Classification of apoptosis proteins by discriminant analysis

Kandemır-Cavas, Cagin; Nasıbov, Efendi

doi:10.5505/tjb.2012.44153

Cited by 6 publications

(2 citation statements)

References 33 publications

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“…The main aim of the DA method was to predict group membership based on a linear combination of the interval variables. (Li et al, 2006;Kandemir-Cavas & Nasibov, 2012). The samples can be divided into several groups by computing the Mahalanobis distance between a sample and the mean value of a set of standards (spectra in this study) according to formula (1) (Yu et al, 2007).…”

Section: Discriminant Analysismentioning

confidence: 99%

Classification and recognition of genetically modified organisms by chemometrics methods using terahertz spectroscopy

Chen

Yin

et al. 2015

Int J of Food Sci Tech

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Summary The aim of this study was to evaluate the potential of terahertz (THz) spectroscopy to discriminate genetically modified (GM) and non‐GM organisms. In this study, eighty‐four sugar beet samples (thirty‐six GM sugar beets and forty‐eight of their parents, non‐GM ones) were investigated using terahertz time‐domain spectroscopy (THz‐TDS) system between 0.2 and 1.2 THz. Discriminant analysis (DA) based on principal component analysis (PCA) was used to discriminate sugar beet samples into two classes: GM organisms (GMOs) and non‐GMOs. Study results indicate that the DA method leads to an excellent classification. A total of 95.8% of the non‐GM samples were accurately classified, and no GM samples were misclassified, as there was 100% correctness. Results of this study demonstrate that THz spectroscopy combined with chemometrics techniques can provide a fast, nondestructive and reliable method to differentiate GMOs and non‐GMOs, which avoids time‐consuming, laborious and expensive sensory and chemical analyses.

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Section: Discriminant Analysismentioning

confidence: 99%

Classification and recognition of genetically modified organisms by chemometrics methods using terahertz spectroscopy

Chen

Yin

et al. 2015

Int J of Food Sci Tech

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“…Queues are formed when the demand for a service exceeds its supply [1]. Queuing up for services is a common phenomenon; we queue up for services in the restaurants, banks, schools, supermarkets, filling stations, hospitals, etc.…”

Section: Introductionmentioning

confidence: 99%

Optimality Test for Multi-Sever Queuing Model with Homogenous Server in the Out-Patient Department (OPD) of Nigeria Teaching Hospitals

Ikwunne¹,

Onyesolu²

2016

IJMECS

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Abstract-Queuing by patients in the out-patients department to access hospital services in Nigeria teaching hospitals is a teething concern to most healthcare providers. This causes inconvenience to patients and economic costs to the hospitals. Patients waiting for minutes, hours, days or months to receive medical services could result in waiting costs to them. Providing too much service could result in excessive costs. Also not providing adequate services could result in excessive waiting and costs. This study sought to determine an optimal server level and at a minimum total cost which include waiting and service costs in homogenous servers in order to reduce patients' congestions in the hospital as low as reasonably practicable. The queuing characteristics in all the twenty-three (23) teaching hospitals in Nigeria were analysed using a Multi-server Queuing Model and the waiting and service costs determined with a view to ascertaining the optimal service level. The data for this study were collected through observations and interviews. The data was analysed using Quantitative Methods, Production and Operations Management (POM QM) and Queuing Theory Calculator Software as well as using descriptive analysis. The results of the analysis demonstrated that average queue length, waiting time of patients as well as over utilization of specialist doctors at the teaching hospitals could be reduced at an optimal server level and at a minimum total cost as against their present server level with high total cost which include waiting and service costs. Therefore, this call for refocusing so as to improve the overall patient care in our cultural context and meet the patient needs in our environment.

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Detection of Genetically Modified Sugarcane by Using Terahertz Spectroscopy and Chemometrics

et al. 2018

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Classification of apoptosis proteins by discriminant analysis

Cited by 6 publications

References 33 publications

Classification and recognition of genetically modified organisms by chemometrics methods using terahertz spectroscopy

Classification and recognition of genetically modified organisms by chemometrics methods using terahertz spectroscopy

Optimality Test for Multi-Sever Queuing Model with Homogenous Server in the Out-Patient Department (OPD) of Nigeria Teaching Hospitals

Detection of Genetically Modified Sugarcane by Using Terahertz Spectroscopy and Chemometrics

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