Furfural is one of the one of pollutants in refinery industrial wastewaters. In this study advanced oxidation process using UV/H2O2 was investigated for furfural degradation in synthetic wastewater. The results from the experimental work showed that the degradation of furfural decreases as its concentration increases, reaching 100% at 50mg/l furfural concentration and increasing the concentration of H2O2 from 250 to 500 mg/l increased furfural removal from 40 to 60%.The degradation of furfural reached 100% after 90 min exposure time using two UV lamps, where it reached 60% using one lamp after 240 min exposure time. The rate of furfural degradation k increased at the pH and initial concentration of furfural decreased, but different H2O2concentrations indicated no significant effects on the reaction rate. UV/H2O2 process is effective for furfural degradation in wastewater at neutral pH where the disposal of such effluents will be within the environmental limitations.
Abstract
This study was conducted by using soil map of LD7 project to interpret the
distribution and shapes of map units by using the index of compaction as an
index of map unit shape explanation. Where there were wide and varied
ranges of compaction index of map units, where the maximum value was
0.892 for MF9 map unit and the lower value was 0.010 for same map unit.
MF9 has wide range appearance of index of compaction after those indices
were statistically analyzed by using cluster analysis to group the similar
ranges together to ease using their values, so the unit MF9 was considered as
key map unit that appears in the soils of LD7 project which may be used to
expect another map units existence in area of
Inflammatory response had a role in cancer progression, presence of noticeable inflammation within the tumor and its margin may play an important prognostic role in colorectal carcinoma.
يهدف هذا العمل الى بيان طبيعة العلاقة بين الادارة بالتجوال والتجديد الاستراتيجي ، ومدى تأثير المتغير المستقل في المتغير التابع. تضمنت فقرات الاستبانة بوصفه الأداة الرئيسة لجمع البيانات ثلاث جوانب اساسية، تضمن الاول البيانات الشخصية للمستجيبين، فيما تضمن الجانب الثاني الفقرات الخاصة بمتغير الادارة بالتجوال من خلال خمسة ابعاد، فيما اشتمل الجانب الثالث على فقرات التجديد الاستراتيجي عبر تناول اربعة ابعاد. ي
... Show MoreThis work aims to show the nature of the relationship between management by walking around (the independent variable) and strategic renewal (the dependent variable), as well as it shows the effect of the independent variable on the dependent variable. Questionnaire items were considered the main tool for data collection by three basic aspects. The first involved the personal data of the respondents, while the second included items related to management by walking in five dimensions, and the third is strategic renewal items by addressing four dimensions. The tourism sector, while the community has six Excellent grade hotels was taken into account in this wor
... Show MoreNeural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.
Shadow detection and removal is an important task when dealing with color outdoor images. Shadows are generated by a local and relative absence of light. Shadows are, first of all, a local decrease in the amount of light that reaches a surface. Secondly, they are a local change in the amount of light rejected by a surface toward the observer. Most shadow detection and segmentation methods are based on image analysis. However, some factors will affect the detection result due to the complexity of the circumstances. In this paper a method of segmentation test present to detect shadows from an image and a function concept is used to remove the shadow from an image.
Water/oil emulsion is considered as the most refractory mixture to separate because of the interference of the two immiscible liquids, water and oil. This research presents a study of dewatering of water / kerosene emulsion using hydrocyclone. The effects of factors such as: feed flow rate (3, 5, 7, 9, and 11 L/min), inlet water concentration of the emulsion (5%, 7.5%, 10%, 12.5%, and 15% by volume), and split ratio (0.1, 0.3, 0.5, 0.7, and 0.9) on the separation efficiency and pressure drop were studied. Dimensional analysis using Pi theorem was applied for the first time to model the hydrocyclone based on the experimental data. It was shown that the maximum separation efficiency; at split ratio 0.1, was 94.3% at 10% co
... Show MoreCompressing the speech reduces the data storage requirements, leading to reducing the time of transmitting the digitized speech over long-haul links like internet. To obtain best performance in speech compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry.The MCT bases functions are derived from GHM bases function using 2D linear convolution .The fast computation algorithm methods introduced here added desirable features to the current transform. We further assess the performance of the MCT in speech compression application. This paper discusses the effect of using DWT and MCT (one and two dimension) on speech compression. DWT and MCT performances in terms of comp
... Show MoreDiabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att
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