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The COVID-19 pandemic was caused by the zoonotic SARS-CoV-2. A variety of animals involved in human life worldwide have been investigated for infection. As the degree of infection increased, extensive monitoring in animals became necessary to determine the degree of infection in animals. The study was conducted on a sample of dogs and cats, which were randomly sampled according to the number of confirmed cases in the region. Animals from both COVID-19-confirmed households and generally disease-negative families and animal shelters were included. Tests included real-time qPCR tests for SARS-CoV-2 antigens, ELISA for antibodies, and plaque reduction neutralization tests (PRNT) for neutralizing antibodies. As a result, SARS-CoV-2 viral RNA was detected in 2 cats out of 1018 pets (672 dogs and 346 cats). A total of 16 dogs (2.38%) and 18 cats (5.20%) tested positive using ELISA, and 14 dogs (2.08%) and 17 cats (4.91%) tested positive using PRNT. Antigens of- and/or antibodies to SARS-CoV-2 were detected in the animals regardless of whether the companion family was infected; this was the case even in animal shelters, which have been regarded as relatively safe from transmission. In conclusion, continuous viral circulation between humans and animals is inevitable; therefore, continuous monitoring in animals is required.

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Section: Methodsmentioning

confidence: 99%

Evidence of Exposure to SARS-CoV-2 in Dogs and Cats from Households and Animal Shelters in Korea

Bae

Tark

Moon

et al. 2022

Animals

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“…To understand which features (sensor readings collected through BMC) have a high correlation with CPU utilization, we study the relationship between them using two correlation methods: Pearson correlation coefficient (α) and Spearman correlation coefficient (β) [48]. α evaluates the linear relationship between two variables, whereas β evaluates the monotonic relationship: α is linear when the change in one variable leads to a proportional change in another variable; β measures the change in a variable, but the relationship is not necessarily linear.…”

Section: F Feature Vector In ML Modelsmentioning

confidence: 99%

NASCENT: A Non-Invasive Solution for Detecting Utilization of Servers in Bare-Metal Cloud

et al. 2022

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Physical servers are available as-a-service in bare-metal public and private cloud platforms, and their demand has been proliferating because of the high levels of privacy and security guarantees they provide to the tenants. This raises the need for efficient management of bare-metal clouds to keep operational costs low such as by reducing energy consumption. For efficiently managing the cloud infrastructure, baremetal cloud operators need to monitor the utilization of servers. However, the privacy and security concerns prohibit the installation of third-party monitoring agents on the servers; thus, finding the server-utilization becomes a challenge. In this work, we present NASCENT, a scalable machine-learning (ML) based noninvasive solution for finding the utilization of servers without compromising the privacy and security of bare-metal cloud tenants. Our key idea is to infer utilization from various sensor readings accessible via a server's baseboard management controller (BMC) hardware. We evaluate the proposed solution with three regression based supervised ML algorithms in a Bare-metal-as-a-service (BMaaS) cloud. Our experimental evaluation shows that one of the ML algorithms employed in NASCENT infers the utilization with a rootmean-square error (RMSE) between 2.9 to 8.7 for different workloads. Also, the proposed solution uses minimal memory resources (19 KB) and can even run on BMC hardware which has very limited memory. We also propose a BMaaS cloud architecture that seamlessly integrates automated training and deployment of the ML algorithm in our solution into the life-cycle of bare-metal servers. NASCENT's codebase can be found at https://github.com/iithcandle/dhi-ojas

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“…We then calculate the Pearson Correlation matrix [66] for variables calculated in table II and the results are shown in Fig. 7.…”

Section: Correlationsmentioning

confidence: 99%

“…7. The colour coded correlation matrix also show the statistical significance in form of p-value [66] for different confidence interval i.e. 95%, 99% and 99.9%.…”

Section: Correlationsmentioning

confidence: 99%

Properties of hot finite nuclei and associated correlations with infinite nuclear matter

2022

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This work aim to study the various thermal characteristics of nuclei in view of the saturation and critical behavior of infinite nuclear matter. The free energy of a nucleus is parametrized using the density and temperature-dependent liquid-drop model and interaction among nucleons is worked out within the effective relativistic mean-field theory (E-RMF). The effective mass (m, * ) and critical temperature of infinite symmetric nuclear matter (Tc) of a given E-RMF parameter force play a seminal role in the estimation of thermal properties. A larger (m * ) and Tc of the E-RMF set estimate larger excitation energy, level density, and limiting temperature (T l ) for a given nucleus. The limiting temperature of a nucleus also depends on the behavior of the nuclear gas surrounding the nucleus, making the equation of state (EoS) at subsaturation densities an important input. A stiff EoS in the subsaturation region estimates a higher pressure of the nuclear gas making it less stable. Since the Tc plays an important part in these calculations, we perform a Pearson correlation statistical study of fifteen E-RMF parameter sets, satisfying the relevant constraint on EoS. Effective mass seems to govern the thermal characteristics of infinite as well as finite nuclear matter in the framework of E-RMF theory.

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Pearson's and Spearman's Correlation

Cited by 11 publications

References 0 publications

Evidence of Exposure to SARS-CoV-2 in Dogs and Cats from Households and Animal Shelters in Korea

Evidence of Exposure to SARS-CoV-2 in Dogs and Cats from Households and Animal Shelters in Korea

NASCENT: A Non-Invasive Solution for Detecting Utilization of Servers in Bare-Metal Cloud

Properties of hot finite nuclei and associated correlations with infinite nuclear matter

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