Labeling of Paley Digraphs

Parameswari, R.; Rajeswari, R.

doi:10.12732/iejpam.v7i3.3

Cited by 2 publications

(2 citation statements)

References 4 publications

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“…It is very tough to predict those specifications during the early stages of the project, where the scope of every module has yet to be marked, and when we still have no conclusive evidence for the ultimate functional requirements of the product [2]. Most frequently, insufficient knowledge of the affecting factors and the possible risks that can happen, or the work deadline fears, and conventional effort estimation methods [3], which are widely accepted by the opinions of various software domain experts, may sometimes lead to erroneous estimates . Because of these, the software product may not be delivered in time with the expected non-functional requirements.…”

Section: Introductionmentioning

confidence: 99%

Software Effort Estimation through Ensembling of Base Models in Machine Learning using a Voting Estimator

Kumar¹,

Bilgaiyan²,

Mishra³

2023

IJACSA

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For a long time, researchers have been working to predict the effort of software development with the help of various machine learning algorithms. These algorithms are known for better understanding the underlying facts inside the data and improving the prediction rate than conventional approaches such as line of code and functional point approaches. According to no free lunch theory, there is no single algorithm which gives better predictions on all the datasets. To remove this bias our work aims to provide a better model for software effort estimation and thereby reduce the distance between the actual and predicted effort for future projects. The authors proposed an ensembling of regressor models using voting estimator for better predictions to reduce the error rate to over the biasness provide by single machine learning algorithm. The results obtained show that the ensemble models were better than those from the single models used on different datasets.

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Section: Introductionmentioning

confidence: 99%

Software Effort Estimation through Ensembling of Base Models in Machine Learning using a Voting Estimator

Kumar¹,

Bilgaiyan²,

Mishra³

2023

IJACSA

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“…Agricultural and industrial waste by products, naturally available seaweeds and especially microbial biomass are regarded as effective materials for biosorption of heavy metals 3 . Microbial biomass has been extensively studied for the evacuation of heavy metals from the environment 4 . Conventional methods used for the removal of toxic heavy metals such as chemical precipitation, lime coagulation, ion exchange, reverse osmosis and solvent extraction are very expensive requiring large input of energy and chemicals and led to the production of toxic by-products.…”

Section: Introductionmentioning

confidence: 99%

Cr+6 REMOVAL BY INDIGENOUS BACTERIA IN CONJUNCTION WITH DIFFERENT BIOWASTE MATERIALS: AN ECOFRIENDLY APPROACH

Batool

Hasnain

2014

J. Chil. Chem. Soc.

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Two Cr+6 reducing bacterial strains previously isolated from tannery effluents were used in the present study and identified as Pseudomonas aeruginosa Rb-1 and Ochrobacterum intermedium (Rb-2) by 16S rRNA sequencing. Different biowaste materials (waste tea leaves, carrot juice pulp, dry leaves of eucalyptus and rice husk) were assessed for sorption / removal of Cr +6 from aqueous solution of K 2 Cr 2 O 4 . Feasibility of mono and mixed cultures of indigenous bacterial strains was evaluated for Cr +6 removal in conjunction with different biowaste materials. Among all tested biowastes materials, waste tea leaves showed optimum removal of Cr +6 from metal solution alone (77.1%) as well as in combination with bacterial strains (99.4%) after 720 minutes of contact time. Mixed culture of bacterial strains was found to be more efficient in Cr +6 removal than monoculture. The contact time of 720 minutes, pH 7, biomass concentration of 2.5 gram 100 mL -1 , 37˚C and shaking speed of 100 rpm were found to be most optimum for optimum Cr +6 sorption alone as well as in combination with bacterial strains. Fourier transform infrared spectroscopy revealed that carboxyl, amino and OH groups present on the waste tea leaves played a significant role in the binding of Cr +6 ions with the biomass. The present study is unique in this respect that this approach involve both living and non-living materials and we could not find any report documenting such findings up to our knowledge.

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Labeling of Paley Digraphs

Abstract: In this paper, we deal with the uniqueness problems on entire and meromorphic functions concerning differential polynomials that share fixed-points. These results improve and extend those given by Xiaojuan Li and C. Meng, see [2].

Cited by 2 publications

References 4 publications

Software Effort Estimation through Ensembling of Base Models in Machine Learning using a Voting Estimator

Software Effort Estimation through Ensembling of Base Models in Machine Learning using a Voting Estimator

Cr+6 REMOVAL BY INDIGENOUS BACTERIA IN CONJUNCTION WITH DIFFERENT BIOWASTE MATERIALS: AN ECOFRIENDLY APPROACH

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