bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Understanding of Artificial Bee Colony Algorithm from the Perspective of Computation and Applied Mathematics: A Comparative Study
Authors: Mohammed Ali Hassan , Yasir Asmahan Abed 
Published: November 2019

Abstract
In the recent past, one of the swarm-based algorithms that have been introduced is Artificial Be Colony (ABC) algorithms. The role of ABC lies in the stimulation of honeybee swarms’ intelligent foraging behavior. This study applied the ABC algorithm toward large numerical test function optimization. Also, the results were compared with those that had been reported by experimental studies employing evolution strategies, differential evolution algorithm, particle swarm optimization algorithm, and genetic algorithm. From the findings, the study established that ABC exhibits superior performance compared to population-based algorithms, with other situations also witnessing the algorithm’s performance likened to or similar to the population-based algorithms. The factor that explained the superiority of the ABC algorithm was that it employs fewer control parameters.
Examining a Round Vessel Relative to the Impact Posed By Porous Media and Constant Wall Permeability on the Creeping Flow: In Relation to Computational and Applied Mathematics Techniques
Authors: Hamil Shahed Ali , Majeed Abdulrahman H. 
Published: November 2019

Abstract
In this study, the main aim was to determine the impact of the parameters of porous media and constant wall permeability on the round vessel’s creeping flow. To determine the exact solution, the study employed the inverse technique. Also, the mathematical expression for leakage flux, flow rate, pressure distribution, wall shear stress, velocity components, and stream function were used to understand the flow behavior. The motivation was to determine how flow properties exist relative to porous media and wall permeability. From the findings, the study established that there is a reduction in fluid velocity when the permeability of the porous medium is low. The maximum permeation rate was recorded at 84% and was obtained following high osmotic pressure drop and increased wall permeability. Similarly, the porous media’s state of porosity did not affect the amount of permeable fluid, as well as leakage flow. Rather, these parameters dependent on the nature of constant wall permeability.
Applying Matching Coefficients in the 2D Stick-Model to Classify Human Motion: An Experimental Study in Applied Mathematics
Authors: Kadhum Shatha Abdul-Hussein 
Published: November 2019

Abstract
Recently, different techniques have been employed toward motion estimation. Some of these approaches include image based, model based, and silhouette based estimations. Despite their promising nature and outcomes, it remains notable that the techniques rely on motion data quality before producing optimal classification with precision and accuracy. Also, most of the existing algorithms have been complex relative to motion estimation, making interpretation challenging. Therefore, this study strived to respond to these dilemmas by modeling simple human motions through which various patterns of activity behavior could be recognized and aid in classification analyses. Three body components were used to develop the framework. These components included the lower body (LB), the upper body (UB), and the backbone (BB). Indeed, it was through these parts that a simple 2D human stick figure was formed. It is also notable that upon completion, the motion estimation mathematical model was compared to the performance of real motion phases to determine its efficiency in classification. The classifiers to which the model’s performance was compared included Rules and Tress, Misc, Meta, Function, Lazy, and Bayes classifiers. From the results, it was established that the 2D stick-model matching estimation was feasible and could be used to play a crucial rule in analyzing human motion classification.
Applying logarithmic density function to develop a segmentation model for intensity and noisy inhomogeneity images: towards informed decisions in computational and applied mathematics
Authors: Hamil Shahed Ali , Majeed Abdulrahman H. 
Published: November 2019

Abstract
This study examined the how a logarithmic intensity function could be used to develop a segmentation model for intensity and noisy homogeneity images. Whereas inhomogeneous images demand the use of local image data, it remains notable that it remains defective for noisy images. The eventuality is that active contour motions tend to be misguided by the local information. In the proposed model, the logarithmic function was able to capture minute details contained in selected images and also counter or ignore the perceived noise. As such, the model proved effective and robust, worth applying to such images. To verify the effectiveness of the model, its results were compared to the experimental outcomes previously reported after employing local Chan-Vese Model. Indeed, the proposed model exhibited superior performance in relation to the treatment of intensity and noisy inhomogeneity images.
Examining a Stretching and Shrinking Wedge to Determine the Predictive Role of Nanoparticles in Shaping Nanofluid Heat Transfer in Nano-Darcy Mixed Convective Settings
Authors: Salman Imad Kh , Almothafar Nuhad S. 
Published: November 2019

