Introduction: Although soap industry is known from hundreds of years, the development accompanied with this industry was little. The development implied the mechanical equipment and the additive materials necessary to produce soap with the best specifications of shape, physical and chemical properties. Objectives: This research studies the use of vacuum reactive distillation VRD technique for soap production. Methods: Olein and Palmitin in the ratio of 3 to 1 were mixed in a flask with NaOH solution in stoichiometric amount under different vacuum pressures from -0.35 to -0.5 bar. Total conversion was reached by using the VRD technique. The soap produced by the VRD method was compared with soap prepared by the reaction - only method which is known as the conventional method. The two kinds of soap were compared in yield, the reaction temperature, the volume of the co-product liquid and its composition, FTIR analysis, the density and the time of production. Results: It was shown that the yield of soap using VRD was 2.45 times that produced by the reaction - only method. The process temperature was reduced 0.11 times. The volume of the co-product liquid was reduced 95.76% consisting of water only. The analyses of FTIR were compared with a commercial soap regarded as a standard and they showed identical functional groups. Very little difference in density was recorded. The time of production was shorter than the conventional method giving another priority to the VRD method. Conclusion: It was beneficial to adopt VRD method in soap production in batch mode. Continuous mode of soap production using VRD method may be investigated in future study.
The study showed flow rates and the interaction between the settlements served by applying the model of gravity theory to measure depending on the number of the population between city Najaf and the rest of the other settlements served and using three functions of disability, time and cost, as recorded an increase in the interaction index with some settlements like them Kufa, Abbasid and Manathira, while the indicator contrast was in other settlements, either when the application of the gravity model depending on trips and socio-economic characteristics accuracy rate was more pronounced.
Because of the experience of the mixture problem of high correlation and the existence of linear MultiCollinearity between the explanatory variables, because of the constraint of the unit and the interactions between them in the model, which increases the existence of links between the explanatory variables and this is illustrated by the variance inflation vector (VIF), L-Pseudo component to reduce the bond between the components of the mixture.
To estimate the parameters of the mixture model, we used in our research the use of methods that increase bias and reduce variance, such as the Ridge Regression Method and the Least Absolute Shrinkage and Selection Operator (LASSO) method a
... Show MoreThis world is moving towards knowledge economy which basically depends on knowledge and information. So, the economic units need to develop its financial reporting system which helps to provide useful information in timeliness for investors in accordance with the requirements of the knowledge economy and meets the needs of those investors. This research aims to revealing the reflects of knowledge economy on the approaches of financial reporting and suggesting a financial reporting model in the environment of knowledge economy, depending on combining the value approach with the events approach using database and communication technology and providing useful accounting information for all users regardless of
... Show MoreIn this paper, we will provide a proposed method to estimate missing values for the Explanatory variables for Non-Parametric Multiple Regression Model and compare it with the Imputation Arithmetic mean Method, The basis of the idea of this method was based on how to employ the causal relationship between the variables in finding an efficient estimate of the missing value, we rely on the use of the Kernel estimate by Nadaraya – Watson Estimator , and on Least Squared Cross Validation (LSCV) to estimate the Bandwidth, and we use the simulation study to compare between the two methods.
The study presents the test results of stabilizing gypseous soil embankment obtained from
Al- Faluja university Campus at Al-Ramady province. The laboratory investigation was divided
into three phases, The physical and chemical properties, the optimum liquid asphalt (emulsion)
requirements (which are manufactured in Iraq) were determined by using one dimensional
unconfined compression strength test.in the first phase , The optimum fluid content was 11%
(6% of emulsion with 5% water content).. At phase two, the effect of Aeration technique was
investigated using both direct shear and permeability test. At phase three for the case of static
load , the pure soil embankment model under dry test condition was investigated
In this paper, a Sokol-Howell prey-predator model involving strong Allee effect is proposed and analyzed. The existence, uniqueness, and boundedness are studied. All the five possible equilibria have been are obtained and their local stability conditions are established. Using Sotomayor's theorem, the conditions of local saddle-node and transcritical and pitchfork bifurcation are derived and drawn. Numerical simulations are performed to clarify the analytical results
The paper shows how to estimate the three parameters of the generalized exponential Rayleigh distribution by utilizing the three estimation methods, namely, the moment employing estimation method (MEM), ordinary least squares estimation method (OLSEM), and maximum entropy estimation method (MEEM). The simulation technique is used for all these estimation methods to find the parameters for the generalized exponential Rayleigh distribution. In order to find the best method, we use the mean squares error criterion. Finally, in order to extract the experimental results, one of object oriented programming languages visual basic. net was used
In this paper, previous studies about Fuzzy regression had been presented. The fuzzy regression is a generalization of the traditional regression model that formulates a fuzzy environment's relationship to independent and dependent variables. All this can be introduced by non-parametric model, as well as a semi-parametric model. Moreover, results obtained from the previous studies and their conclusions were put forward in this context. So, we suggest a novel method of estimation via new weights instead of the old weights and introduce
Paper Type: Review article.
another suggestion based on artificial neural networks.