Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles and others relative geometric features for recognition give accuracy about 95.73% when the seven emotion classes are tested and 97.23% when the 6 classes (except normal class) are only tested. These rates are considered high when compared with the results of other newly published works.
Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c
... Show MoreWhenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas
... Show MoreData generated from modern applications and the internet in healthcare is extensive and rapidly expanding. Therefore, one of the significant success factors for any application is understanding and extracting meaningful information using digital analytics tools. These tools will positively impact the application's performance and handle the challenges that can be faced to create highly consistent, logical, and information-rich summaries. This paper contains three main objectives: First, it provides several analytics methodologies that help to analyze datasets and extract useful information from them as preprocessing steps in any classification model to determine the dataset characteristics. Also, this paper provides a comparative st
... Show MoreThe present study attempts to find out the effect of some fish preservatives in the laboratory, such as alcohol and dilute formalin, on some biological characteristics related to the body measurements of those fish preserved in these materials. The fish used in this study were the local Planiliza abu. The processes of expansion and contraction of the bodies of fish preserved in diluted formalin solution at a concentration of 10% and diluted ethyl alcohol solution at a concentration of 70%. As that the standard length of the specimens of this study, which are separately preserved in formalin 10% and alcohol 70%, in a completely isolated are fluctuating in change. Constant shrinkage in head length in both diluted formalin and alcohol.
... 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