Abstract
The aim of this study was to determine how nanoparticles tend to affect the heat transfer and velocity parameters during nanofluid flow processes. The study gained insights from the context of Non-Darcy mixed convection systems. Also, a wedge was considered for investigation, with specific features under examination involving surface stretching and shrinkage. Also, the coordinate transformation technique was used to obtain ordinary differential equations, which were also obtained after the conversion of governing partial differential equations. Similar, the fourth order Runge Kutta technique was used to solve the transformed equations, complemented by the shooting technique. Upon achieving the temperature and velocity field results, they were presented both in tabular and graphical forms. The motivation was to provide room for studying the movement of water, gas, and oil through the gas field or oil reservoir, as well as water purification and groundwater migration. From the results, it was established that an increase in the rate of nanoparticles concentration heat transfer causes a decrease in the friction factor. On the other hand, an increase in nanoparticles concentration caused an increase in Nusselt number or the rate of heat transfer. Additional findings demonstrate that an increase in the suction parameter causes an increase in the rate of heat transfer, as well as the friction factor. Lastly, this study established that as the wedge angle increases, the Nusselt number or rate of heat transfer increases, with a similar trend observed regarding the correlation between the wedge angle and the friction factor.
Developing an Improved Grey Prediction Model for Application to Electricity Consumption Prediction: Toward Enhanced Model Accuracy
Authors: Rasheed Maryam K. , Majeed Abdulrahman. H. 
Published: November 2019

Abstract
In the economy, one of the crucial trends or processes that play an important role involves electricity consumption prediction. Indeed, forecasting the consumption of electricity with accuracy and precision paves the way for relevant policy makers to establish strategies for electricity supply. Despite this promising and beneficial effect of accurate forecasting, limited variables and data are unlikely to offer adequate data through which satisfactory prediction accuracy might be gained. Due to the need to address this dilemma, this study developed a novel model as an improvement of the grey forecasting model. The proposed framework combined the background value’s interpolation optimization (for the GM model) and the original data sequence’s data transformation. Also, cases studies were conducted to discern the proposed model’s prediction performance. From the findings, the proposed model outperformed most of the other grey-linked frameworks relative to the parameter of forecasting accuracy. Apart from forecasting accuracy, another parameter on which the proposed model exhibited superior results compared to grey modification frameworks and the traditional GM model involves the total electricity consumption. The implication is that the findings were informative and of practical importance whereby they would allow relevant agencies in the electricity sector to develop short-term plans or strategies (due to its electricity consumption prediction accuracy), even in situations where the source data is limited.
Applying NSGA-II to Shell-and-Tube Heat Exchangers: Insights from the Exergetic Optimization Perspective
Authors: Alshamusi Qusay K. Mojar , Al-Hayder Layth S. Jasim , Alshamsi Hassan A. Habeeb 
Published: November 2019

Abstract
This study employed a genetic algorithm technique to examine and predict how shell-and-tube heat exchangers’ performance regarding heat recovery could be improved. In particular, a multi-objective energy-based optimization algorithm was employed. Two major parameters that were investigated in relation to their potential moderating effect included cost and energy efficiency. Regarding the cost, the study examined specific parameters such as operating cost (energy expenditure accruing from pumping) and equipment capital spending (the surface area of the heat exchanger). Regarding the design parameters, issues that were analyzed included baffle cut ratio, baffle spacing ratio, tube length, tube pitch ratio, tube diameters, and tube arrangement. To ensure that an optimal heat exchange was designed, aspects of the coefficient of heat transfer and pressure drop were estimated using Bell-Delaware procedure and the ε – NTU method. To ensure that minimum total cost, minimum energy destruction, and maximum energy efficiency were obtained, NSGA-II algorithm was applied. In turn, Pareto optimal solutions were reported in the results. From the findings, it was evident that two objective functions conflicted and that a change in geometrical properties would decrease the exergy destruction (or increase the exergy efficiency), leading to increased total cost. In exergy destruction, the heat exchanger optimization relative to exergy analysis indicated that irreversibility such as high temperature differences between the cold and hot steam and pressure drop affect the nature of exergy destruction. As such, it was concluded that when the heat exchanger’s component efficiency is increased, its cost increases.
A Study of the Renewable Energy Unit with Uncertainty: Towards Reserve and Energy Capacity Co-Optimization
Authors: Abbass Husein Hadi , Hadi Noor AL Huda Salim 
Published: November 2019

Abstract
This study proposed a system model through which reserve and energy capacity could be dispatched. Moderating factors that were considered included unsteady power generation and uncertain load demand. The parameters considered centered on uncertainty in power demand management while considering environmental, user, and utility objectives. The proposed mode also considered day-ahead markets for electricity relative to power demand bid variation. In so doing, the model strived to generate certain amounts of the required energy, as well as reserve capacity. Furthermore, the model predicted any lost opportunity cost before incorporating the expected load that would go unreserved. The investigation culminated into the analysis of the impact of separate and combined energy dispatch and reserve on system outcomes. To address non linear cost curves, robust optimization technique was used to optimize the selected objective function. To conduct and evaluate the numerical outcomes, as well as the feasibility of the proposed framework, case analyses were conducted. From the simulation outcomes, the proposed scheduling model proved effective in such a way that it posed beneficial effects such as improved system stability and reduced cost.
An Empirical Approach towards Solar Energy Harvesting Optimization
Authors: Jamil Zeana Zaki , Hamed Mustafa Mohamed 
Published: November 2019

