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 media of all kinds have the task of introducing, expressing and objectively representing the cultures of different societies in various types and forms of press and media. The precept of media pluralism is the basis for freedom of expression & the cornerstone of its realization. Therefore, it is linked to the establishment of several conditions and elements in order to establish it as a principle and practice. Issues of cultural diversity in media and cultural pluralism are one of the most important elements and indicators. So, this paper aims to shed light on the concept of media pluralism and related concepts within the framework of cultural diversity and multicultural indicators. Thus, highlighting the feature
... Show MoreIn the present research is marked (expressive drawing in contemporary Iraq, the study of morphological features) eating expressive as the direction of modern art in the drawing for the period before and after World Wars I and II. And follow the tracks. And in research and investigation about the origins and sources and characteristics of expressionist painting at adult patrons and art gatherings, and the extent of their impact in the drawing for contemporary Iraqi sixties and seventies generation (generation of professors) and down to the younger generation in the eighties of the last century. Over the nearly two decades of history of fine movement in Iraq, a period specified in the search within the limits of temporal boundaries, and by
... Show MoreThis article discusses some linguistic problems that arise when translating the Holy Quran from Arabic to Russian. We analyze lexical, syntactic and semantic problems and support them with Examples of verses from the Qur'an, since the Qur'an is the word of Allah. It contains prayers and instructions full of both literal representations and figurative comparisons. The identification of linguistic and rhetorical features challenges translators of the Holy Qur'an, especially when translating such literary devices as metaphor, assonance, epithet, irony, repetition, polysemy, metonymy, comparisons, synonymy and homonymy. The article analyzes: metaphor, metonymy, ellipsis, polysemy.
Abstract
The Umayyad poets tried to invest all artistic tools in order to achieve a measure of creativity in their texts. The phenomenon of visual composition is breaking the familiar writing system, with the aim of increasing the number of possible connotations. The visual in the Umayyad poetry tries to replace it through expression with the visual image, and its manifestations were manifested by the multiplication of punctuation marks in the body of the poetic text and the tearing of the single poetic line by cutting it into several sentences or repetition.
Keywords: visual formation, poetic writing, Umayyad poetry, recipien
Recommender Systems are tools to understand the huge amount of data available in the internet world. Collaborative filtering (CF) is one of the most knowledge discovery methods used positively in recommendation system. Memory collaborative filtering emphasizes on using facts about present users to predict new things for the target user. Similarity measures are the core operations in collaborative filtering and the prediction accuracy is mostly dependent on similarity calculations. In this study, a combination of weighted parameters and traditional similarity measures are conducted to calculate relationship among users over Movie Lens data set rating matrix. The advantages and disadvantages of each measure are spotted. From the study, a n
... Show MoreThe rapid development of telemedicine services and the requirements for exchanging medical information between physicians, consultants, and health institutions have made the protection of patients’ information an important priority for any future e-health system. The protection of medical information, including the cover (i.e. medical image), has a specificity that slightly differs from the requirements for protecting other information. It is necessary to preserve the cover greatly due to its importance on the reception side as medical staff use this information to provide a diagnosis to save a patient's life. If the cover is tampered with, this leads to failure in achieving the goal of telemedicine. Therefore, this work provides an in
... Show MoreNowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor
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