One of the main aims of Metrical Phonology Theory (MTT) is to provide the stress of poetry on the syllable, the foot, and the phonological word levels. Analyzing poetry embodies one of the most prominent and controversial metrical issues as the subsumed number and types of syllables, feet, and meters are balanced compared to other literary texts. The MTT saw the light during the late seventies (1975) and (1977) by Liberman and Prince, who produced it as part of non-linear phonology. Its roots originated in prosody, which studies poetic meter and versification. The basis of the metrical analysis is the prosodic analysis developed in London by Firth and his students in 1950. This study aims to identify the values of five metri

Sex chromatin (SC) is defined as inactive X chromosome in the female somatic cells, it condensed as heterochromatic at interphase of the nucleus and appears like nuclear satellite projection, and only female cells contain SC in mammals. Different ages of cocks: immature (8,16 weeks old), growing (24 weeks old) and production age (32,48 weeks old) , were studied to detect the sex chromatin (SC) with it's various shapes :Sessile nodule(SS), Drum stick(DS), Tear drop(TD) and Club shape(CS) in the blood lymphocytes of blood smears prepared from WBCs of 45 New Hampshire(NH) strain cocks. Also SC measurements were detected which include: vertical (V) and horizontal (H) axes, SC area (SCA), nuclear area (NA), and the

Source, sedimentation, coagulation, flocculation, filter, and tank are parts of a water treatment plant. As a result, some issues threaten the process and affect the drinking water quality, which is required to provide clean drinking water according to special standards and international and local specifications, determined by laboratory results from physical, chemical, and biological tests. In order to keep the water safe for drinking, it is necessary to analyze the risks and assess the pollution that occurs in every part of the plant. The method is carried out in a common way, which is monitoring through laboratory tests, and it is among the standards of the global and local health regulators

In this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN). Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN). In this work, the precision agriculture system  is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce p

KE Sharquie, AA Noaimi, MS Younis, BS Al-Sultani, Journal of Cosmetics, Dermatological Sciences and Applications, 2014 - Cited by 5

The limitations of wireless sensor nodes are power, computational capabilities, and memory. This paper suggests a method to reduce the power consumption by a sensor node. This work is based on the analogy of the routing problem to distribute an electrical field in a physical media with a given density of charges. From this analogy a set of partial differential equations (Poisson's equation) is obtained. A finite difference method is utilized to solve this set numerically. Then a parallel implementation is presented. The parallel implementation is based on domain decomposition, where the original calculation domain is decomposed into several blocks, each of which given to a processing element. All nodes then execute computations in parall

In this paper we investigate the automatic recognition of emotion in text. We propose a new method for emotion recognition based on the PPM (PPM is short for Prediction by Partial Matching) character-based text compression scheme in order to recognize Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method is very effective when compared with traditional word-based text classification methods. We have also found that our method works best if the sizes of text in all classes used for training are similar, and that performance significantly improves with increased data.