Research Area

Research Area Filter

Search Result For 'mathematics' , Result Number : 42

Staff Name
Research Area
Amr Mohamed Samy Mohammed Mahdi
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
applied mathematics
Amr Mohamed Samy Mohammed Mahdi
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
computational mathematics
Ali Ahmed Ali Masoud
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
engineering mathematics رياضيات هندسية
Rasha Ibrahiem Saleh Mohamed
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
engineering mathematics
Khaled Lotfy Mohamed Azab
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Applied Mathematics
Sameh Abdalazahr Hussein Mouawad
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Applied Mathematics
Hatem Elsayed Abdelwahied Semary
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Financial Mathematics
Hatem Elsayed Abdelwahied Semary
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Mathematics
Mohamed Elsayed Ahmed Mead
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Financial Mathematics
Mohamed Elsayed Ahmed Mead
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Mathematics
Mohamed Adel Tawfik Elshahat
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
mathematics
Ahmed Abdelhaliem Ahmmd
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
A.A. Halim, S.P. Kshevetskii and S.B. Leble, Numerical integration of a couped Kortweg-de Varies system, Computer and Mathematics with applications 45 (2003) 581-591
Ibtesam Ezzeldin Mohamed Abdelfattah
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
A program based on Successful Intelligence Theory to Develop Pedagogical Knowledge of Mathematics Content and Reflective Practices among Student Teachers at the College of Education.
Ibtesam Ezzeldin Mohamed Abdelfattah
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
The effectiveness of a program based on enjoyable learning in teaching mathematics to develop mathematical reasoning and some habits of mind among preparatory stage students
Ibtesam Ezzeldin Mohamed Abdelfattah
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
The Effectiveness of a Program based on Scamper in teaching Mathematics to Develop Lateral Thinking and Decision-making Skills for Preparatory Stage Students.
Ibtesam Ezzeldin Mohamed Abdelfattah
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
The Effectiveness of a proposed strategy based on the Six Thinking Hats in Teaching Mathematics to Develop the Mathematical Proficiency of Primary School Students.
Ibtesam Ezzeldin Mohamed Abdelfattah
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
The Effectiveness of a teaching program based on the principles of brain-based learning theory for developing future thinking skills and academic ambition in the Mathematics course for sixth grade primary students in Sharkia Governorate
Ibtesam Ezzeldin Mohamed Abdelfattah
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
The effectiveness of combining the two strategies of scientific stations and gardens of ideas in developing productive thinking and a love of mathematics among preparatory school students.
Ibtesam Ezzeldin Mohamed Abdelfattah
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
The Effectiveness of using Mind Mapping Strategy to teach Mathematics in Developing Branching Thinking Skills among Primary School Students.
Asmaa Mohamed Hassan Abdelmgied
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Abstract Science and Mathematics Teachers in language and International schools- Current reality and proposed Visualization
Enas yousry kamel abouelsouied
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Engineering Mathematics
Hamied Soliman Eraky Rizk
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Engneering Mathematics
Khalied Mohamed Hosny
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Applied Mathematics
Rania Bahgat Mohamed Amer
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Mathematics Engineering
Salwa Amien Mohamed ebrhiem
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Applied Mathematics
Samah Mohamed Mabrouk
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
engineering mathematics
Mohamed Ahmed Hanafy Mahmoud Elshaer
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Engineering Mathematics
Medhat Mostafa Mostafa Helal
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Engineering Mathematics
Medhat Mostafa Mostafa Helal
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Phs. and Eng. Mathematics
Fatma Desouky Mohamed Abdallah
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Applied Mathematics 2019, 9(1): 1-5 DOI: 10.5923/j.am.20190901.01 Role of Time Series Analysis in Forecasting Egg Production Depending on ARIMA Model Fatma D. M. Abdallah Department of Animal Wealth Development, Faculty of Veterinary Medicine, Zagazig University, Egypt Abstract The goal of this study is to show the role of time series models in predicting process and to demonstrate the suitable type of it according to the data under study. Autoregressive integrated moving averages (ARIMA) model is used as a common and a more applicable model. Univariate ARIMA model is used here to forecast egg production in some layers depending on daily data from the period of May to October 2018. Different criteria of the ARIMA model can be used to choose the suitable one such as the coefficient of determination (R2), mean absolute error (MAE), root mean square error (RMSE) and mean absolute relative percentage error (MARPE). Depending on these measures the autoregressive integrated moving average model with ordering (2,2,1) is considered the best model for forecasting process. The model fit statistics such as RMSE (331.520) which was low and the lowest BIC value (11.745) indicating that the model fit the data well. The high value of R2 (0.95) and MAPE (4.542) indicated a perfect forecasting model. Also, ARIMA model with ordering (1,2,2) is good in prediction process.
Fatma Desouky Mohamed Abdallah
