Phonetics has close relevance with Musicology; in this study I decided explaining the interlinkages and harmony between Phonetics and Musicology. Linguists preceded philosophers in an attempt to link Phonetics with Musicology; the 1st serious attempt to link Phonetics with Musicology was done by Ibn Jeny (Dead 392 IC), but the real attempt is found with Farabi through his book under title Al Musiqa Al Kabeer, he defined music and link it with tune and relation between melody and tone, This is the same as pointed out by Ikhwan Al Safa who followed the doctrine of al-Farabi, their attention was with music and link it with phoneme, as they made music independent science, and they created special mathematics rules for it. Melody in music can

In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

A robust video-bitrate adaptive scheme at client-aspect plays a significant role in keeping a good quality of video streaming technology experience. Video quality affects the amount of time the video has turned off playing due to the unfilled buffer state. Therefore to maintain a video streaming continuously with smooth bandwidth fluctuation, a video buffer structure based on adapting the video bitrate is considered in this work. Initially, the video buffer structure is formulated as an optimal control-theoretic problem that combines both video bitrate and video buffer feedback signals. While protecting the video buffer occupancy from exceeding the limited operating level can provide continuous video str

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

The current study aimed to determine the morphometric and meristic characteristics of the North African catfish Clarias gariepinus (Burchell, 1822). Six specimens of C. gariepinus were collected from the Tigris River, in central Iraq. This study is considered the confirmation first record of this species in Iraq, and the second documentation of this exotic fish. The present species is characterized by a very long dorsal fin, a rounded caudal fin and four pairs of barbels.

Freshwater mussels are a guild of stationary, suspended-feeding species; they perform significant ecological functions like nitrogen cycling, bioturbation that gives oxygen and habitat that other creatures need to survive, and increasing water clearance by filtration. Knowledge of the freshwater mussel Unio tigridis Bourguignat, 1852, distribution, and molecular study in Iraq was inadequate. In the current study, this species of freshwater Mussels belonging to the family Unionidae was collected from different locations in the Greater Zab River, from April 2022 to November 2022. The average water temperature of the site was arranged between (17.8 to 36.1 C°). All previous studies in the Kurdistan Region and Iraq were based on morphologic

This research was conducted to determine content levels of heavy metal pollution. Samples taken from Ishaqi River bank and adjacent agricultural soils area, in ten sites, distributed along 48 km of the Ishaqi River, north Baghdad. The evaluated metals were Zinc, Copper, Manganese, Iron, Cobalt, Nickel, Chromium, Cadmium, Vanadium and Lead. PH and Electric Conductivity (EC) were measured to evaluate the acidity and (EC). Results showed that most site were contaminated with metals evaluated. Among these metals, Zn, Mn, Fe and Ni were consistently higher in all the samples (both river bank and adjacent soil) followed by PB, CU, V, Cd, Co and Cr. The level concentrations of river bank were almost higher than that of adjacent soil. As will be re