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FILTRATION MODELING USING ARTIFICIAL NEURAL NETWORK (ANN)
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In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, with a
good degree of accuracy reaching 97.26, 95.92 and 86.43% respectively. These ANN models could be used as a support for workers in operating the filters in water treatment plants and to improve water treatment process. With the use of ANN, water systems will get more efficient, so reducing operation cost and improving the quality of the water produced.

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Publication Date
Fri Mar 07 2014
Journal Name
Annals Of Applied Biology
High throughput screening of rooting depth in rice using buried herbicide
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Abstract<p>Root research requires high throughput phenotyping methods that provide meaningful information on root depth if the full potential of the genomic revolution is to be translated into strategies that maximise the capture of water deep in soils by crops. A very simple, low cost method of assessing root depth of seedlings using a layer of herbicide (<styled-content style="fixed-case">TRIK</styled-content> or diuron) buried 25 or 30 cm deep in soil‐filled boxes of varying size is described that is suitable for screening hundreds or thousands of rice accessions in controlled environment conditions. Variation in cultivar sensitivity to the herbicide when injected into pots was detected but con</p> ... Show More
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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Engineering
Zirconium Sulfate as Catalyst for Biodiesel Production by Using Reactive Distillation
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Production of fatty acid esters (biodiesel) from oleic acid and 2-ethylhexanol using sulfated zirconia as solid catalyst for the production of biodiesel was investigated in this work.

 

       The parameters studied were temperature of reaction (100 to 130°C), molar ratio of alcohol to free fatty acid (1:1 to 3:1), concentration of catalyst (0.5 to 3%wt), mixing speed (500 to 900 rpm) and types of sulfated zirconia (i.e modified, commercial, prepared  catalyst according to literature and reused catalyst). The results show the best conversion to biodiesel was 97.74% at conditions of 130°C, 3:1, 2wt% and 650 rpm using modified catalyst respectively. Also, modified c

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Publication Date
Sat Dec 01 2018
Journal Name
Fuel
Biodiesel from batch and continuous oleic acid esterification using zeolite catalysts
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Publication Date
Mon Apr 01 2019
Journal Name
2019 4th Scientific International Conference Najaf (sicn)
Pneumatic Control System of Automatic Production Line Using SCADA Implement PLC
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Publication Date
Thu Jun 01 2023
Journal Name
Heliyon
Heterogeneously catalyzed transesterification reaction using waste snail shell for biodiesel production
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Biodiesel as an attractive energy source; a low-cost and green synthesis technique was utilized for biodiesel preparation via waste cooking oil methanolysis using waste snail shell derived catalyst. The present work aimed to investigate the production of biodiesel fuel from waste materials. The catalyst was greenly synthesized from waste snail shells throughout a calcination process at different calcination time of 2–4 h and temperature of 750–950 ◦C. The catalyst samples were characterized using X-Ray Diffraction (XRD), Brunauer-Emmett-Teller (BET), Energy Dispersive X-ray (EDX), and Fourier Transform Infrared (FT-IR). The reaction variables varying in the range of 10:1–30:1 M ratio of MeOH: oil, 3–11 wt% catalyst loading, 50–

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Publication Date
Mon Jun 26 2023
Journal Name
Asia-pacific Journal Of Chemical Engineering
Sustainable environment through using porous materials: A review on wastewater treatment
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Abstract<p>Porous materials play an important role in creating a sustainable environment by improving wastewater treatment's efficacy. Porous materials, including adsorbents or ion exchangers, catalysts, metal–organic frameworks, composites, carbon materials, and membranes, have widespread applications in treating wastewater and air pollution. This review examines recent developments in porous materials, focusing on their effectiveness for different wastewater pollutants. Specifically, they can treat a wide range of water contaminants, and many remove over 95% of targeted contaminants. Recent advancements include a wider range of adsorption options, heterogeneous catalysis, a new UV/H<sub>2</sub>O<j></j></p> ... Show More
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Publication Date
Tue Jan 01 2019
Journal Name
Spe/aapg/seg Asia Pacific Unconventional Resources Technology Conference
Optimizing the dispersion of coal fines using Sodium Dodecyl Benzene Sulfonate
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Coal fines are highly prone to be generated in all stages of Coal Seam Gas (CSG) production and development. These detached fines tend to aggregate, contributing to pore throat blockage and permeability reduction. Thus, this work explores the dispersion stability of coal fines in CSG reservoirs and proposes a new additive to be used in the formulation of the hydraulic fracturing fluid to keep the fines dispersed in the fluid. In this work, bituminous coal fines were tested in various suspensions in order to study their dispersion stability. The aggregation behavior of coal fines (dispersed phase) was analyzed in different dispersion mediums, including deionized-water, low and high sodium chloride solutions. Furthermore, the effect of Sodium

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Detection of Suicidal Ideation on Twitter using Machine Learning & Ensemble Approaches
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Suicidal ideation is one of the most severe mental health issues faced by people all over the world. There are various risk factors involved that can lead to suicide. The most common & critical risk factors among them are depression, anxiety, social isolation and hopelessness. Early detection of these risk factors can help in preventing or reducing the number of suicides. Online social networking platforms like Twitter, Redditt and Facebook are becoming a new way for the people to express themselves freely without worrying about social stigma. This paper presents a methodology and experimentation using social media as a tool to analyse the suicidal ideation in a better way, thus helping in preventing the chances of being the victim o

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Publication Date
Mon Dec 14 2020
Journal Name
2020 13th International Conference On Developments In Esystems Engineering (dese)
Anomaly Based Intrusion Detection System Using Hierarchical Classification and Clustering Techniques
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With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

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Publication Date
Fri Mar 01 2024
Journal Name
Heliyon
Using unsafe traditional practices by Iraqi mothers to treat newborns' problems
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