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.
MS Elias, RGM AL-helfy, Plant Archives, 2019
The study was conducted at the College of Agricultural Engineering Sciences - University of Baghdad in 2022. It aimed to improve the growth of the European black Henbane plant (
The need to constantly and consistently improve the quality and quantity of the educational system is essential. E-learning has emerged from the rapid cycle of change and the expansion of new technologies. Advances in information technology have increased network bandwidth, data access speed, and reduced data storage costs. In recent years, the implementation of cloud computing in educational settings has garnered the interest of major companies, leading to substantial investments in this area. Cloud computing improves engineering education by providing an environment that can be accessed from anywhere and allowing access to educational resources on demand. Cloud computing is a term used to describe the provision of hosting services
... Show MoreEach art has its own language. Per his style as an artist, which is characterized by the other. The methods differ and vary expressive art to another depending on the tools and methods used, and is a theatrical phenomenon did, and see, and touch, grasp, understand, and imagine, and emotion, and the blending of ideas and images. When unable to speak the language of the traditional theater For the delivery of a specific meaning or a single non-current at the time the highlight of our new language with a very wide area up to the extent of the unification of the languages of the world as it is in fine painting, it's the body of actor language, so it has become a mime art, which expressed Representative meanings reference and movement of vari
... Show MoreSentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina
... Show MoreBreast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep
... Show MoreIn Computer-based applications, there is a need for simple, low-cost devices for user authentication. Biometric authentication methods namely keystroke dynamics are being increasingly used to strengthen the commonly knowledge based method (example a password) effectively and cheaply for many types of applications. Due to the semi-independent nature of the typing behavior it is difficult to masquerade, making it useful as a biometric. In this paper, C4.5 approach is used to classify user as authenticated user or impostor by combining unigraph features (namely Dwell time (DT) and flight time (FT)) and digraph features (namely Up-Up Time (UUT) and Down-Down Time (DDT)). The results show that DT enhances the performance of digraph features by i
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