This research aims to suggest formulas to estimate carry-over effects with two-period change-over design, and then, all other effects in the analysis of variance of this design, and find the efficiency of the two-period change-over design relative to another design (say, completely randomized design).

In this paper, the dynamic behaviour of the stage-structure prey-predator fractional-order derivative system is considered and discussed. In this model, the Crowley–Martin functional response describes the interaction between mature preys with a predator.  e existence, uniqueness, non-negativity, and the boundedness of solutions are proved. All possible equilibrium points of this system are investigated.  e su‰cient conditions of local stability of equilibrium points for the considered system are determined. Finally, numerical simulation results are carried out to con‹rm the theoretical results.

The present research was conducted to reduce the sulfur content of Iraqi heavy naphtha by adsorption using different metals oxides over Y-Zeolite. The Y-Zeolite was synthesized by a sol-gel technique. The average size of zeolite was 92.39 nm, surface area 558 m²/g, and pore volume 0.231 cm³/g. The metals of nickel, zinc, and copper were dispersed by an impregnation method to prepare Ni/HY, Zn/HY, Cu/HY, and Ni + Zn /HY catalysts for desulfurization. The adsorptive desulfurization was carried out in a batch mode at different operating conditions such as mixing time (10,15,30,60, and 600 min) and catalyst dosage (0.2,0.4,0.6,0.8,1, and 1.2 g). The most of the sulfur compounds were removed at 10 min for all catalyst ty

The tourism industry, with its two sides (recreational and religious), is one of the important investment fields in Iraq, it is represented Iraq as the second economic source after the oil sector. So a need for serious efforts to develop the tourism sector and maintain its sustainability. This paper will be one of the important contributions in this field; the paper aims to explore the extent of the impact of the sustainable strategy on the level of overall performance in the Iraqi tourism sector. The field of research was some Iraqi tourist institutions at Iraqi tourism, Which covers the field of study on the one side, and can be studied on the other side, for the developing study methodology and organizing its main parts, the research pap

The research aims to measure the impact of the empowerment strategy on the performance of employees by mediating organizational trust in the organization. The problem of research was the weak ability of most business organizations to employ the strategy of empowerment in maximizing the performance of employees, and the importance of research in practice lies in the results of a guide to managers in how to use the strategy of empowerment in maximizing the performance of employees by mediating organizational trust dimensions of ability, benevolence, integrity. In order to achieve the objectives of the research and to answer the questions of the problem, the researcher has adopted the descriptive analytical approach as the questionnaire was

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

In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.

The availability of different processing levels for satellite images makes it important to measure their suitability for classification tasks. This study investigates the impact of the Landsat data processing level on the accuracy of land cover classification using a support vector machine (SVM) classifier. The classification accuracy values of Landsat 8 (LS8) and Landsat 9 (LS9) data at different processing levels vary notably. For LS9, Collection 2 Level 2 (C2L2) achieved the highest accuracy of (86.55%) with the polynomial kernel of the SVM classifier, surpassing the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) at (85.31%) and Collection 2 Level 1 (C2L1) at (84.93%). The LS8 data exhibits similar behavior. Conv