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.
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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Some 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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In this paper, an efficient image segmentation scheme is proposed of boundary based & geometric region features as an alternative way of utilizing statistical base only. The test results vary according to partitioning control parameters values and image details or characteristics, with preserving the segmented image edges.
Methods: 112 placentae samples were investigated during the period from August 2007 to August 2008 under light microscopefor mother aged 15 - 45 years old.Results: It was found that normal placental shapes had no correlation to mother age, while abnormal shapes were found more inyoung age groups. The better placental measured parameters were found in mother age 20-24 years. The percentages ofabnormal umbilical cord insertion were very high compared to other studies. Babies’ gender had a correlation with theplacental thickness; male babies have thicker placentae than females. Male babies have longer umbilical cords with widerdiameter than females. Light microscope picture showed the chorionic villi with isolated fetal blood vessel were hig
... Show MoreCorruption (Definition , Characteristics , Reasons , Features , and ways of combating it)
Eichhornia crassipes (Mart.) Solms or Water hyacinth is a fertile floating aquatic widespread in worldwide. The form of plants and the anatomy parts of this plant were studied. The most important feature was obvious the air chamber with intercellular spaces by amazing arrangement. As well can notice aerenchyma tissue allow the parts of plants floated on the surface of water located in the ground meristem of root, petiole and in the mesophyll of leaves also presence of two type of crystals raphides and styloid crystals was noted of various member in the plant in addition appear astrosclereids around the air chambers, to support the plant parts from the unsuitable environmental conditions such as the speed of water flow or floods or high leve
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To understand what the arts in general, and plastic arts in particular, have to do, it is necessary to know how they perform, not only that, but also to know their history, which we should understand at least in general terms. Which in turn gives an image of the standards of taste prevailing in each age, and some of the social and historical relationship of each era, and the cultural expression of that era, which is shown in the arts. We need to understand that the arts of each stage, although different from each other, yet remain interrelated in what we see through the effects that appear through the succession of times, which creates certain artistic traditions, inherited by one generation after the other. The research in this field de
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