{"title":"The Effect of Laser Shots on Morphological and Optical Properties of Copper Oxide NPs Prepared by Nd-Yag Laser of 1064 nm Wavelengths in Distilled Water","authors":"M. M Kareem","doi":"10.24271/psr.33","DOIUrl":"https://doi.org/10.24271/psr.33","url":null,"abstract":"This study examines the synthesis of copper oxide nanoparticles (NPs) by using a Q-Switched Nd-Yag (1064 nm) laser on copper foil immersed in Distilled Water (DW). The solution color changed to light green refers to the production of copper oxide NPs. The generated nanoparticles were studied to determine their characteristics as a function of pulse laser shots and the NPs were obtained by taking 500 and 1000 laser pulse shots on Cu target. Thin films deposited on both (glass and silicon) substrates were characterized by X-Ray Diffraction (XRD), Field Emission-Scanning Electron Microscopy (FE-SEM), and Atomic Force Microscopy (AFM) techniques. Later, regarding the colloidal nanoparticles, NPs were instantly characterized by UV-vis spectroscopy and examined by TEM microscopy. The production rate of Cu-NPs concentration in the colloidal solution was measured by atomic absorption spectra type (ICP-OES), which increased by increasing the number of laser shots in the liquid volume. The Energy Dispersion Spectroscopy (EDS) analysis resulted in the presence of copper (Cu) and oxygen (O) elements in the film structure with a nearly stoichiometry ratio. The optical energy gap was decreased to (2.44 eV) with increasing the number of laser shots in the colloidal solution.","PeriodicalId":33835,"journal":{"name":"Passer Journal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68882303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Comparison Study of Data Mining Algorithms for blood Cancer Prediction","authors":"Noor Bahjat, Snwr Jamak","doi":"10.24271/psr.29","DOIUrl":"https://doi.org/10.24271/psr.29","url":null,"abstract":"Cancer is a common disease that threats the life of one of every three people. This dangerous disease urgently requires early detection and diagnosis. The recent progress in data mining methods, such as classification, has proven the need for machine learning algorithms to apply to large datasets. This paper mainly aims to utilise data mining techniques to classify cancer data sets into blood cancer and non-blood cancer based on pre-defined information and post-defined information obtained after blood tests and CT scan tests. This research conducted using the WEKA data mining tool with 10-fold cross-validation to evaluate and compare different classification algorithms, extract meaningful information from the dataset and accurately identify the most suitable and predictive model. This paper depicted that the most suitable classifier with the best ability to predict the cancerous dataset is Multilayer perceptron with an accuracy of 99.3967%.","PeriodicalId":33835,"journal":{"name":"Passer Journal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68882223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}