Abstract: Word sense disambiguation (WSD) is a significant field in computational linguistics as it is indispensable for many language understanding applications. Automatic processing of documents is made difficult because of the fact that many of the terms it contain ambiguous. Word Sense Disambiguation (WSD) systems try to solve these ambiguities and find the correct meaning. Genetic algorithms can be active to resolve this problem since they have been effectively applied for many optimization problems. In this paper, genetic algorithms proposed to solve the word sense disambiguation problem that can automatically select the intended meaning of a word in context without any additional resource. The proposed algorithm is evaluated on a col

As s widely use of exchanging private information in various communication applications, the issue to secure it became top urgent. In this research, a new approach to encrypt text message based on genetic algorithm operators has been proposed. The proposed approach follows a new algorithm of generating 8 bit chromosome to encrypt plain text after selecting randomly crossover point. The resulted child code is flipped by one bit using mutation operation. Two simulations are conducted to evaluate the performance of the proposed approach including execution time of encryption/decryption and throughput computations. Simulations results prove the robustness of the proposed approach to produce better performance for all evaluation metrics with res

The study examined the assessment of raw water and drinking water projects of  Diyala Governorate for the year 2017, amounting to (24) projects, The average per capita supply of potable water (0.396 m3 / day/person), which is less than the global standard for the average per capita of drinking water, and constitute water rumors within the network of water transport in the province (3%), and the water of raw and drinking value within the limits allowed to be used by Iraq and the global indicators of {Total acidity, alkaline, acidic function, chlorides, magnesium, Electrical conductivity, total soluble salts, sodium, potassium, sulfates, turbidity other than (raw water)}. While the index of calcium only a value higher than the limits

Ondansetron HCl (OND) is a potent antiemetic drug used for control of nausea and vomiting associated with cancer chemotherapy. It exhibits only 60 – 70 % of oral bioavailability due to first pass metabolism and has a relative short half-life of 3-5 hours. Poor bioavailability not only leads to the frequent dosing but also shows very poor patient adherence. Hence, in the present study an approach has been made to develop OND nanoparticles using eudragit^® RS100 and eudragit^® RL100 polymer to control release of OND for transdermal delivery and to improve patient compliance.

Six formulas of OND nanoparticles were prepared using nanoprecipitation technique. The particles sizes and zeta potential were measured

John Updike’s use of setting in his fiction has elicited different and even conflicting reactions from critics, varying from symbolic interpretations of setting to a sense of confusion at his use of time and place in his stories.  The present study is an attempt at examining John Updike’s treatment of binary settings in Pigeon Feathers and Other Stories (1962) to reveal theme, characters’ motives and conflicts.  Analyzing Updike’s stories from a structuralist’s perspective reveals his employment of two different places and times in the individual stories as a means of reflecting the psychological state of the characters, as in “The Persistence of Desire”, or expressing conflicting views on social and political is

Several stress-strain models were used to predict the strengths of steel fiber reinforced concrete, which are distinctive of the material. However, insufficient research has been done on the influence of hybrid fiber combinations (comprising two or more distinct fibers) on the characteristics of concrete. For this reason, the researchers conducted an experimental program to determine the stress-strain relationship of 30 concrete samples reinforced with two distinct fibers (a hybrid of polyvinyl alcohol and steel fibers), with compressive strengths ranging from 40 to 120 MPa. A total of 80% of the experimental results were used to develop a new empirical stress-strain model, which was accomplished through the application of the parti

This paper present the fast and robust approach of English text encryption and decryption based on Pascal matrix. The technique of encryption the Arabic or English text or both and show the result when apply this method on plain text (original message) and how will form the intelligible plain text to be unintelligible plain text in order to secure information from unauthorized access and from steel information, an encryption scheme usually uses a pseudo-random enecryption key generated by an algorithm. All this done by using Pascal matrix. Encryption and decryption are done by using MATLAB as programming language and notepad ++to write the input text.This paper present the fast and robust approach of English text encryption and decryption b

The process of accurate localization of the basic components of human faces (i.e., eyebrows, eyes, nose, mouth, etc.) from images is an important step in face processing techniques like face tracking, facial expression recognition or face recognition. However, it is a challenging task due to the variations in scale, orientation, pose, facial expressions, partial occlusions and lighting conditions. In the current paper, a scheme includes the method of three-hierarchal stages for facial components extraction is presented; it works regardless of illumination variance. Adaptive linear contrast enhancement methods like gamma correction and contrast stretching are used to simulate the variance in light condition among images. As testing material

Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.