The synthesis and properties of two new series of compounds having 1,3-Oxazepineand 1,3-thiazole rings connected through azo linkage are reported. These compounds weresynthesized by the reaction of phthalic anhydride with Schiff bases. The molecular structuresof these compounds were verified by elemental analysis, FTIR and 1HNMR spectroscopy.The mesomorphic behaviors of these compounds were studied by optical polarizedmicroscopy (OPM) and differential scanning calorimetry (DSC). All compounds of the twoseries show liquid crystalline properties. The influence of the central oxazepine and thiazolerings and the terminal substituents on the type and temperature range of the mesomorphousproperties of these compounds has been elucidated

Previously, many empirical models have been used to predict corrosion rates under different CO₂ corrosion parameters conditions. Most of these models did not predict the corrosion rate exactly, besides it determined effects of variables by holding some variables constant and changing the values of other variables to obtain the regression model. As a result the experiments will be large and cost too much. In this paper response surface methodology (RSM) was proposed to optimize the experiments and reduce the experimental running. The experiments studied effects of temperature (40 – 60 °C), pH (3-5), acetic acid (HAc) concentration (1000-3000 ppm) and rotation speed (1000-1500 rpm) on CO₂ corrosion performance of t

Abstract: The aim of the current research is to identify (the relationship between deep understanding skills and mathematical modeling among fifth grade students) the research sample consisted of (411) male and female students of the fifth grade of biology distributed over the General Directorates of Education in Baghdad / Al-Rusafa / 2 / and Al-Karkh / 1 /, and two research tools were built: 1- A test of deep understanding skills, consisting of (20) test items and a scale for two skills. 2- The second test consists of (24) test items distributed among (18) essay items and (6) objective items. The psychometric properties of validity, stability, discriminatory strength, and effectiveness of alternatives were verified for the two tests fo

Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

0

Multi-point forming (MPF) is an advanced flexible manufacture technology, and the technology results from the idea that the whole die is separated into small punches that can be adjusted height. This idea is applied to the traditional rigid blank-holder, so flexible blank-holder (FBH) idea can be obtained. In this work, the performance of a multi-point die is investigated with pins in square matrix and suitable blank holder. Each pin in the punch holder can be a significant moved according to the die high and at different load that applied with spring with respect to spring stiffness. The results shows the reduction in setting time with respect to traditional single point incremental forming process that lead to (90%). and also show duri

The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is