Depletion of fossil fuel is one of the main reasons why the bioethanol has become popular. It is a renewable energy source. In order to meet the great demand of bioethanol, it is best that the bioethanol production is from cheap raw materials. Since the golden shower fruit is not being utilized and is considered as waste material, hence, this study was conducted to make use of the large volume of the residue as feedstock to test its potential for bioethanol extraction.The main goal of this study is to obtain the most volume of bioethanol from the golden shower fruit liquid residue by the factors, days of fermentation (3, 5, and 7 days) and sugar concentration (15, 20 and 25 brix) of the liquid residue. Also, part of the study is to compute the cost of production in extracting bioethanol from the golden shower fruit. Each treatment was replicated three (3) times. The Two-Factorial Analysis of Variance (ANOVA) of the Complete Randomized Design (CRD) was used to analyze the treatments. Treatments means were compared using the Duncan’s Multiple Range Test (DMRT).
Abstract:
The researcher shed light on a diet in Iraq before 2003 became in this period. And how the ration card has a variety of vocabulary and cover the need of the population of commodities and have a key role in saving Iraq from a real crisis in the period of economic siege, especially in light of the State's direction to support the agricultural sector, which in that period able to fill half of the market needs of food the basic. As well as providing strategic storage at the Ministry of Commerce enough for six months But after the events of 2003 and the crises that hit the country and the unstable security situation began to rise voices calling for reform of the ration card system as a system that is a burden on the
... Show MoreThe purpose of this study is to examine the moderating role of business environment on the relationship between Entrepreneurial Skills (ES) and business performance of Small Business (SB) in Iraq, Baghdad. This study aims to resolve the inconsistencies found in the contemporary literature regarding the relationship between ES and business performance. Questionnaire using a 5-point Likert scale was adopted from previous work to ascertain the responses of the respondents. Survey research design was adopted, and self-administered questionnaires were used to collect the data from small business owners in 9 districts in Baghdad the capital of Iraq. The analysis was conducted using SPSS version 23.0. The direct relationship and hierarchical regre
... Show MoreGlobal warming has a serious impact on the survival of organisms. Very few studies have considered the effect of global warming as a mathematical model. The effect of global warming on the carrying capacity of prey and predators has not been studied before. In this article, an ecological model describing the relationship between prey and predator and the effect of global warming on the carrying capacity of prey was studied. Moreover, the wind speed was considered an influencing factor in the predation process after developing the function that describes it. From a biological perspective, the nonnegativity and uniform bounded of all solutions for the model are proven. The existence of equilibria for the model and its local stability is inves
... Show Moren this research, several estimators concerning the estimation are introduced. These estimators are closely related to the hazard function by using one of the nonparametric methods namely the kernel function for censored data type with varying bandwidth and kernel boundary. Two types of bandwidth are used: local bandwidth and global bandwidth. Moreover, four types of boundary kernel are used namely: Rectangle, Epanechnikov, Biquadratic and Triquadratic and the proposed function was employed with all kernel functions. Two different simulation techniques are also used for two experiments to compare these estimators. In most of the cases, the results have proved that the local bandwidth is the best for all the types of the kernel boundary func
... Show MoreThe reserve estimation process is continuous during the life of the field due to risk and inaccuracy that are considered an endemic problem thereby must be studied. Furthermore, the truth and properly defined hydrocarbon content can be identified just only at the field depletion. As a result, reserve estimation challenge is a function of time and available data. Reserve estimation can be divided into five types: analogy, volumetric, decline curve analysis, material balance and reservoir simulation, each of them differs from another to the kind of data required. The choice of the suitable and appropriate method relies on reservoir maturity, heterogeneity in the reservoir and data acquisition required. In this research, three types of rese
... Show MoreThe downhole flow profiles of the wells with single production tubes and mixed flow from more than one layer can be complicated, making it challenging to obtain the average pressure of each layer independently. Production log data can be used to monitor the impacts of pressure depletion over time and to determine average pressure with the use of Selective Inflow Performance (SIP). The SIP technique provides a method of determining the steady state of inflow relationship for each individual layer. The well flows at different stabilized surface rates, and for each rate, a production log is run throughout the producing interval to record both downhole flow rates and flowing pressure. PVT data can be used to convert measured in-situ rates
... Show MoreThe method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par
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