Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

Interface bonding between asphalt layers has been a topic of international investigation over the last thirty years. In this condition, a number of researchers have made their own techniques and used them to examine the characteristics of pavement interfaces. It is obvious that test findings won't always be comparable to the lack of a globally standard methodology for interface bonding. Also, several kinds of research have shown that factors like temperature, loading conditions, materials, and others have an impact on surface qualities. This study aims to solve this problem by thoroughly investigating interface bond testing that might serve as a basis for a uniform strategy. First, a general explanation of how the bonding strength

Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

      The Matching and Mosaic of the satellite imagery play an essential role in many remote sensing and image processing projects. These techniques must be required in a particular step in the project, such as remotely change detection applications and the study of large regions of interest. The matching and mosaic methods depend on many image parameters such as pixel values in the two or more images, projection system associated with the header files, and spatial resolutions, where many of these methods construct the matching and mosaic manually. In this research, georeference techniques were used to overcome the image matching task in semi automotive method. The decision about the quality of the technique can be considered i

This work deals with the separation of benzene and toluene from a BTX fraction. The separation was carried out using adsorption by molecular sieve zeolite 13X in a fixed bed. The concentration of benzene and toluene in the influent streams was measured using gas chromatography. The effect of flow rate in the range 0.77 – 2.0 cm3/min on the benzene and toluene extraction from BTX fraction was studied. The flow rate increasing decreases the breakthrough and saturation times. The effect of bed height in the range 31.6 – 63.3 cm on benzene and toluene adsorption from BTX fraction was studied. The increase of bed height increasing increases the break point values. The effect of the concentration of benzene in the range 0.0559 – 0.2625g/

The biochar prepared from sawdust raw material was applied in this study for the treatment of wastewater polluted with methyl orange dye. The effect of pH (2-11), initial concertation (50-250 mg/L) and time were studied. The isotherm of Langmuir, Frendluch and temkin models studied. The Langmuir model was the best to explain the adsorption process, maximum uptake was 136.67 mg/g at 25C^o of methyl orange dye. Equilibrium reached after four hours of contact for most adsorbents.The values of thermodynamic parameters ∆G were negative at various temperatures, so the process spontaneous, while ∆H values were 16683 j/mol and ∆S values was 60.82 j/mol.k.

In order to reduce hydrostatic pressure in oil wells and produce oil from dead oil wells, laboratory rig was constructed, by injecting LPG through pipe containing mixture of two to one part of East Baghdad crude oil and water. The used pressure of injection was 2.0 bar, which results the hydrostatic pressure reduction around 246 to 222 mbar and flow rate of 34.5 liter/hr fluid (oil-water), at 220 cm injection depth. Effects of other operating parameters were also studied on the behavior of two phase flow and on the production of oil from dead oil wells.

This work focuses on the use of biologically produced activated carbon for improving the physi-co-chemical properties of water samples obtained from the Tigris River. An eco-friendly and low-cost activated carbon was prepared from the Alhagi plant using potassium hydroxide (KOH) as an impregnation agent. The prepared activated carbon was characterised using Fourier-transform infrared spectroscopy to determine the functional groups that exist on the raw material (Alhagi plant) and Alhagi activated carbon (AAC). Scanning electron microscope–energy-dispersive X-ray spectroscope was also used to investigate the surface shape and the elements that compose the powder. Brunauer–Emmett–Teller surface area analysis was used to evaluate the spe

The exploitation of obsolete recyclable resources including paper waste has the advantages of saving resources and environment protection. This study has been conducted to study utilizing paper waste to adsorb phenol which is one of the harmful organic compound byproducts deposited in the environment. The influence of different agitation methods, pH of the solution (3-11), initial phenol concentration (30-120ppm), adsorbent dose (0.5-2.5 g) and contact time (30-150 min) were studied. The highest phenol removal efficiency obtained was 86% with an adsorption capacity of 5.1 mg /g at optimization conditions (pH of 9, initial phenol concentration of 30 mg/L, an adsorbent dose of 2 g and contact time of 120min and at room temperature).

In this study, the adsorption of Zn (NO3)2 is carried out by using surfaces of malvaparviflora. The validity of the adsorption is evaluated by using atomic absorption Spectrophotometry through determination the amount of adsorbed Zn (NO3)2. Various parameters such as PH, adsorbent weight and contact time are studied in terms of their effect on the reaction progress. Furthermore, Lagergren’s equation is used to determine adsorption kinetics. It is observed that high removal of Zn (NO3)2 is obtained at PH=2. High removal of Zn (NO3)2 is at the time equivalent of 60 min and reaches equilibrium,where 0.25gm is the best weight of adsorbant . For kinetics the reaction onto malvaparviflora follows pseudo first order Lagergren’s equation.