Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or

The UV−VIS absorption spectroscopy technique was used to study the formation of a new complex of charge transfer (CT) between bioactive organic molecules as (Nystatin) containing both a π-electrons from a conjugated system and lone-pair of electrons (amine) with Tetrachloro-1,4 benzoquinone (TCBQ) as a π-acceptor in which the transferred electron goes into its vacant anti-bonding molecular orbitals. The Tyrian purple-colored complex formed was quantitatively measured at 544 nm. This complex shows obeying Beer's law within the concentration range of (10-90) μg.ml-1The stoichiometry of the formed complex between the (Nys.) and (TCBQ) was found 1:2 as evaluated by continuous variation (Job's method) and mole ratio method The value of mola

The novel Vierordt’s approach, or simultaneous equation method, was created and validated for the concurrent determination of vincristine sulfate (VCS) and bovine serum albumin (BSA) in pure solutions utilizing UV spectrophotometry. It is simple, precise, economical, rapid, reliable, and accurate. This method depends on measuring absorbance at two wavelengths, 296 nm and 278 nm, which correspond to the λ_max of VCS and BSA in deionized water, respectively. The calibration curves of VCS and BSA are linear at concentration ranges of 10–60 μg/mL and 200–1600 μg/mL, with correlation coefficient values (R²) of 1 and 0.999, respectively. The limits of detection (LOD) and quantification (LO

Research summarized in applying the model  of fuzzy goal programming for aggregate production planning , in General Company for hydraulic industries / plastic factory to get an optimal production plan  trying to cope with the impact that fluctuations in demand and  employs all available resources using two strategies where they are available   inventories  strategy and  the strategy of  change in the level of the workforce, these   strategies  costs are usually imprecise/fuzzy. The plant administration trying to minimize total production costs, minimize carrying costs and minimize changes in labour levels. depending on the gained data from th

The present study considers to confirming the applicability of flow with double-sided square lid driven cavity flow by using the lattice Boltzmann equation with moment-based boundary conditions for no slip boundaries.  The boundary conditions are applied over the hydrodynamic moments of the lattice Boltzmann equations locally at each node. The investigation is carried out numerically for both single and multiple relaxation time models. To simulate two-sided lid driven-cavity flow, the top and bottom walls are moving with constant velocity while other walls are stationary. Various Reynolds numbers are used in a range of 100 and up to 5000. The present method shows the effect of the moving boundaries on the two symmetrical cavities t

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri