In this study, two types of local plants were chosen, the first is the plant golden pothos Epipremnum aureum and the second is the Iraqi Sheikh's chin plant Tribulus terrestris L, for the purpose of making a comparison between them in terms of their possession of chemical groups with antioxidant activity in order to use them as a natural alternative to using antioxidants Industrial that cause negative effects on human health, the samples were prepared using the method of water and alcohol extraction (ethanol 70%) for both plants. It revealed the presence of a number of chemical groups (tannins, carbohydrates, phenols, flavonoids, alkaloids) for both plants, the aqueous and alcoholic extracts. Coumarins are only found in the sheikh's chin pl

This study was carried out to determine the effects of NaCl (0.00, 50, 100, 150, 180 or 200) mM and two different types of mutagens chemical mutagen ethyl methyl sulphonate (EMS) at 0.5% and physical mutagen UV-B irradiation (40 min time exposure), on mitotic division in two Iraqi rice genotypes Amber 33 (A33) and Amber Baghdad (AB). Different concentrations of NaCl were used. Mitotic index (MI %) was decreased significantly by increasing NaCl concentration, however the highest mitotic index was recorded in mutated genotypes with EMS and UV-B. Different abnormal chromosomes were noticed in mutated plants. Results showed high percentage of abnormal chromosomes in EMS mutated genotypes. In addition no significant differences between genotypes

Recognizing speech emotions is an important subject in pattern recognition. This work is about studying the effect of extracting the minimum possible number of features on the speech emotion recognition (SER) system. In this paper, three experiments performed to reach the best way that gives good accuracy. The first one extracting only three features: zero crossing rate (ZCR), mean, and standard deviation (SD) from emotional speech samples, the second one extracting only the first 12 Mel frequency cepstral coefficient (MFCC) features, and the last experiment applying feature fusion between the mentioned features. In all experiments, the features are classified using five types of classification techniques, which are the Random Forest (RF),

Over the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric for the identification and recognition of humans due to its consistent shape and rich texture variation. The ear presents an attractive solution since it is visible, ear images are easily captured, and the ear structure remains relatively stable over time.  In this paper, a comprehensive review of prior research was conducted to establish the efficacy of utilizing ear features for individual identification through the employment of both manually-crafted features and deep-learning approaches. The objective of this model is to present the accuracy rate of person identification systems based on either manually-crafted features such as D

This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

Silver nanoparticles synthesized by different species