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

A Factorial Study for separation anxiety in students, of Baghdad City

Academic Buoyancy of High School students at the Distinguished Schools

The present study aims to identify the socio-psychological implications that police investigators experience regarding the variable of gender, age, place of residence, qualification, military rank, and work experience. The study included 6 individuals who were working in investigation department in Hebron district as a sample. The results demonstrated that the targeted sample had a dump attitude toward the socio-psychological implications. The psychological implications reflected 2.8739, the social side represents 3.2956.

In the present work, bentonite clay was used as an adsorbent for the removal of a new prepared mono azo dye, 4-[6-bromo benzothiazolyl azo] thymol (BTAT) using batch adsorption method. The effect of many factors like adsorption time, adsorbent weight, initial BTAT concentration and temperature has been studied. The equilibrium adsorption data was described using Langmuir and frundlich adsorption isotherm. Based on kinetics study, it was found that the adsorption process follow pseudo second order kinetics. Thermodynamics data such as Gibbes Free energy ∆Gᵒ, entropy ∆Sᵒ and ∆Hᵒ were also determined using Vant Hoff plot.

Sorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.

The current research aimed to explore the practicing of cyber bullying among college students as well as the differences of practicing cyber bullying among university students based on gender variable. The finding revealed that there was a high prevalence rate for cyber bullying among research sample who was students from Baghdad University. It assured clearly that this group participated in cyber bullying effectively, due to the biological and psychological factors which make them super sensitive toward the social and economic problems. Moreover, the results showed that there were significant differences between male and female in practicing cyber bullying. The study proved that women use cyber bulling more than men.  

Phenytoin selective electrodes were constructed based on penytoin-phosphotungstate (Ph-PT) complex with different plasticizers; di-butyl phosphate (DBP), tri-butyl phosphate (TBP), di-butyl phthalate (DBPH),and o-nitro phenyl octyl ether (NPOE) phthalate. The electrodes based on DBPH, ONPOE plasticizers gave Narnistain slope which are, 56.4 and 55.3mV/decade with detection limit of 1.9x10-5 M , 1.8x10-5 and concentration range 10-1 to 10-4 M and pH range 3.0 – 8.0. The electrodes based on TBP and DBP showed non-Nernistain slopes, 40.2,40.5 mV/decade for both plasticizers. Interfering of some cations was investigated and shows no interfering with electrodes response. Potentiometric methods were used for measuring phenytion in