The aims of this study are to measure the defect rate and analyze the problems of production of ready concrete mixture plant by using Six Sigma methodology which is a business strategy for operations improvement depending basically on the application of its sub-methodology DMAIC improvement cycle and the basic statistical tools where the process sigma level of concrete production in the case study was 2.41 σ.

The present work presents a new experimental study of the enhancement of turbulent
convection heat transfer inside tubes for combined thermal and hydrodynamic entry length of one
popular “turbulator” (twisted tape with width slightly less than internal tube diameter) inserted for
fire tube boilers. Cylindrical combustion chamber was used to burn (1.6 to 7kg/h) fuel oil #2 to
deliver hot gases with ranges of Reynolds number (10500 to 21700), and (11400 to 24150) for both
empty and inserted tube respectively.A uniform wall temperature technique was used by keeping
approximately constant water temperature difference (25ºC) between inlet and exit cooling water in
parallel flow shell and tube heat exchanger. The test

This work presents a computer studying to simulate the charging process of a dust grain immersed in plasma with negative ions. The study based on the discrete charging model. The model was developed to take into account the effect of negative ions on charging process of dust grain.
The model was translated to a numerical calculation by using computer programs. The program of model has been written with FORTRAN programming language to calculate the charging process for a dust particle in plasma with negative ion, the time distribution of a dust charge, number charge equilibrium and charging time for different value of ηe (ratio of number density of electron to number density of positive ion).

The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.

Motifs template is the input for many bioinformatics systems such codons finding, transcription, transaction, sequential pattern miner, and bioinformatics databases analysis. The size of motifs arranged from one base up to several Mega bases, therefore, the typing errors increase according to the size of motifs. In addition, when the structures motifs are submitted to bioinformatics systems, the specifications of motifs components are required, i.e. the simple motifs, gaps, and the lower bound and upper bound of each gap. The motifs can be of DNA, RNA, or Protein. In this research, a motif parser and visualization module is designed depending on a proposed a context free grammar, CFG, and colors human recognition system. GFC describes the m

The density-based spatial clustering for applications with noise (DBSCAN) is one of the most popular applications of clustering in data mining, and it is used to identify useful patterns and interesting distributions in the underlying data. Aggregation methods for classifying nonlinear aggregated data. In particular, DNA methylations, gene expression. That show the differentially skewed by distance sites and grouped nonlinearly by cancer daisies and the change Situations for gene excretion on it. Under these conditions, DBSCAN is expected to have a desirable clustering feature i that can be used to show the results of the changes. This research reviews the DBSCAN and compares its performance with other algorithms, such as the tradit