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Statistical Modelling of Categorical Outcome with More than Two Nominal Categories Fatma D.M. Abdallah* Department of Animal Wealth Development, Faculty of Veterinary Medicine, Zagazig University, Egypt *Corresponding author: Nour_stat2013@yahoo.com Received August 13, 2018; Revised October 04, 2018; Accepted December 04, 2018 Abstract This paper aims to explain and apply an important statistical method used for modelling categorical outcome variable with at least two unordered categories. Logistic regression model especially multinomial logistic type (MNL) model is the best choice to model unordered qualitative data. A simulation study was done to examine the efficiency of the model in representing categorical response variable. Three explanatory variables (age, species, and sex) are used for discrimination. While the outcome variable was Rose Bengal Plate Test (RBPT) results which has four outcome categories (negative, positive, false positive, and false negative). Therefore, logit model will be utilized to model this data. MNL models were fitted using SPSS packages and parameters estimated depending on maximum likelihood (MLE) by the Newton-Raphson algorithm. This model depends mainly on two estimates to interpret the results, they are the regression coefficient and the exponentiated coefficients which known as the odds ratio. This model was a good fitted for description the data of 500 values of Rose Bengal Plate Test results of Brucella in sheep and goat species. The results showed fitting of the model to the data with highly significant likelihood ratio statistic for the overall model (P value = 0.000**). Wald test was significant for all variables in positive category and this indicated that age, species and sex are good predictors for test results. The odds ratio in case of positive category for age, species and sex was 1.589, 0.214 and 0.133 respectively. Keywords: multinomial logistic regression, odds ratio, Rose Bengal Plate Test (RBPT), maximum likelihood and pseudo R2 Cite This Article: Fatma D.M. Abdallah, “Statistical Modelling of Categorical Outcome with More than Two Nominal Categories.” American Journal of Applied Mathematics and Statistics, vol. 6, no. 6 (2018): 262-265. doi: 10.12691/ajams-6-6-7.
Fatma Desouky Mohamed Abdallah
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Using Discriminant Analysis and Artificial Neural Network Models for Classification and Prediction of Fertility Status of Friesian Cattle Eman A. Abo Elfadl1,*, Fatma D. M. Abdallah2 1Department of Animal Husbandry and Development of Animal Wealth, Faculty of Veterinary Medicine, Mansoura University, Egypt 2Department of Animal Wealth Development, Faculty of Veterinary Medicine, Zagazig University, Egypt *Corresponding author: emmy_f1984@yahoo.com Abstract Background & objectives: This study was undertaken to compare the accuracies of Discriminant analysis model (DA) and Artificial neural networks model (ANN) for classification and prediction of Friesian cattle fertility status by using its reproductive traits. Methods: Data was collected through field survey of 2843 animal records of Friesian breed belongs to El Dakhalia province farms, Egypt. Data was covering the period extended from 2010 to 2013. The samples of dairy production sectors were selected randomly. Data was collected from valid farm records or the structured questionnaires established by the researcher. Results: The results of classification accuracy indicated that the artificial neural network (ANN) model is more efficient than the discriminant analysis (DA) model in expressing overall classification accuracy and accuracies of correctly classified cases of fertility status for Friesian cattle. The results showed that The ANN models had shown the highest classification accuracy (93.6%) for year (2010) while, it was (79.9%) for DA. The comparison of overall classification accuracies clearly favored the supremacy of ANN over DA. The results also were confirmed by the areas under Receiver Operating Characteristic Curves (ROC) captured by ANN and DA. ROC curves are used mainly for comparing different discriminating rates. Areas under ROC curves were higher in case of ANN models across the different years compared to DA models. The differences in accuracies were also significant at 5% level of significance with p-value 0.005 by using Paired Sample t-test. From all of the above we can conclude that artificial neural network model was more accurate in prediction and classification of fertility status than a traditional statistical model (Discriminant analysis). Keywords: artificial neural networks, discriminant analysis, prediction, classification, ROC curve and fertility status Cite This Article: Eman A. Abo Elfadl, and Fatma D. M. Abdallah, “Using Discriminant Analysis and Artificial Neural Network Models for Classification and Prediction of Fertility Status of Friesian Cattle.” American Journal of Applied Mathematics and Statistics, vol. 5, no. 3 (2017): 90-94. doi: 10.12691/ajams-5-3-1.
Usama Abdelhamid Ibrahim
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
21. A. Kandil, O. Tantawy and M. Abdelhakeem, Flou Topological Spaces via Ideals, International Journal of Applied Mathematics, 23(5), 873-885, 2010.
Hassan Mostafa Metwally
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Mathematics
Sami Hassan Ahmed Hassn
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Applied Mathematics
Mahmoud Elsayed Mustafa Gabr
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Applied Mathematics
Halle Mahmoud Ahmed Khaleel
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Pure Mathematics
Nazira Mohamed Mansour Mosa
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
applied mathematics
Ahmed Nagah Saeed Majid
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
applied mathematics
Ahmed Nagah Saeed Majid
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Bio-mathematics
Ahmed Nagah Saeed Majid
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
mathematics
Ibtesam Elsayed Mostafa Attia Eraky
- Faculty Research Area On Zu Site
- Faculty Research Area On Staff Site
Applied Mathematics