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Reaction kinetic model for a recent co-produced water treatment technology

Journal of Environmental Sciences 2011年第3期23卷 360-365页

作者： abdulwahab m ali tuwati mark A.Bentley Chemical & Petroleum Engineering University of Wyoming

With the increasing demand for fossil based energy and implementation of progressively strict environmental pollution control standards, treatment of a large amount of co-produced waters （CPWs） from fossil based energy production has become increasingly important. Removal of bicarbonate with H2SO4 has been recently studied as a simple and cost-effective method to decrease the alkalinity of CPWs. The present work investigates the kinetics of the reaction between H2SO4 and NaHCO3, which could provide the base for scaling-up the CPW treatment technology. Based on the measured quantity change of the CO2 gas generated from the reaction between H2SO4 and NaHCO3 with time under specified initial reaction conditions, the reaction orders with respect to H2SO4 and NaHCO3 were determined. Experiments were also conducted within the temperature of 15-30℃ to find various global rate coefficients of the reaction to calculate the activation energy and the pre-exponential factor of the empirical Arrhenius form of the bicarbonate removal reaction, which are 197.7 kJ/mol and 3.13 × 1034 （mol-3.7 ×L3.7 ×sec^-1 ）, respectively.

关键词： fossil fuels water wastewater alkalinity bicarbonate

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Automated Speech Recognition System to Detect Babies’ Feelings through Feature Analysis

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Computers, materials & Continua 2022年第11期73卷 4349-4367页

作者： Sana Yasin Umar Draz Tariq ali Kashaf Shahid Amna Abid Rukhsana Bibi muhammad Irfan mohammed A.Huneif Sultan A.Almedhesh Seham m.Alqahtani Alqahtani abdulwahab mohammed Jamaan Alzahrani Dhafer Batti Alshehri Alshehri ali Abdullah Saifur Rahman Faculty of Computing University of OkaraOkara57000Pakistan Department of Computer Science University of SahiwalSahiwal57000PunjabPakistan Computer Science Department COMSATS University IslamabadLahore Campus57000Pakistan Department of Computer Science CUISahiwal CampusSahiwal57000Pakistan Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Pediatric Department Medical CollegeNajran University Saudi ArabiaNajran61441Saudi Arabia Consultant of ORL&HNs and Facial Plastic Surgery College of MedicineNajran University Saudi ArabiaNajran61441Saudi Arabia

Diagnosing a baby’s feelings poses a challenge for both doctors and parents because babies cannot explain their feelings through expression or *** the emotions of babies and their associated expressions during different sensations such as hunger,pain,etc.,is a complicated *** infancy,all communication and feelings are propagated through cryspeech,which is a natural *** clinical methods can be used to diagnose a baby’s diseases,but nonclinical methods of diagnosing a baby’s feelings are *** such,in this study,we aimed to identify babies’feelings and emotions through their cry using a nonclinical *** in the cry sound can be identified using our method and used to assess the baby’s *** considered the frequency of the cries from the energy of the *** feelings represented by the infant’s cry are judged to represent certain sensations expressed by the child using the optimal frequency of the recognition of a real-world audio *** used machine learning and artificial intelligence to distinguish cry tones in real time through feature *** experimental group consisted of 50%each male and female babies,and we determined the relevancy of the results against different *** application produced real-time results after recognizing a child’s cry *** novelty of our work is that we,for the first time,successfully derived the feelings of young children through the cry-speech of the child,showing promise for end-user applications.

关键词： Cry-to-speak machine learning artificial intelligence cry speech detection babies

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Forecasting mental Stress Using machine Learning Algorithms

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Computers, materials & Continua 2022年第9期72卷 4945-4966页

作者： Elias Hossain abdulwahab Alazeb Naif Almudawi Sultan Almakdi mohammed Alshehri m.Gazi Golam Faruque Wahidur Rahman Department of Software Engineering Daffodil UniversityDhakaBangladesh Collage of Computer Science and Information System University of NajranNajranSaudi Arabia Department of Computer Science and Engineering Khwaja Yunus Ali UniversitySirajganj 6751Bangladesh

Depression is a crippling affliction and affects millions of individuals around the *** general,the physicians screen patients for mental health disorders on a regular basis and treat patients in collaboration with psychologists and other mental health experts,which results in lower costs and improved patient ***,this strategy can necessitate a lot of buy-in from a large number of people,as well as additional training and logistical ***,utilizing the machine learning algorithms,patients with depression based on information generally present in a medical file were analyzed and *** methodology of this proposed study is divided into six parts:Proposed Research Architecture(PRA),Data Pre-processing Approach(DPA),Research Hypothesis Testing(RHT),Concentrated Algorithm Pipeline(CAP),Loss Optimization Stratagem(LOS),and model Deployment Architecture(mDA).The Null Hypothesis and Alternative Hypothesis are applied to test the *** addition,Ensemble Learning Approach(ELA)and Frequent model Retraining(FmR)have been utilized for optimizing the loss ***,the Features Importance Interpretation is also delineated in this *** forecasts could help individuals connect with expert mental health specialists more quickly and *** to the findings,71%of people with depression and 80%of those who do not have depression can be appropriately *** study obtained 91%and 92%accuracy through the Random Forest(RF)and Extra Tree *** after applying the Receiver operating characteristic(ROC)curve,79%accuracy was found on top of RF,81%found on Extra Tree,and 82%recorded for the eXtreme Gradient Boosting(XGBoost)***,several factors are identified in terms of predicting depression through statistical data *** the additional effort is needed to develop a more accurate model,this model can be adjustable in the healthcare sector for diagnosing depression.

关键词： Depression analysis mental health machine learning model deployment XGBoost ROC-AUC

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A Selection Study for Sanitary Landfill Site at Basra City, South of Iraq

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Journal of Life Sciences 2016年第4期10卷 198-202页

作者： Wathiq A. A1-Ramdhan mahmood S. Thamir Assaad F. Hamza abdulwahab A. Sultan ali G. Katea'a Najem A1-Dean A. Al-hajaj Ayad K. Jirri Ekhlass B. Zubery Southern Technical University Technical Institute of Basra Environmental Pollution Research Unit Basra Iraq Southern Technical University University Presidency Basra Iraq Iraqi Ports Company Basra Iraq

The selection study for a sanitary landfill site at Basra city （south of lraq） indicated to choose Al-Barjesia region at chwabedian area which belong to AI-Zubair directorate, using global positioning system （GPS）. The measured latitude and longitude axes of this area are 30° 25.4＇ north and 47° 29＇ west. It is located at a distance of about 25 km straight line from the city center. The calculated elevation range of the chwabedian site was obtained to be 5-10 m above sea level, while the depth ofplutonic water in the landfill site is range from 15-25 m. The measured permeability for this site was about 0.75-0.84 mma/min. The evaluation of soil components percentage in the suggested site was listed in table 1, as examined by the international constructional laboratory, at Basra/Iraq. A primarily modern design for chwabedian sanitary landfill was projected and sketched in figure 3.

关键词： Landfill site solid waste management leachate.

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