Audio classification is the process to classify different audio types according to contents. It is implemented in a large variety of real world problems, all classification applications allowed the target subjects to be viewed as a specific type of audio and hence, there is a variety in the audio types and every type has to be treatedcarefully according to its significant properties.Feature extraction is an important process for audio classification. This workintroduces several sets of features according to the type, two types of audio (datasets) were studied. Two different features sets are proposed: (i) firstorder gradient feature vector, and (ii) Local roughness feature vector, the experimentsshowed that the results are competitive to those gotten from other popular methods inthis field, such as Zero Crossing Rate (ZCR), Amplitude Descriptor (AD), Short Time Energy (STE), and Volume (Vo). The test results indicated, that the attained averageaccuracy of classification is improved up to94.9232% for training set and 95.8666%for testing set.The classification performance of these two extracted featuresets is studied individually, and then they used together as one feature set. Theiroverall performance is investigated, the test results showed that the proposed methods give high classification rates for the audio.
This work was conducted to study the extraction of pelletierine sulphate from Punica granatum L. roots by liquid membrane techniques. Pelletierine sulphate is used widely in medicine. The general behavior of extraction process indicates that pelletierine conversion increased with increasing the number of stages and the discs rotation speed but high rotation speed was not favored because of the increased risk of droplet formation during the operation. The pH of feed and acceptor solution was also important. The results exhibit that the highest pelletierine conversion was obtained when using two stages, (10 rpm) discs speed of stainless steel discs, (pH=9.5) of feed solution and (pH=2) of acceptor solution in n-decane. Assuming the existen
... Show MoreAbstract: Iatrogenic furcal root perforations are serious complications during dental treatment. This study was aimed to compare the sealing ability of new bioceramic root repair material TotalFill® with the other perforation repair materials (GIC, MTA and Biodentine) using a dye- extraction method.Materials and Methods: Forty extracted, human mandibular molars with non-fused well developed root were collected. Artificial perforations were made from the external surface of the teeth. Then the teeth were randomly divided into 4 experimental groups (n= 10) according to the type of repair material used in this study; Medifil glass ionomercement, TotalFill® bioceramic root repair material, BiodentineTM and MTA Plus. The specimens were then im
... Show MoreIraqi crude Atmospheric residual fraction supplied from al-Dura refinery was treated to remove metals contaminants by solvent extraction method, with various hydrocarbon solvents and concentrations. The extraction method using three different type solvent (n-hexane, n-heptane, and light naphtha) were found to be effective for removal of oil-soluble metals from heavy atmospheric residual fraction. Different solvents with using three different hydrocarbon solvents (n-hexane, n-heptane, and light naphtha) .different variables were studied solvent/oil ratios (4/1, 8/1, 10/1, 12/1, and 15/1), different intervals of perceptual (15, 30-60, 90 and 120 min) and different temperature (30, 45, 60 and 90 °C) were used. The metals removal perce
... Show More
(1)
Lipase enzyme has attracted a lot of attention in recent years because of its diverse biotechnological applications. The present study was conducted to screen germinated seeds of four crops, namely sunflower (Helianthus annuus), flaxor linseed (Linum usitatissimum ), peanut (Arachis hypogaea ) and castor bean (Ricinus communis), for the activity of their lipases. to the study also included the extraction and purification of lipase from the seeds of the most promising crop using different solvents. The results indicated that the maximum enzymatic activity (0.669 U/ml) was obtained when 0.1 M Tris-HCl buffer extract was used after 3 days of seed germination of all the tested species, as compared to the other test solvents
... Show More
(11)
(5)
Two different oxidative desulfurization strategies based on oxidation/adsorption or oxidation/extraction were evaluated for the desulfurization of AL-Ahdab (AHD) sour crude oil (3.9wt% sulfur content). In the oxidation process, a homogenous oxidizing agent comprising of hydrogen peroxide and formic acid was used. Activated carbons were used as sorbent/catalyst in the oxidation/adsorption process while acetonitrile was used as an extraction solvent in the oxidation/extraction process. For the oxidation/adsorption scheme, the experimental results indicated that the oxidation desulfurization efficiency was enhanced on using activated carbon as catalyst/sorbent. The effects of the operating conditions (contact time, temperat
... Show MoreAnchusa strigosa L.: Hardy annual biennial or perennial herb, with hairs especially on the leaves., flowers generally regular. Commonly named (Lisan Althour) in Iraq, from Boraginaceae family. The plant contains phenolic acids, flavonoids, alkaloids, sterols, and terpenoids. The Whole plant part defatted with n-hexane for 24 hours. The defatted plant material extracted using absolute methanol by Soxhlet apparatus for 24 hours, the extract fractionated by solvents of different polarity: petroleum ether- chloroform - ethylacetate- and n-butanol respectively. The n-butanol fraction hydrolyzed with 10% HCl for 5 hours by reflex to break down the glycosidic linkage. Rosmarinic acid, caffeic acid, genistein, and silybin were isolated
... Show More
(14)
(4)
Analysis the economic and financial phenomena and other requires to build the appropriate model, which represents the causal relations between factors. The operation building of the model depends on Imaging conditions and factors surrounding an in mathematical formula and the Researchers target to build that formula appropriately. Classical linear regression models are an important statistical tool, but used in a limited way, where is assumed that the relationship between the variables illustrations and response variables identifiable. To expand the representation of relationships between variables that represent the phenomenon under discussion we used Varying Coefficient Models
... Show More
A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure aga
... Show MoreA genetic algorithm model coupled with artificial neural network model was developed to find the optimal values of upstream, downstream cutoff lengths, length of floor and length of downstream protection required for a hydraulic structure. These were obtained for a given maximum difference head, depth of impervious layer and degree of anisotropy. The objective function to be minimized was the cost function with relative cost coefficients for the different dimensions obtained. Constraints used were those that satisfy a factor of safety of 2 against uplift pressure failure and 3 against piping failure.
Different cases reaching 1200 were modeled and analyzed using geo-studio modeling, with different values of input variables. The soil wa
(11)
Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu
... Show More
(4)
(2)
