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.
The aim of current study is to analyze the content of intermediate stage biology books based on multiple intelligences. To do this, the researcher used the descriptive analytical approach. To analyze the three books of the intermediate stage, the author adopted content analysis tool and area unit. They were exposed to group of experts in methods of teaching biology, and measurement and evaluation. The findings of the study have shown a significant difference between what was expected and the observation of the multiple intelligences for the three biology books excluded the (social, musical, and kinetic intelligence), and there is no significant difference between the analysis' result of the biology books and the expectations of b
... Show MoreThe poster is one of the means which can be communicate with others through it, to transfer ideas that the designer want to focus on, for its importance to accomplish the poster. It’s a visual mean contact aim to submit an idea to the audience to get a clear idea, and that would be through the shapes and subject to submit the idea. Depend on that our goal in this study is to find out, what follows:1-Finding the relationship between the shape and the idea.And the study comes up with several results, like:1-The drawings that contain themes connected with what the designer want to achieve, through the clearness of idea and to make those elements clear by putting more elements to surround the main shape.2-To assure that the strong connecti
... Show MoreMost studies combine that it is important to determine the extent of the public's trust TV for two reasons. First of knowing the impact of satellite TV audience ranges and the second determining public outlets for Information Find regard to the extent of the public's confidence in knowing the contents of the satellite during the occupation of Mosul crisis by organizing the Islamic state in Iraq and the Levant And the researcher developed a questionnaire to find out the public's confidence statement satellite contents provided by the questions related to exposandscale.
The researcher audience chose the city of Baghdad to the suitabil
... Show MoreThis research is dedicated to study Al-Ra’ee Al-Numayri, a distinctive poetic character, to find out the most important (artistic) pre-Islamic features that contributed to its formation. It is further dedicated to know the influence of these features on his literature in the literary arena. After surveying his poetic texts and reading them according to the analytical and investigative methods, the art of the researcher was limited to the field of traditionalists. He was following the footsteps of the ancients by adhering to the traditional Arabic poetry style and the traditional poetic image. Despite that, he had his own imprints and unique style of interrogating times and places with its people, animals and plants. H
... Show Morethe study considers the optical classification of cervical nodal lymph cells and is based on research into the development of a Computer Aid Diagnosis (CAD) to detect the malignancy cases of diseases. We consider 2 sets of features one of them is the statistical features; included Mode, Median, Mean, Standard Deviation and Maximum Probability Density and the second set are the features that consist of Euclidian geometrical features like the Object Perimeter, Area and Infill Coefficient. The segmentation method is based on following up the cell and its background regions as ranges in the minimum-maximum of pixel values. The decision making approach is based on applying of Minimum Dista
In the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used
... Show MoreDiabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed
... Show MoreIn recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.
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