The effect of different cutting fluids on surface roughness of brass alloy workpiece during turning operation was carried out in this research. This was performed with different cutting speed, while other cutting parameters had been regarded as constants(feeding rate , and depth of cut). Surface roughness of machined parts that will be tested by electronic surface roughness tester .The results show that the standard coolant gives the best values of surface roughness for fixed cutting speed ,followed by sun flower oil that has approximately the same effect, while the air stream as a coolant gave unsatisfied results for the evaluation of surface roughness.

In the other hand the best values of surface roughness were recorded for max

Environmental pollution is experiencing an alarming surge within the global ecosystem, warranting urgent attention. Among the significant challenges that demand immediate resolution, effective treatment of industrial pollutants stands out prominently, which for decades has been the focus of most researchers for sustainable industrial development aiming to remove those pollutants and recover some of them. The liquid membrane (LM) method, specifically electromembrane extraction (EME), offers promise. EME deploys an electric field, reducing extraction time and energy use while staying eco-friendly. However, there's a crucial knowledge gap. Despite strides in understanding and applying EME, optimizing it for diverse industrial pollutant

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

 A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.

One of the recent significant but challenging research studies in computational biology and bioinformatics is to unveil protein complexes from protein-protein interaction networks (PPINs). However, the development of a reliable algorithm to detect more complexes with high quality is still ongoing in many studies. The main contribution of this paper is to improve the effectiveness of the well-known modularity density ( ) model when used as a single objective optimization function in the framework of the canonical evolutionary algorithm (EA). To this end, the design of the EA is modified with a gene ontology-based mutation operator, where the aim is to make a positive collaboration between the modularity density model and the proposed

This effort is related to describe and assess the performance of the Iraqi cement sample planned for oil well-cementing jobs in Iraq. In this paper, major cementing properties which are thickening time, compressive strength, and free water in addition to the rheological properties and filtration of cement slurry underneath definite circumstances are experimentally tested. The consequences point to that the Iraqi cement after special additives encounter the requests of the API standards and can consequently is used in cementing jobs for oil wells. At this research, there is a comparative investigation established on experimental work on the effectiveness of some additives that considered as waste materials which are silica fume, baux

Villages in most rural areas of the developing world, including Iraq, suffer from a deterioration in the urban structure in its various aspects, both in the lack of internal planning in terms of residential unit design which is not commensurate with the sustainable health life, in addition to the lack of infrastructure and community services networks As well as road networks linking them to neighboring urban centers, which was accompanied by the emergence of other problems, including the desire of the population to migrate to neighboring cities and the deterioration of economic activities due to lack of activation of economic development plans (Rural villages suffer from a lack of interest in urban development within the regional spatial

Chilled ceilings systems offer potential for overall capital savings. The main aim of the present research is to investigate the thermal performance of the indirect contact closed circuit cooling tower, ICCCCT used with chilled ceiling, to gain a deeper knowledge in this important field of engineering which has been traditionally used in various industrial & HVAC systems. To achieve this study, experimental work were implemented for the ICCCCT use with chilled ceiling. In this study the thermal performances of closed wet cooling tower use with chilled ceiling is experimentally and theoretically investigated. Different experimental tests were conducted by varying the controlling parameters to investigate their effects

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob