Historic city centers are cultural archives where built forms and spatial practices hold the collective memory of generations. In Baghdad, the concept of Cultural DNA (C-DNA) is a tool to understand how cultural codes are the generative rules that shape the evolution and persistence of the historic urban fabric. This research explores the role of C-DNA as a trigger of urban morphogenesis in Rusafa, the historic heart of Baghdad, by looking into how cultural values underpin spatial continuity, change, and adaptability. The study uses Space Syntax methodologies with DepthmapX, supported by historical maps, surveys, and field observations, to analyze two morphological stages of Rusafa: 1850 and now. Through axial analysis, the research

This contribution provides an atomistic understanding into the impact of W, Nb, and Mo co-substitution at Hf-site of cubic HfO2 lattice to produce Hf1−xTMxO2 system at x = 25%. The calculations have been performed under the framework of density functional theory supported by Habbured parameter (DFT+U). Structural analysis demonstrates that the recorded lattice constants is in good coherence with the previously published results. For the lattice parameters, contraction by 1.33% comparing with the host system has been reported. Furthermore, the doping effect of TM on the band gap leads to its reduction in the resulting Hf0.75TM0.25O2 configurations. The partial density of states (PDOS) indicate that hybridization through localized electroni

This contribution provides an atomistic understanding into the impact of W, Nb, and Mo co-substitution at Hf-site of cubic HfO2 lattice to produce Hf1−xTMxO2 system at x = 25%. The calculations have been performed under the framework of density functional theory supported by Habbured parameter (DFT+U). Structural analysis demonstrates that the recorded lattice constants is in good coherence with the previously published results. For the lattice parameters, contraction by 1.33% comparing with the host system has been reported. Furthermore, the doping effect of TM on the band gap leads to its reduction in the resulting Hf0.75TM0.25O2 configurations. The partial density of states (PDOS) indicate that hybridization through localized electroni

DBN Dr. Liqaa Habeb, International Journal of Multidisciplinary Reseach, 2015

Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f

The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm