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.
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Digital change detection is the process that helps in determining the changes associated with land use and land cover properties with reference to geo-registered multi temporal remote sensing data. In this research change detection techniques have been employed to detect the changes in marshes in south of Iraq for two period the first one from 1973 to 1984 and the other from 1973 to 2014 three satellite images had been captured by land sat in different period. Preprocessing such as geo-registered, rectification and mosaic process have been done to prepare the satellite images for monitoring process. supervised classification techniques such maximum likelihood classification has been used to classify the studied area, change detection aft
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A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification
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The aim of this study is to investigate the existence of some heavy metals (lead, cadmium, chromium) in colored plastic table dishes and study the migration of these metals to the food meals and the affecting factors in migration , such as storage period and food temperature. Six kinds of colored plastic table dishes were collected from Baghdad markets. The heavy metals in table dishes and in the prepared food meals put in them were estimated using atomic absorption spectrophotometer (Shimadzu A5000). The results indicated the existence of lead in all samples (1.61_1.00 mg/ kg) and chromium in three samples (0.85_0.97 mg/ kg) while other samples are free of chromium, and cadmium. Investigating the migration of these metals to food at dif
... Show MoreSome of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems. Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic. Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance. In this study, two different sets of select
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Filed experiment was conducted to test the effect of saline water and potassium fertilizers rate on proline and water potential of Pisum sativum L. (Var.Senador Cambados ) leaves . Treatments of the experiment included two levels of water salinity( 2, 7 dSm-1) as a main plot and fertilizer rates as a sub plot. Results indicated that irrigation of plant with saline water 7 dSm-1 and fertilization 150 kg/donum increased proline accumulation and water potential 0.31 mmol/g,-17.00 bar at 9 AM morning and 0.62 mmol/g , -21.00 bar at 3 PM afternoon ,Irrigating plant with a 2 dSm-1 and fertilization 300 kg/donum decreased proline accumulation and water potential of leaves 0.22 mmol/g, -16.00 bar at 9 A
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Two field experiments were conducted during the spring seasons of 2000,2001.The aim was to study the effect of hardening to drought tolerance on moisture percentage in root and stem of sunflower plant during growth stages . Asplit-split plots design was used with three replications.The main plots included irrigation treatments:irrigation to100%(full irrigation),75and50%of available soil water.The sub plots were the cultivars Euroflor and Flame.The sub-sub plots represented four seed soaking treatments :Control(unsoaked),soaking in water ,Paclobutrazol solution(250ppm),and Pix solution(500ppm). The soaking continued for 24 hours then seeds were dried at room temperature until they regained their original weight. Amount of water
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Conjugated Linoleic Acid (CLA) is an essential polyunsaturated omega fatty acid that occurs naturally in vegetable oils. It also plays an important role in preserving meat for longer periods by preventing oxidation of other fats. Thus, it can be used in the production of functional foods with high biological value and low cholesterol levels by adding poultry diets. Objective: The aim of the present study was to evaluate the effect of adding CLA to broiler diets on production performance and fatty acid content in the meat. Methodology: One-day-old Ross-308 chicks were randomly distributed into four dietary treatment groups: control (0 g CLA kgG1 diet; A1), 0.5 g CLA kgG1 diet (A2), 0.75 g CLA kgG1 diet (A3) and 1 g CLA kgG1 diet (A4). Diets
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Abstract
This paper represents a study of the effect of the soil type, the drilling parameters and the drilling tool properties on the dynamic vibrational behavior of the drilling rig and its assessment in the drilling system. So first, an experimental drilling rig was designed and constructed to embrace the numerical work.
The experimental work included implementation of the drill-string in different types of soil with different properties according to the difference in the grains size, at different rotational speeds (RPM), and different weights on bit (WOB) (Thrust force), in a way that allows establishing the charts that correlate the vibration acceleration, the rate of penetration (ROP), and the power
... Show MoreStevia rebaudiana Bertoni contains diterpenoid steviol glycosides that have no adverse impact on blood sugar levels despite being 300 times sweeter than sugar. This study aimed to investigate the rate of callus induction from stevia leaves and the content of glycosides when changing the sucrose percentage in the culture medium.. Murashige and Skoog (MS) culture medium supported by 4.0 mg/l naphthalene acetic acid (NAA) and 1.0 mg/l benzyl adenine (BA) was used, and different concentrations of sucrose (2, 3, 4, 5 and 6%) were tested .The extraction of glycosides from leaf and callus tissues was performed by using methanol. Extracted glycosides were analyzed by high-performance liquid chromatography (HPLC). The results showed signific
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