The concentrations of SO2 emissions released from Kuwaiti power plant are discussed in this paper. The level was assessed utilizing the upsides of Air Quality Index - AQI pointer, which is estimated hourly, every day and yearly. The air quality was observed at four unique local locations in Kuwait throughout the span of a year. Air Quality Index (AQI) is utilized here to survey the degree of SO2 outflows from such power stations in Kuwait. The QAI has a relation with the rate of pollutants emissions which is determined in this paper. It was found by comparing the studied power plants in Kuwait that Mutla power plant has the higher SO2 concentrations followed by Mansouriya, then Jahra and finally Rabia in 2008, this is refer for the emission reduction technology followed in each of the four studied power plants. Also depending on Air Quality Index (AQI) values it was found that AQI at the three power plant (Jahra, Mansouriya and Al-Qurain) is in good level of air pollution. In 2021, the Doha power plant has a higher values of SO2, then Al-Qurain area, Al-Mansouriya area and Al-Jahra area respectively.

ML is often seen as a ‗plug-and-play‘ learning methodology that can be thrown at raw data for whatever problem comes to hand. Given this fact, this study aims to develop design principles in an AI context by taking into account various design guidelines, processes, and tools. The study explores how designers and AI engineers conceptualize the guidelines from different ―points of view‖ to co-create AIX. By exploring the relevant body of existing work, the paper develops design framework based on a set of hypothetical model metrics. For generalization, it is suggested that the proposed design principles need to be validated in different contexts in further research. Last, but not least, it should be taken into account that it ML models merely provide advice as to which features of the problem seemed to be important and which seemed unimportant rather than offering a full intuitive understanding of the topic at hand.

This working paper will discuss on the significants of procedures for classifying, sequencing instructional objectives and Using Bloom's Revised Taxonomy in Assessment. Content analysis method was utilized in this study for gathering of data using citations and literatures from the Internet, speeches and books. It was suggested that a behavioral taxonomy is often useful as a classiflcation scheme to organize instructional objectives. Taxonomies for the cognitive, affective, and psychomotor domains were presented. Suggestions were then offered for employing the taxonomies for classifying objectives. Task analysis was examined as a procedure for sequencing objectives in a hierarchal arrangement. As such, task analysis is a procedure used to complement objective classification. Task analysis used in conjunction with taxonomic classification provides necessary information for sequencing instructional objectives.

Tetrabutylammonium bromide (TBAB) influence on the binary complexes of divalent selected metal ions of first transition series;Manganese(II), Cobalt(II), Nickel(II), Copper(II) and Zinc(II) with L-glutamine (Gln) and succinic acid (Suc) has been studied pH metrically at an ionic strength of 0.16 mol dm-3 and temperature 303 K. Various models for the species of these ligands are refined by using the computer programs SCPHD and MINIQUAD75. The active species of the selected metal ions are MLH for succinic acid and ML2H for L-glutamine. The trend in the variation of stability constants with atomic number is explained on the basis of ionic radii of metal ions, electrostatic and non-electrostatic interactions in solutions. The species distribution with pH, plausible equilibria and structures of the species are also presented.