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Atan regularized for the high dimensional Poisson regression model
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Variable selection in Poisson regression with high dimensional data has been widely used in recent years. we proposed in this paper using a penalty function that depends on a function named a penalty. An Atan estimator was compared with Lasso and adaptive lasso. A simulation and application show that an Atan estimator has the advantage in the estimation of coefficient and variables selection.

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Publication Date
Mon Jun 05 2023
Journal Name
Al-khwarizmi Engineering Journal
Determination of the Optimum Conditions for Removal of Congo Red Dye by Peroxidase Enzyme Plant
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The pollution producing from textile industries effluents is growing since the years, due to at discharged lots of it in water without treatment. The resulting effluent is colourful, highly toxic, and poses a significant environmental hazard. This problem can be solved by using enzymic biological treatment, where the Congo red dye was used with concentrations (100,200,300,500) mg /L, pH values (3,4,5,6,7,8), and variable temperatures (25,35,45)°C, the best removal of Congo red (CR) dye  under optimum conditions for degradation was at  concentration of 100 mg/L, at (pH 6, 25 °C) with efficiency of 99.85 % using the peroxidase enzyme extracted from red radish plant, while the removal percentage decreased when increase dye concentration

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Measuring the Critical Success Factors for Total Quality Management Applications (Compared research of many colleges)
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ABSTRACT

This research aim to measure the critical success factors for total quality management applications, in order to know the key and important role played by these factors at applying the total quality management through a comparative study conducted in a number of a private colleges.

The research problem posed a set of questions, the most important ones are: Are the colleges (sample of research) aware of the critical success factors at applying the total quality management? What is the availability of the critical success factors at the work of the colleges (sample of research)? 

What are the critical success factors in the work of the researc

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Publication Date
Thu Jan 01 2026
Journal Name
Procedia Computer Science
Revolutionizing Higher Education by Harnessing the Power of AI and Big Data for Sustainable Education
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The integration of Artificial Intelligence with Big Data Analytics is one of the most groundbreaking developments that could change the face of educational sustainability in higher education.. Using AI and Big Data technologies not only makes the educational process more efficient but also changes the way people learn and thus opens the door for educators and institutions to make decisions based on the data. The document imparts the manner that the use of AI and the digital revolution can remove student requirements, execute the efficiency of the curriculum, and acquire the balance of educational resources through a majority of instances and the latest developments in that field. Furthermore, the paper, along with the issues of morality wit

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Publication Date
Tue Jul 11 2017
Journal Name
The 39th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc'17)
Higuchi fractal dimension of the electroencephalogram as a biomarker for early detection of Alzheimer's disease
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It is widely accepted that early diagnosis of Alzheimer's disease (AD) makes it possible for patients to gain access to appropriate health care services and would facilitate the development of new therapies. AD starts many years before its clinical manifestations and a biomarker that provides a measure of changes in the brain in this period would be useful for early diagnosis of AD. Given the rapid increase in the number of older people suffering from AD, there is a need for an accurate, low-cost and easy to use biomarkers that could be used to detect AD in its early stages. Potentially, the electroencephalogram (EEG) can play a vital role in this but at present, no reliable EEG biomarker exists for early diagnosis of AD. The gradual s

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Publication Date
Sun Jun 27 2010
Journal Name
All Days
Optimal Field Development Through Infill Drilling for the Main Pay in South Rumaila Oil Field
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Abstract<p>Study of determining the optimal future field development has been done in a sector of South Rumaila oil field/ main pay. The aspects of net present value (economic evaluation) as objective function have been adopted in the present study.</p><p>Many different future prediction cases have been studied to determine the optimal production future scenario. The first future scenario was without water injection and the second and third with 7500 surface bbls/day and 15000 surface bbls/day water injection per well, respectively. At the beginning, the runs have been made to 2028 years, the results showed that the optimal future scenario is continuing without water in</p> ... Show More
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Publication Date
Thu Jul 01 2021
Journal Name
Solar Energy
A new approach for employing multiple PCMs in the passive thermal management of photovoltaic modules
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Publication Date
Mon Mar 01 2021
Journal Name
Journal Of Management In Engineering
Identifying Pertinent Indicators for Assessing and Fostering Diversity, Equity, and Inclusion of the Construction Workforce
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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
Characterization of a novel pathway for xanthene degradation by the engineered strain Sphingobium yanoikuyae B1DR
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Polyaromatic hydrocarbons (PAHs) are a group of aromatic compounds that contain at least two rings. These compounds are found naturally in petroleum products and are considered the most prevalent pollutants in the environment. The lack of microorganism capable of degrading some PAHs led to their accumulation in the environment which usually causes major health problems as many of these compounds are known carcinogens. Xanthene is one of the small PAHs which has three rings. Many xanthene derivatives are useful dyes that are used for dyeing wood and cosmetic articles. However, several studies have illustrated that these compounds have toxic and carcinogenic effects. The first step of the bacterial degradation of xanthene is conducted by d

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Review of the Mechanisms for Preventing, Diagnosing, and Treatment of Pipe Sticking in Drilling Operations
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Stuck pipe is a prevalent and costly issue in drilling operations, with the potential to cost the petroleum industry billions of dollars annually. To reduce the likelihood of this issue, efforts have been made to identify the causes of stuck pipes. The main mechanisms that cause stuck pipes include drill cutting of the formation, inappropriate hole-cleaning, wellbore instability, and differential sticking forces, particularly in highly deviated wellbores. The significant consequences of a stuck pipe include an increase in well costs and Non-Productive Time (NPT), and in the worst-case scenario, the loss of a wellbore section and down-hole equipment, or the need to sidetrack, plug, or abandon the well. This paper provides a comprehensive

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