Face Emotion Recognition Based on Machine Learning: A Review

Computers can now detect, understand, and evaluate emotions thanks to recent developments in machine learning and information fusion. Researchers across various sectors are increasingly intrigued by emotion identification, utilizing facial expressions, words, body language, and posture as means of discerning an individual's emotions. Nevertheless, the effectiveness of the first three methods may be limited, as individuals can consciously or unconsciously suppress their true feelings. This article explores various feature extraction techniques, encompassing the development of machine learning classifiers like k-nearest neighbour, naive Bayesian, support vector machine, and random forest, in accordance with the established standard for emotion recognition. The paper has three primary objectives: firstly, to offer a comprehensive overview of effective computing by outlining essential theoretical concepts; secondly, to describe in detail the state-of-the-art in emotion recognition at the moment; and thirdly, to highlight important findings and conclusions from the literature, with an emphasis on important obstacles and possible future paths, especially in the creation of state-of-the-art machine learning algorithms for the identification of emotions

Evaluation of Classification Algorithms for Intrusion Detection System: A Review

Intrusion detection is one of the most critical network security problems in the technology world. Machine learning techniques are being implemented to improve the Intrusion Detection System (IDS). In order to enhance the performance of IDS, different classification algorithms are applied to detect various types of attacks. Choosing a suitable classification algorithm for building IDS is not an easy task. The best method is to test the performance of the different classification algorithms. This paper aims to present the result of evaluating different classification algorithms to build an IDS model in terms of confusion matrix, accuracy, recall, precision, f-score, specificity and sensitivity. Nevertheless, most researchers have focused on the confusion matrix and accuracy metric as measurements of classification performance. It also provides a detailed comparison with the dataset, data preprocessing, number of features selected, feature selection technique, classification algorithms, and evaluation performance of algorithms described in the intrusion detection system

A Review of Principal Component Analysis Algorithm for Dimensionality Reduction

Big databases are increasingly widespread and are therefore hard to understand, in exploratory biomedicine science, big data in health research is highly exciting because data-based analyses can travel quicker than hypothesis-based research. Principal Component Analysis (PCA) is a method to reduce the dimensionality of certain datasets. Improves interpretability but without losing much information. It achieves this by creating new covariates that are not related to each other. Finding those new variables, or what we call the main components, will reduce the eigenvalue /eigenvectors solution problem. (PCA) can be said to be an adaptive data analysis technology because technology variables are developed to adapt to different data types and structures. This review will start by introducing the basic ideas of (PCA), describe some concepts related to (PCA), and discussing. What it can do, and reviewed fifteen articles of (PCA) that have been introduced and published in the last three years

Multi-Agent Based Security Framework for E-Government in Recently technology Developed Countries

E-Government is an environment where government produces services to citizens electronically, this is beside services to other e-Governments, and one crucial factor regarding the reliability of accepting services provided by e-Government is the security factor. This work is targeting Countries in their developing process that need to develop configurable management model, that capable of adapting security technologies to other factors revealed from the society.  The configuration of this management model will be autonomously built up through the association of three domains presented by this proposal: policies, measures and infrastructure. Along this work; ontology will be built up to accommodate these domains and eventually to grant Agent software the ability to perceive the environment and configure the management model for deploying security technologies. Keywords: Socio-Techno, Java Agent, Security policy, eGovernment, JADE, Ontology, knowledge development

Image steganography using least significant bit and secret map techniques

In steganography, secret data are invisible in cover media, such as text, audio, video and image. Hence, attackers have no knowledge of the original message contained in the media or which algorithm is used to embed or extract such message. Image steganography is a branch of steganography in which secret data are hidden in host images. In this study, image steganography using least significant bit and secret map techniques is performed by applying 3D chaotic maps, namely, 3D Chebyshev and 3D logistic maps, to obtain high security. This technique is based on the concept of performing random insertion and selecting a pixel from a host image. The proposed algorithm is comprehensively evaluated on the basis of different criteria, such as correlation coefficient, information entropy, homogeneity, contrast, image, histogram, key sensitivity, hiding capacity, quality index, mean square error (MSE), peak signal-to-noise ratio (PSNR) and image fidelity. Results show that the proposed algorithm satisfies all the aforementioned criteria and is superior to other previous methods. Hence, it is efficient in hiding secret data and preserving the good visual quality of stego images. The proposed algorithm is resistant to different attacks, such as differential and statistical attacks, and yields good results in terms of key sensitivity, hiding capacity, quality index, MSE, PSNR and image fidelity

