In the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used

In recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor

This study attempts to provide an approach analysis for the news, depending on the bases and principles which conceptuality semiotic researchers of this field first of them «A. J. Gremas» for the theory of «narrative discourse analysis», to more clarify we tried to apply it on a published press- news, to concludes the most important steps and methods that are necessary to follows gain more understanding of the press- news.

This research supports the UN’s 2030 Agenda and its goals of ending poverty and hunger. Fruit and vegetable (FandV) lose their freshness and weight when stored at unsuitable temperatures and relative humidity. This study was conducted in Baghdad governorate, located at latitude 33.3128057 and longitude 44.3614875, in the Karrada region from February 27 to April 17, 2024. It compared the effectiveness of different storage technologies, including evaporative cooling, various air velocities, and diverse packaging methods, against sustainable and nonpackaging approaches. The study employed an air cooler with a volume of 2000 ft3/s and insulated packaging. Temperature and relative humidity were recorded in the storage environment

Many pharmaceutical molecules have solubility problems that until yet consist a hurdle that restricts their use in the pharmaceutical preparations. Lacidipine (LCDP) is a calcium-channel blocker with low aqueous solubility and bioavailability.

        Lipid dosage forms are attractive delivery systems for such hydrophobic drug molecules. Nanoemulsion (NE)  is one of the popular methods that has been used to solve the solubility problems of many drugs. LCDP was formulated as a NE utilizing triacetin as an oil phase, tween 80 and tween 60 as a surfactant and ethanol as a co-surfactant. Nine formulas were prepared, and different tests performed to ensure the stability of the NEs, such as thermodyna

The present work aims to investigate the aerodynamic characteristics of the winglet cant angle of Boeing 737-800 wing numerically and experimentally. The wing contain two swept angles 38.3o and 29.13o respectively, taper ratio 0.15 and aspect ratio 8.04. The wing involves three types of airfoils sections. Four cant angles for blended winglet have been considered (0o, 34o, 60o, 83.3o). The winglet has been analyzed to find the best cant angle for the wing without and with winglet. These models have been tested theoretically at Reynolds number of 2.06 x106 in order to study the winglet aerodynamic characteristics which consist of coefficient of Drag, coefficient of lift and Lift to drag ratio, pitching moment coefficient and bending moment co