AYMAN ALMUTLAQ | KFUPM - Academia.edu (original) (raw)
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Al Imam Mohammad Ibn Saud Islamic University (IMSIU)
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Papers by AYMAN ALMUTLAQ
International Journal of Advanced Computer Science and Applications
The accuracy of effort estimation in one of the major factors in the success or failure of softwa... more The accuracy of effort estimation in one of the major factors in the success or failure of software projects. Analogy-Based Estimation (ABE) is a widely accepted estimation model since its flow human nature in selecting analogies similar in nature to the target project. The accuracy of prediction in ABE model in strongly associated with the quality of the dataset since it depends on previous completed projects for estimation. Missing Data (MD) is one of major challenges in software engineering datasets. Several missing data imputation techniques have been investigated by researchers in ABE model. Identification of the most similar donor values from the completed software projects dataset for imputation is a challenging issue in existing missing data techniques adopted for ABE model. In this study, Fuzzy C-Mean Imputation (FCMI), Mean Imputation (MI) and K-Nearest Neighbor Imputation (KNNI) are investigated to impute missing values in Desharnais dataset under different missing data percentages (Desh-Miss1, Desh-Miss2) for ABE model. FCMI-ABE technique is proposed in this study. Evaluation comparison among MI, KNNI, and (ABE-FCMI) is conducted for ABE model to identify the suitable MD imputation method. The results suggest that the use of (ABE-FCMI), rather than MI and KNNI, imputes more reliable values to incomplete software projects in the missing datasets. It was also found that the proposed imputation method significantly improves software development effort prediction of ABE model.
Advances in Materials Science and Engineering, 2015
The effect of grain size and stacking fault energy (SFE) on the strain hardening rate behavior un... more The effect of grain size and stacking fault energy (SFE) on the strain hardening rate behavior under plane strain compression (PSC) is investigated for pure Cu and binary Cu-Al alloys containing 1, 2, 4.7, and 7 wt. % Al. The alloys studied have a wide range of SFE from a low SFE of 4.5 mJm−2for Cu-7Al to a medium SFE of 78 mJm−2for pure Cu. A series of PSC tests have been conducted on these alloys for three average grain sizes of ~15, 70, and 250 μm. Strain hardening rate curves were obtained and a criterion relating twinning stress to grain size is established. It is concluded that the stress required for twinning initiation decreases with increasing grain size. Low values of SFE have an indirect influence on twinning stress by increasing the strain hardening rate which is reflected in building up the critical dislocation density needed to initiate mechanical twinning. A study on the effect of grain size on the intensity of the brass texture component for the low SFE alloys has re...
Materials Science and Engineering: A, 2011
Samples of Cu-Al and Cu-Zn alloys with different compositions were subjected to large strains und... more Samples of Cu-Al and Cu-Zn alloys with different compositions were subjected to large strains under plane strain compression (PSC), a process that simulates the rolling operation. Four compositions in the Cu-Al system, namely 1, 2, 4.7 and 7 wt.% Al and three compositions in the Cu-Zn system of 10, 20 and 30 wt.% Zn, were investigated. Adding Al or Zn to Cu effectively lowers the stacking fault energy (SFE) of the alloy and changes the deformation mechanism from dislocation slipping to dislocation slipping and deformation twinning. True stress-true strain responses in PSC were documented and the strain hardening rates were calculated and correlated to the evolved microstructure. The onset of twinning in low SFE alloys was not directly related to the low value of SFE, but rather to build up of a critical dislocation density during strain hardening in the early stage of deformation (ε < 0.1). The evolution of texture was documented for the Cu-Al samples using X-ray diffraction for samples plane strain compressed to true axial strains of 0.25, 0.5, 0.75 and 1.0. Orientation distribution function (ODF) plots were generated and quantitative information on the volume fraction of ideal rolling orientations were depicted and correlated with the stacking fault energy.
International Journal of Advanced Computer Science and Applications
The accuracy of effort estimation in one of the major factors in the success or failure of softwa... more The accuracy of effort estimation in one of the major factors in the success or failure of software projects. Analogy-Based Estimation (ABE) is a widely accepted estimation model since its flow human nature in selecting analogies similar in nature to the target project. The accuracy of prediction in ABE model in strongly associated with the quality of the dataset since it depends on previous completed projects for estimation. Missing Data (MD) is one of major challenges in software engineering datasets. Several missing data imputation techniques have been investigated by researchers in ABE model. Identification of the most similar donor values from the completed software projects dataset for imputation is a challenging issue in existing missing data techniques adopted for ABE model. In this study, Fuzzy C-Mean Imputation (FCMI), Mean Imputation (MI) and K-Nearest Neighbor Imputation (KNNI) are investigated to impute missing values in Desharnais dataset under different missing data percentages (Desh-Miss1, Desh-Miss2) for ABE model. FCMI-ABE technique is proposed in this study. Evaluation comparison among MI, KNNI, and (ABE-FCMI) is conducted for ABE model to identify the suitable MD imputation method. The results suggest that the use of (ABE-FCMI), rather than MI and KNNI, imputes more reliable values to incomplete software projects in the missing datasets. It was also found that the proposed imputation method significantly improves software development effort prediction of ABE model.
Advances in Materials Science and Engineering, 2015
The effect of grain size and stacking fault energy (SFE) on the strain hardening rate behavior un... more The effect of grain size and stacking fault energy (SFE) on the strain hardening rate behavior under plane strain compression (PSC) is investigated for pure Cu and binary Cu-Al alloys containing 1, 2, 4.7, and 7 wt. % Al. The alloys studied have a wide range of SFE from a low SFE of 4.5 mJm−2for Cu-7Al to a medium SFE of 78 mJm−2for pure Cu. A series of PSC tests have been conducted on these alloys for three average grain sizes of ~15, 70, and 250 μm. Strain hardening rate curves were obtained and a criterion relating twinning stress to grain size is established. It is concluded that the stress required for twinning initiation decreases with increasing grain size. Low values of SFE have an indirect influence on twinning stress by increasing the strain hardening rate which is reflected in building up the critical dislocation density needed to initiate mechanical twinning. A study on the effect of grain size on the intensity of the brass texture component for the low SFE alloys has re...
Materials Science and Engineering: A, 2011
Samples of Cu-Al and Cu-Zn alloys with different compositions were subjected to large strains und... more Samples of Cu-Al and Cu-Zn alloys with different compositions were subjected to large strains under plane strain compression (PSC), a process that simulates the rolling operation. Four compositions in the Cu-Al system, namely 1, 2, 4.7 and 7 wt.% Al and three compositions in the Cu-Zn system of 10, 20 and 30 wt.% Zn, were investigated. Adding Al or Zn to Cu effectively lowers the stacking fault energy (SFE) of the alloy and changes the deformation mechanism from dislocation slipping to dislocation slipping and deformation twinning. True stress-true strain responses in PSC were documented and the strain hardening rates were calculated and correlated to the evolved microstructure. The onset of twinning in low SFE alloys was not directly related to the low value of SFE, but rather to build up of a critical dislocation density during strain hardening in the early stage of deformation (ε < 0.1). The evolution of texture was documented for the Cu-Al samples using X-ray diffraction for samples plane strain compressed to true axial strains of 0.25, 0.5, 0.75 and 1.0. Orientation distribution function (ODF) plots were generated and quantitative information on the volume fraction of ideal rolling orientations were depicted and correlated with the stacking fault energy.