ESTIMATION FOLLICULAR FLUID CONTENTS AND SERUM IN AGEING IRAQI WOMEN-DURING IVF/ICSI CYCLES

 This study was aimed to estimate the effects of women age on oocytes quantity and quality and to determine whether there is a correlation between serum and follicular hormone levels. The samples were collected in the higher institute for the diagnosis of infertility and assisted reproduction techniques, Baghdad, Iraq. The 60 participants were split into two age groups, G1involved women younger than 35, while G2 involved women older than 35 years of age. The levels of FSH, LH, AMH, and GH in the serum and follicular fluid (FF) could be measured using (ELISA). The results demonstrated differences in the serum levels of FSH, LH, AMH, and GH between the young and elderly groups of infertile women on the day of oocyte extraction. The results proved statistically highly significant (P≤0.01) drop in the mean levels of hormones in the aged women group (FSH 21.67±0.53; LH 62.12±0.54; AMH 1370.74±94.59; GH 9.76±0.32 mIU/ML) compared with the younger women group (FSH 33.86±0.72; LH 85.072±2.70; AMH 3310.92±83.87; GH 30.40±0.45 mIU/ML). in this study the level of studied hormones in FF were significantly decreased with increasing women age, the mean of (FSH 19.59 ±0.28; LH 63.34 ±0.27; AMH 1769.46 ±17.92; GH 7.86 ±027 mIU/ML) in comparison with those levels in the younger group (FSH 31.40 ±0.95; LH 95.07 ±2.58; AMH 2547.35 ±124.09; GH 23.33 ±0.67 mIU/ML)

Synthesis, Anticancer and Antibacterial Activity of Mannose-based bis-1,2,3-Triazole Derivatives

       In the current work, aromatic amines and alkyl halides have been converted to the corresponding azides 2a‒d and 4a-d by the reaction with sodium nitrite and sodium azide respectively for amines and sodium azide for halides. Then, dipropargyl ether derivative of D-mannose 8 has been synthesized from diacetone mannose that has been obtained by the treatment of D-mannose (5) with dry acetone in the presence of sulfuric acid. Then, aldol condensation has been used to prepare diol 7 from the mannose diacetonide 6. The reaction of compound 7 with propargyl bromide in alkaline media has been afforded dipropargyl derivative 8. In a parallel step, both dialkyne with aromatic and aliphatic azide have been coupled to produce 1,2,3-triazole derivatives 9a‒d in the presence of Cu(I) salts. All synthesized compounds have been characterized by 1D and 2D NMR spectra alongside with HRMS data. The antibacterial activity against both gram-positive and gram-negative has been tested. Moreover, the anticancer activity has also been evaluated against AMJ13 cell line

Infantile Nephropathic Cystinosis in Sulaimani Pediatric Teaching Hospital: A Retrospective Cohort Study

Cystinosis is a rare metabolic autosomal recessive disorder which characterized by intralysosomal accumulation of cystine. There are three forms; infantile nephropathic is the commonest forms. to evaluate clinical presentations and outcome of infantile cystinosis. A retrospective cohort study conducted in Sulaimani Pediatric Teaching Hospital on 25 patients with infantile cystinosis during May 1, 2014, to June 1, 2017. This study has depended on clinical symptoms and signs, and corneal crystallization for the diagnosis of cystinosis. Gender of the patients was 13 (52%) females and 12 (48%) males. The ages were ranged between (1-12 years) with a mean age of (6.25 years). Eight (32%) patients were from Sulaimani city, but the other 17 (68%) patients were from outside of Sulaimani. Moreover, a 17 (68%) of them were Arabic and the other eight (32%) were Kurdish ethnic groups. The study showed a 20 (80%) positive consanguinity with 19 (76%) positive family history of infantile cystinosis. Additionally, the age of first presentations was between (0.25-2 years) with a mean of (0.8 years). Clinical features included a 100% for polyuria, polydipsia, and failure to thrive. Furthermore, 10 (40%) presented with constipation, 23 (92%) photophobia and 5 (20%) blond hair. Complications included 24 (96%) rickets, 14 (56%) renal insufficiency, 5 (20%) hypothyroidism, 4 (16%) genu valgum, 3 (12%) growth hormone deficiency, and 3 (12%) developed end-stage renal disease. Subsequently, two patients died (8%) due to end-stage renal disease. Finally, there was a statistically significant relationship between both renal insufficiency (P-value = 0.042) and hypothyroidism (P-value < 0.001) with Kurdish ethnicity. Conclusion: Incidence of cystinosis was high among consanguineous parents and those patients who had a positive family history of cystinosis. Furthermore, the delay in diagnosis was due to atypical presentations and unavailability of specific investigations

Buckling Analysis of Stiffened and Unstiffened Laminated Composite Plates

The present study focused mainly on the analysis of stiffened and unstiffened composite laminated plates subjected to buckling load. Analytical, numerical and experimental analysis for different cases has been considered. The experimental investigation is to manufacture the laminates and to find mechanical properties of glass-polyester such as longitudinal, transverse young modulus, shear modulus. The compressive test was carried to find the critical buckling load of plate. The design parameters of the laminates such as aspect ratio, thickness ratio, boundary conditions and number of stiffeners were investigated using high order shear deformation theory (HOST) and Finite element coded by ANSYS .The main conclusion was the buckling load could increase and decrease depending on the boundary conditions, thickness ratio, and, the aspect ratio and number of stiffeners of the plate