A field trial was conducted in Experimental Station of The Field Crops Department – College Of Agriculture In Abu Ghraib, University of Baghdad to assess the effect of sulphur applications and the time after application on pH and EC of soil sample solutions ,and on the growth and yield of rape seed (Brassica napus L.)A split plot design was used with four replications , The main plot included four sulphur applications levels (0,2000,3000,4000Kg S/ha) the sub plot were the time after application (0,1,2,and 3 moths) .Sulphur application significantly decreased soil pH value ,although that decrease reached minimum parameter after two months from application date .Rather increment of sulphur application level significantly raised soil EC val

The experiment was conducted using Potato( Solanum tuberosum L.) at the eastern Radwaniyah at private field during fall season 2020/2021 and spring 2021 to study the effect of nitrogen levels to 350, 275, 200 kg N h-1 ( N1, N2, N3) and phosphorous to 100, 180, 360 kg P2O5 h-1 ( P1, P2, P3) and potassium to 100, 200, 300 kg K2O h-1 ( K1, K2, K3) to vegetative growth and yield of industrial potato, The seeds of the hybrid potato Sinora, Class A, were planted in the fall season on 15/9/2020 and Elite in the spring season on 31/1/2021. The experimental fertilizers were added in four batches and in proportions according to the stages of plant age, Factorial experiment with RCBD using three replications. The results showed that changing t

The research aims to measure the impact of envy on job stress because the topic of envy represents a negative emotion that exists at all organizational levels, which may cause stress in the work environment.

The Research problem is represented by the lack of perception of most of the faculty staff on the negative effects of envy on their well-being in the Technical College of Management - Baghdad, and what is the impact level of envy on their job stress.

To achieve this, the scale of envy was based on two dimensions (being envied, Envying others), While the job stress scale was based on seven dimensions (workload, conflict role, Family factors, work environment, work relationships

     Heavy metal ion removal from industrial wastewater treatment systems is still difficult because it contains organic contaminants. In this study, functional composite hydrogels with photo Fenton reaction activity were used to decompose organic contaminants. Fe₃O₄ Nanoparticle, chitosan (CS), and other materials make up the hydrogel. There are different factors that affected Photo-Fenton activity including (pH, H₂O₂ conc., temp., and exposure period). Atomic force microscopy was used to examine the morphology of the composite and its average diameter (AFM). After 60 minutes of exposure to UV radiation, CS/ Fe₃O₄ hydrogel composite had degraded methylene blue (M.B.)

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet