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کاربرد نوع شرط:
- جایگاه : پژوهشی
- مجله: International Journal of Nano Dimension
- نوع مقاله: Journal Article
- کلمات کلیدی: electrochemical impedance spectroscopy,Magnetic property,Combustion synthesis,Nano-structure characterization,X-ray powder diffraction
- چکیده:
- چکیده انگلیسی: Pure (S1) and Dy3+-doped α-Fe2O3 (S2 and S3) nanoparticles were prepared by a combustion synthesis method at 700 ºC for 8 h using Fe(acac)3 (Tris(acetylacetonato)Iron(III)) as raw material. Characterizations of the prepared powders were carried out by powder X-ray diffraction (PXRD). Structural analysis was performed by the FullProf program employing profile matching with constant scale factors. Scanning electron microscopy (SEM), transmission electron microscopy (TEM), electrochemical impedance spectroscopy (EIS), elemental maps analysis and energy-dispersive X-ray spectroscopy (EDS) were also performed to determine the dopant amount in the α-Fe2O3 crystal structure (S3). The results showed that the patterns had a main hexagonal structure with space group R . The cell parameters data, calculated by rietveld analysis, showed that the cell parameters were decreased with increasing the dopant (Dy3+) amount in the α-Fe2O3 crystal structure. The average particles sizes estimated from TEM images for S3 were about 60 nm. Besides, the magnetic properties of S1 and S3 were measured by vibrating sample magnetometer (VSM). It was found that with the addition of Dy3+ ions into the Fe2O3 system, the coercivity was decreased and the remanent magnetization was abruptly increased. The influence of dysprosium addition was also studied using electrochemical impedance spectroscopy. This study showed that in the presence of dysprosium ion, the charge transfer resistant increased in the electrochemical process.
- انتشار مقاله: 05-06-1396
- نویسندگان: Mahbobeh Jafari,Mahdi Salehi,Mahdi Behzad
- مشاهده
- جایگاه : پژوهشی
- مجله: International Journal of Finance and Managerial Accounting
- نوع مقاله: Journal Article
- کلمات کلیدی: CEO Overconfidence,Naive Bayesian Classification Algorithm,Probit Regression
- چکیده:
- چکیده انگلیسی: Corporate directors are influenced by overconfidence, which is one of the personality traits of individuals; it may take irrational decisions that will have a significant impact on the company's performance in the long run. The purpose of this paper is to validate and compare the Naive Bayesian Classification algorithm and probit regression in the prediction of Management's overconfident at present and in the future. Financial during the years are 2012 to 2017. To support the theoretical results, the samples were the companies admitted to the Tehran Stock Exchange, (financial data of 1292 companies/year in total). Data collection in the theoretical part of the study benefitted from the library method, and for calculating data, Excel software was used, and in order to test the research hypotheses Matlab 2017 and Eviews10.0 were used. The empirical findings demonstrate that, Gained nonlinear prediction model of the Naive Bayes Classification algorithm, has high ability to predict, and the Probit regression model, has limited ability to predict the over-confidence of management. Finally, the artificial intelligence prediction model (naive Bayesian classification algorithm) has better result compared with statistical binary regression prediction model (probit regression).
- انتشار مقاله: 23-10-1397
- نویسندگان: Shokoufeh Etebar,Roya Darabi,Mohsen Hamidian,Seiyedeh Mahbobeh Jafari
- مشاهده