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

Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear  classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.

In this paper we have been focus for the comparison between three forms for classification data belongs

Crime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or livin

ABSTRACT The role of specific amino acids namely cysteine, methionine, threonine and asparagine in the protection provided by vamin solution against B-lactam inhibition to E. coli was evaluated in vitro. In minimal medium, Cells were treated with 32 ug/ml of penicillin G, carbencillin, hostacillin, cloxacillin and cephalotin in the presence of specific amino acid supplementations. Deletion of specific amino acids from the media abolished the protection provided by vamin. Threonine was essential for the protection of cells against all tested antibiotics, while cysteine was essential for protection against carbencillin and cephalotin Deletion of methionine or asparagine abolished the protec- tion against carbencillin and to a less extent ce

The role of specific amino acids namely cysteine, methionine, threonine and asparagine in the protection provided by vamin solution against B-lactam inhibition to E. coli was evaluated in vitro In minimal medium, cells were treated with 32 ug/ml of penicillin G, carbenciLlin, hostacillin, cloxacillin and cephalotin in the presence of specific amino acid supplementation. Deletion of specific amino acids from the media abolished the protection provided by vamin. Threonine was essential for the protection of cells against all tested antibiotics, while cysteine was essential for protection against carbencillin and sephalotin. Deletion of methionine or asparagine abolished the protection against carbencillin and to a less extent cephalotin.

tA novel synthesis procedure is presented for preparing triethanolamine-treated graphene nanoplatelets(TEA-GNPs) with different specific areas (SSAs). Using ultrasonication, the covalently functionalizedTEA-GNPs with different weight concentrations and SSAs were dispersed in distilled water to prepareTEA-GNPs nanofluids. A simple direct coupling of GNPs with TEA molecules is implemented to synthesizestable water-based nanofluids. The effectiveness of the functionalization procedure was validated by thecharacterization and morphology tests, i.e., FTIR, Raman spectroscopy, EDS, and TEM. Thermal conduc-tivity, dispersion stability, and rheological properties were investigated. Using UV–vis spectrometer, ahighest dispersion stability of 0.876

We report herein an innovative approach to prostate tumor therapy using tumor specific radioactive gold nanoparticles (198Au) functionalized with Mangiferin (MGF). Production and full characterization of MGF-198AuNPs are described. In vivo therapeutic efficacy of MGF-198AuNPs, through intratumoral delivery, in SCID mice bearing prostate tumor xenografts are described. Singular doses of the nano-radiopharmaceutical (MGF-198AuNPs) resulted in over 85% reduction of tumor volume as compared to untreated control groups. The excellent anti-tumor efficacy of MGF-198AuNPs are attributed to the retention of over 90% of the injected dose within tumors for long periods of time. The retention of MGF-198AuNPs is also rationalized in terms of the higher

The aim of this study is to compare the effects of three methods: problem-based learning (PBL), PBL with lecture method, and conventional teaching on self-directed learning skills among physics undergraduates. The actual sample size comprises of 122 students, who were selected randomly from the Physics Department, College of Education in Iraq. In this study, the pre- and post-test were done and the instruments were administered to the students for data collection. The data was analyzed and statistical results rejected null hypothesis of this study. This study revealed that there are no signifigant differences between PBL and PBL with lecture method, thus the PBL without or with lecture method enhances the self-directed learning skills bette

Abstract

The study aims to examine the relationships between cognitive absorption and E-Learning readiness in the preparatory stage. The study sample consisted of (190) students who were chosen randomly. The Researcher has developed the cognitive absorption and E-Learning readiness scales. A correlational descriptive approach was adopted. The research revealed that there is a positive statistical relationship between cognitive absorption and eLearning readiness.