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Solid waste recycling and management cost optimization algorithm
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Solid waste is a major issue in today's world. Which can be a contributing factor to pollution and the spread of vector-borne diseases. Because of its complicated nonlinear processes, this problem is difficult to model and optimize using traditional methods. In this study, a mathematical model was developed to optimize the cost of solid waste recycling and management. In the optimization phase, the salp swarm algorithm (SSA) is utilized to determine the level of discarded solid waste and reclaimed solid waste. An optimization technique SSA is a new method of finding the ideal solution for a mathematical relationship based on leaders and followers. It takes a lot of random solutions, as well as their outward or inward fluctuations, to find the optimal solution. This method also included multiple adaptive and random variables to guarantee that the solution space was explored and used in various optimization tasks. When all criteria are considered, the results of this study show that the SSA is efficient for least-distance path allocation. The simulation findings reveal a significant improvement over the well-known particle swarm optimization (PSO) algorithm, with recycling and disposal costs decreasing by 10% to 30%.

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Publication Date
Sun Apr 05 2026
Journal Name
Al–bahith Al–a'alami
THE ISSUES OF YOUTH IN THE TALK SHOWS IN THE IRAQI SATELLITE CHANNELS:: (An Analytical Study of the Shabab wa Banat Program at Al-Sumaria TV Channel and of the Hala Shabab at Al-Iraqia TV Channel) (A Research Drawn from a Master’s Thesis)
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The purpose of this research is to identify the youth issues in Talk Shows in the Iraqi satellite channels via monitoring a sample of episodes of the Talk Shows  episodes which are concerned and analyzed the youth issues in the Iraqi satellite channels, namely, «Hala Shabab Program» at Al-Iraqia satellite Channel and «Shabab wa Banat Program» at Al-Sumaria satellite Channel by recording and re-watching them again. This research is classified as one of descriptive researches. The survey method was adopted in this study.

For this purpose, the researcher prepared an analysis form. The researcher de

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Publication Date
Sat Oct 03 2020
Journal Name
International Journal Of Diabetes In Developing Countries
The efficacy of once-daily liraglutide as an add-on to oral antidiabetic agents on weight reduction and glycemic control in obese patients with inadequately controlled type 2 diabetes: a retrospective analysis in relation to liraglutide dose escalation within a 7-month treatment period
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Background This study aimed to evaluate the efficacy of once-daily liraglutide as an add-on to oral antidiabetics (OADs) on glycemic control and body weight in obese patients with inadequately controlled type 2 diabetes (T2D). Methods A total of 27 obese T2D patients who received 7 months (0.6 mg/day for the first month, 1.2 mg/day for 3 months, and 1.8 mg/day for 3 months) of liraglutide treatment as an add-on to OADs were included. Data on body weight (kg), fasting plasma glucose (FPG, mg/dL), postprandial glucose (PPG, mg/dL), and HbA1c (%), were recorded. Results Liraglutide doses of 1.2 mg/day and 1.8 mg/day were associated with significant decreases in body weight (by 8.0% and 11.9%, respectively, p < 0.01 for each) and HbA1c (by 20.0

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Optimized Artificial Neural network models to time series
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        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

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Publication Date
Sun Jan 01 2023
Journal Name
8th Engineering And 2nd International Conference For College Of Engineering – University Of Baghdad: Coec8-2021 Proceedings
Optimal characteristics of wind turbine to maximize capacity factor
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The capacity factor is the main factor in assessing the efficiency of wind Turbine. This paper presents a procedure to find the optimal wind turbine for five different locations in Iraq based on finding the highest capacity factor of wind turbine for different locations. The wind data for twelve successive years (2009-2020) of five locations in Iraq are collected and analyzed. The longitudes and latitudes of the candidate sites are (44.3661o E, 33.3152o N), (47.7738o E, 30.5258o N), (45.8160o E, 32.5165o N), (44.33265o E, 32.0107o N) and (46.25691o E, 31.0510o N) for Baghdad, Basrah, Al-Kut, Al-Najaf, and Al-Nasiriyah respectively. The average wind velocity, standard deviation, Weibull shape and scale factors, and probability density functi

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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
THE EFFECT OF CUTOFF WALL ANGLE ON SEEPAGE UNDER DAMS
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Flow of water under concrete dams generates uplift pressure under the dam, which may cause the dam to function improperly, in addition to the exit gradient that may cause piping if exceeded a safe value. Cutoff walls usually used to minimize the effect of flow under dams. It is required to
1)minimize the flow quantity to conserve water in the reservoir, it is also required to
2)minimize the uplift pressure under the dam to maintain stability of the dam, and it is required to

3) minimize the exit gradient to prevent quick condition to occur at the toe of the dam where piping may occur and may cause erosion of the soil. Varying the angle of cutoff walls affects its influence on the factors aforementioned that are required to

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Publication Date
Wed Feb 01 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Engineering
Effect of laser process an inclined surface cutting of mild steel then analysis data statistically by RSM
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The regression analysis process is used to study and predicate the surface response by using the design of experiment (DOE) as well as roughness calculation through developing a mathematical model. In this study; response surface methodology and the particular solution technique are used. Design of experiment used a series of the structured statistical analytic approach to investigate the relationship between some parameters and their responses. Surface roughness is one of the important parameters which play an important role. Also, its found that the cutting speed can result in small effects on surface roughness. This work is focusing on all considerations to make interaction between the parameters (position of influenc

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Publication Date
Sun Jan 01 2023
Journal Name
International Conference On Scientific Research &amp; Innovation (icsri 2022)
Investigating the capability of MCM-41 nanoparticle for COD removal from Iraqi petroleum refinery wastewater
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Publication Date
Fri Sep 01 2023
Journal Name
Journal Of Engineering
Studying Sustainable Concrete Block Efficiency Production: A Review
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Worldwide, enormous amounts of waste cause major environmental issues, including scrap tires and plastic, and large waste, a consequence of the demolition of buildings, including crushed concrete, crushed clay bricks, and crushed thermo-stone. From that point, it’s possible to consider that the recycling processes for these materials and using them in the manufacturing field will reduce the adverse effects on the environment of these wastes and the consumption of natural resources. Sustainable concrete blocks can be considered as one of the products produced by using these materials as partial volume replacement of the coarse, fine aggregate, or cement content, considering their dry density, workability, absorption, co

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Publication Date
Wed Mar 01 2023
Journal Name
Journal Of Engineering
Recycled Concrete Aggregated for the use in Roller Compacted Concrete: A Literature Review
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The using of recycled aggregates from construction and demolition waste (CDW) can preserve natural aggregate resources, reduce the demand for landfill, and contribute to a sustainable built environment. Concrete demolition waste has been proven to be an excellent source of aggregates for new concrete production. At a technical, economic, and environmental level, roller compacted concrete (RCC) applications benefit various civil construction projects. Roller Compacted Concrete (RCC) is a homogenous mixture that is best described as a zero-slump concrete placed with compacting equipment, uses in storage areas, dams, and most often as a basis for rigid pavements. The mix must be sufficiently dry to support

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