Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles and others relative geometric features for recognition give accuracy about 95.73% when the seven emotion classes are tested and 97.23% when the 6 classes (except normal class) are only tested. These rates are considered high when compared with the results of other newly published works.
This paper aims to study the second-order geometric nonlinearity effects of P-Delta on the dynamic response of tall reinforced concrete buildings due to a wide range of earthquake ground motion forces, including minor earthquake up to moderate and strong earthquakes. The frequency domain dynamic analysis procedure was used for response assessment. Reinforced concrete building models with different heights up to 50 stories were analyzed. The finite element software ETABS (version 16.0.3) was used to analyze reinforced concrete building models.
The study reveals that the percentage increase in buildings' sway and drift due to P-Delta effects are nearly constant for specific building height irrespective of the seism
... Show MoreThe Ceramic was a part from the humanitarian production that masseure the development and promotion of the Nations through decades. The Ceramic development involve wide and more techniques. One of these techniques that appear through the developmental centuries, the ( Alkaro Ceramic )technique, this technique depended the simplicity that comitted on religions thoughts through their development and its origin, so it had connected with these religions thoughts and had transmitted to the differnt Nations and they development in it to stay as a connection to the original key although its a way to keep them from adoption a new path. The tracker of the Ceramic fine art through its modernal level could knew and touched the Enormons transformati
... Show MoreThe primary objective of root canal therapy is adequate biomechanical preparation of root canal system followed by 3D obturation.in clinics we are encountered with several anatomical variations, which we need to manage efficiently. One of the major factors responsible for failure of root canal therapy is missed canals. Recent technological advances have given the clinician opportunity to identify anatomical variations and treat them to satisfaction.
Monthly water samples from three stations in Diwanya river at Diwanyia city were collected during December 1999 to June 2000. Variables from each stations were determined including ; temperature, pH ,dissolved oxygen, dissolved carbon dioxide , alkalinity ,total hardness, calcium ,magnesium , phosphate, nitrite, nitrate, chlorophyll-a , and total number of phytoplankton .The river considered as fresh water , alkaline ,very hard .The parameters recorded at different values from up and down stream.
The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi
... Show MoreThe most significant function in oil exploration is determining the reservoir facies, which are based mostly on the primary features of rocks. Porosity, water saturation, and shale volume as well as sonic log and Bulk density are the types of input data utilized in Interactive Petrophysics software to compute rock facies. These data are used to create 15 clusters and four groups of rock facies. Furthermore, the accurate matching between core and well-log data is established by the neural network technique. In the current study, to evaluate the applicability of the cluster analysis approach, the result of rock facies from 29 wells derived from cluster analysis were utilized to redistribute the petrophysical properties for six units of Mishri
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