scholarly journals On Analysis of Topological Properties for Terbium IV Oxide via Enthalpy and Entropy Measurements

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Muhammad Kamran Siddiqui ◽  
Sana Javed ◽  
Lubna Sherin ◽  
Sadia Khalid ◽  
Muhammad Mathar Bashir ◽  
...  
Keyword(s):  
High Dielectric Constant ◽  
Mean Squared Error ◽  
Topological Indices ◽  
Point Of View ◽  
Discrete Mathematics ◽  
Gas Detectors ◽  
Squared Error ◽  
Enthalpy And Entropy ◽  
High Dielectric ◽  
Modern Technologies

A relation between topological indices and thermodynamics properties of terbium IV oxide has been established by using a rational method as it was found the most efficient method based on mean squared error (MSE). Terbium IV oxide has huge application as an insulator in modern technologies such as microelectronics, gas detectors, and luminiferous owing to mechanical and thermal stability, high dielectric constant, radiation resistance, and variable electrical conductivity. The chemical graph and topological indices have attracted the research community due to their potential application in discrete mathematics, biology, and chemistry. Our commitment is to investigate topological indices and thermodynamic properties of terbium IV oxide that depend on an innovative data utilitarian. Moreover, a relationship between topological indices and curve fitting has been established as an application point of view. All curve fittings have been found using MATLAB software.

ENHANCEMENT OF MAMMOGRAPHIC PHANTOM FEATURES BY NOISE REDUCTION

2007 ◽  
Vol 21 (06) ◽  
pp. 1047-1057
Author(s):  
MOULOUD ADEL ◽  
DANIEL ZUWALA ◽  
MONIQUE RASIGNI ◽  
SALAH BOURENNANE
Keyword(s):  
Noise Reduction ◽  
Mean Squared Error ◽  
Point Of View ◽  
Reduction Scheme ◽  
Squared Error ◽  
Modification Method ◽  
Optimal Function ◽  
Direct Contrast ◽  
The Mean ◽  
Simulated Images

A noise reduction scheme on digitized mammographic phantom images is presented. This algorithm is based on a direct contrast modification method with an optimal function, obtained by using the mean squared error as a criterion. Computer simulated images containing objects similar to those observed in the phantom are built to evaluate the performance of the algorithm. Noise reduction results obtained on both simulated and real phantom images show that the developed method may be considered as a good preprocessing step from the point of view of automating phantom film evaluation by means of image processing.

Ion–solvent interaction of tetraalkylammonium ions in solvents of high dielectric constant. Part I. Conductance and Walden product of tetraalkylammonium ions in N-methylacetamide at different temperatures

1968 ◽  
Vol 46 (22) ◽  
pp. 3525-3530 ◽  
Author(s):  
Raj Deo Singh ◽  
Pushti Prakash Rastogi ◽  
Ram Gopal
Keyword(s):  
Dielectric Constant ◽  
Aqueous Solutions ◽  
High Dielectric Constant ◽  
Electrical Conductance ◽  
Point Of View ◽  
Walden Product ◽  
Solvent Interaction ◽  
Tetraalkylammonium Ions ◽  
Different Temperatures ◽  
High Dielectric

Ion–solvent interaction of the tetraalkylammonium ions (R4N+) in N-methylacetamide has been studied from the point of view of electrical conductance and the derived Walden product. The results indicate R4N+ ions to be structure breakers in this solvent, quite opposite to their general behavior in aqueous solutions. The effect is conspicuous in the smaller Me4N+ and Et4N+ ions, but is less marked in the larger ions.

MOS, Perfect Prog, and Reanalysis

2006 ◽  
Vol 134 (2) ◽  
pp. 657-663 ◽  
Author(s):  
Caren Marzban ◽  
Scott Sandgathe ◽  
Eugenia Kalnay
Keyword(s):  
Mean Squared Error ◽  
Weather Prediction ◽  
Error Variance ◽  
Numerical Weather Prediction Model ◽  
Reanalysis Data ◽  
Point Of View ◽  
Model Output ◽  
Squared Error ◽  
Error Bias ◽  
Model Output Statistics

Abstract Statistical postprocessing methods have been successful in correcting many defects inherent in numerical weather prediction model forecasts. Among them, model output statistics (MOS) and perfect prog have been most common, each with its own strengths and weaknesses. Here, an alternative method (called RAN) is examined that combines the two, while at the same time utilizes the information in reanalysis data. The three methods are examined from a purely formal/mathematical point of view. The results suggest that whereas MOS is expected to outperform perfect prog and RAN in terms of mean squared error, bias, and error variance, the RAN approach is expected to yield more certain and bias-free forecasts. It is suggested therefore that a real-time RAN-based postprocessor be developed for further testing.

Enhanced performance of supercapacitors by constructing a “mini parallel-plate capacitor” in an electrode with high dielectric constant materials

2020 ◽  
Vol 8 (32) ◽  
pp. 16661-16668
Author(s):  
Huayao Tu ◽  
Shouzhi Wang ◽  
Hehe Jiang ◽  
Zhenyan Liang ◽  
Dong Shi ◽  
...  
Keyword(s):  
Dielectric Constant ◽  
Carbon Fiber ◽  
Parallel Plate ◽  
Sandwich Structure ◽  
High Dielectric Constant ◽  
Parallel Plate Capacitor ◽  
Plate Capacitor ◽  
Fiber Metal ◽  
High Dielectric ◽  
Mini Plate

The carbon fiber/metal oxide/metal oxynitride layer sandwich structure is constructed in the electrode to form a mini-plate capacitor. High dielectric constant metal oxides act as dielectric to increase their capacitance.

Use of reflectance spectroscopy to estimate the organic carbon and CaCO3 contents of soils

2012 ◽  
Vol 61 (2) ◽  
pp. 277-290 ◽  
Author(s):  
Ádám Csorba ◽  
Vince Láng ◽  
László Fenyvesi ◽  
Erika Michéli
Keyword(s):  
Organic Carbon ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Mean Squared Error ◽  
Reflectance Spectroscopy ◽  
Least Squares Regression ◽  
Root Mean Squared Error ◽  
Squared Error

Napjainkban egyre nagyobb igény mutatkozik olyan technológiák és módszerek kidolgozására és alkalmazására, melyek lehetővé teszik a gyors, költséghatékony és környezetbarát talajadat-felvételezést és kiértékelést. Ezeknek az igényeknek felel meg a reflektancia spektroszkópia, mely az elektromágneses spektrum látható (VIS) és közeli infravörös (NIR) tartományában (350–2500 nm) végzett reflektancia-mérésekre épül. Figyelembe véve, hogy a talajokról felvett reflektancia spektrum információban nagyon gazdag, és a vizsgált tartományban számos talajalkotó rendelkezik karakterisztikus spektrális „ujjlenyomattal”, egyetlen görbéből lehetővé válik nagyszámú, kulcsfontosságú talajparaméter egyidejű meghatározása. Dolgozatunkban, a reflektancia spektroszkópia alapjaira helyezett, a talajok ösz-szetételének meghatározását célzó módszertani fejlesztés első lépéseit mutatjuk be. Munkánk során talajok szervesszén- és CaCO3-tartalmának megbecslését lehetővé tévő többváltozós matematikai-statisztikai módszerekre (részleges legkisebb négyzetek módszere, partial least squares regression – PLSR) épülő prediktív modellek létrehozását és tesztelését végeztük el. A létrehozott modellek tesztelése során megállapítottuk, hogy az eljárás mindkét talajparaméter esetében magas R2értéket [R2(szerves szén) = 0,815; R2(CaCO3) = 0,907] adott. A becslés pontosságát jelző közepes négyzetes eltérés (root mean squared error – RMSE) érték mindkét paraméter esetében közepesnek mondható [RMSE (szerves szén) = 0,467; RMSE (CaCO3) = 3,508], mely a reflektancia mérési előírások standardizálásával jelentősen javítható. Vizsgálataink alapján arra a következtetésre jutottunk, hogy a reflektancia spektroszkópia és a többváltozós kemometriai eljárások együttes alkalmazásával, gyors és költséghatékony adatfelvételezési és -értékelési módszerhez juthatunk.

Using Approximation Non-Bayesian Computation with Fuzzy Data to Estimation Inverse Weibull Parameters and Reliability Function

2018 ◽  
pp. 397
Author(s):  
Nadia Hashim Al-Noor ◽  
Shurooq A.K. Al-Sultany
Keyword(s):  
Maximum Likelihood ◽  
Expectation Maximization ◽  
Mean Squared Error ◽  
Maximum Likelihood Estimators ◽  
Reliability Function ◽  
Fuzzy Data ◽  
Monte Carlo Simulation Study ◽  
Weibull Parameters ◽  
Squared Error ◽  
Newton Raphson

        In real situations all observations and measurements are not exact numbers but more or less non-exact, also called fuzzy. So, in this paper, we use approximate non-Bayesian computational methods to estimate inverse Weibull parameters and reliability function with fuzzy data. The maximum likelihood and moment estimations are obtained as non-Bayesian estimation. The maximum likelihood estimators have been derived numerically based on two iterative techniques namely “Newton-Raphson” and the “Expectation-Maximization” techniques. In addition, we provide compared numerically through Monte-Carlo simulation study to obtained estimates of the parameters and reliability function in terms of their mean squared error values and integrated mean squared error values respectively.

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