Abstract
To achieve a sustainable future, one of the trends that have been observed to play a crucial role involves renewable energy. In this field, developments have progressed rapidly, with solar energy on particular focus. However, most of the solar energy has failed to fulfill its expected potential due to two main reasons. These reasons include obstacles in the form of efficiency and performance limitations. In this study, the central purpose was to steer improvements in solar panel performance. In particular, the objective of the study was to identify and optimize the affecting parameters. Therefore, a mechanical system was established for holding and controlling the photovoltaic field’s orientation and tilt. To measure and store the system’s performance information, the study relied on an electrical system, as well as a data acquisition system. To determine the impact of the target parameters on output optimization and the yield response, the investigation relied on the Response Surface Methodology and a design of experiments. From the results, the study established that from the horizon, a 600 tilt would attract an optimal result. Also, an optimal result was achieved when the panel condition was clean and that from the south, an azimuth angle was set at 450. Lastly, there was no significant effect posed by the wind factor in the target and specified parameter ranges.
A Proposed Bio-Economic Model for the Prey-Predator Fishery Model with Harvesting: Toward Modeling Dynamics in Applied Mathematics
Authors: Ismaeel Moayad H. , Majeed Azhar Abbas 
Published: November 2019

Abstract
This study proposed and analyzed a mathematical model. The proposed model was used for studying the two-prey predator system dynamics in relation to the fishery model. One of the parameters that were considered involved the possible impact of harvesting on the target populations. In particular, ecological dynamics were studied relative to tilapia, cichlid, and the Nile perch as pre-predator systems. Through system non-dimensionalization, the study computed equilibrium points before obtaining the conditions for global and local instability. To achieve the local instability condition, the investigation used Routh-Hurwitz Criterion and eigenvalues approach. With appropriate Lyapunov function defined, the coexistence equilibrium was proved. In turn, there was the analysis of the bio-economic equilibrium before conducting numerical simulations to verify the analytical outcomes that the study obtained. From the numerical results, the study established that if tilapia and cichlid fishes are not overharvested, the three species are likely to coexist. The populations were observed to play a crucial role to the Nile perch population’s growth rate. Hence, the study’s proposed mathematical model proved informative in such a way that it paved the way for the fishery control management departments to avoid overharvesting tilapia and cichlid fishes.
Data Processing, Storage, and Analysis: Applying Computational Procedures to the Case of a Falling Weight Deflectomer (FWD)
Authors: Rashid Zaman Adel , Ahmed Buthainah A.A. 
Published: November 2019

Abstract
In the field of civil engineering, the adoption and use of Falling Weight Deflectometers (FWDs) is seen as a response to the ever changing and technology-driven world. Specifically, FWDs refer to devices that aid in evaluating the physical properties of a pavement. This paper has assessed the concepts of data processing, storage, and analysis via FWDs. The device has been found to play an important role in enabling the operators and field practitioners to understand vertical deflection responses upon subjecting pavements to impulse loads. In turn, the resultant data and its analysis outcomes lead to the backcalculation of the state of stiffness, with initial analyses of the deflection bowl occurring in conjunction with the measured or assumed layer thicknesses. In turn, outcomes from the backcalculation processes lead to the understanding of the nature of the strains, stresses, and moduli in the individual layers; besides layer thickness sensitivity, the determination of isotropic layer moduli, and establishing estimates in the subgrade CBR. Overall, impositions of elastic and low strain conditions foster the determination of resilient modulus and the analysis of unbound granular materials. Hence, FWD data processing, analysis, and storage gain significance in civil engineering because it informs the nature of designing new pavements and other rehabilitation design options.
An Application of Artificial Neural Networks (ANNs) To the Backcalculation of Flexible Pavement Moduli
Authors: Aubdulnibe Faten Fakher , Jassim kassim A. 
Published: November 2019

Abstract
The role of a falling weight deflectometer (FWD) test lies in the capacity to measure pavement system responses in relation to transient loads. These loads are applied on surfaces of the pavements. A study by ARA Inc. & ERES Consultants Division (2004) indicated that the backcalculation of pavement layer moduli via FWD has continually gained adoption or wide employment, yet it has not gone without limitations. As concurred by Ceylan, Guclu, Tutumluer and Thompson (2005), FWD results are dependent on pavement response static analyses. Indeed, most of the previous studies highlight that the discrepancies between FWD test dynamic nature and the static assumption yield significant errors in moduli (Chatti, Ji & Harichandran, 2004). It has also been established that a number of dynamic solutions exist in relation to pavement response but computational complexities with which these approaches are associated imply that their application in programs of conventional backcalculation is impractical (Goel & Das, 2008). Indeed, it is the limitation of FWD results and the impractical nature of adopting dynamic solutions that have paved way for the application of artificial neural network technologies while seeking to address the backcalculation dilemma with precision. Artificial neural networks constitute simple processing element collections that are highly interconnected and, upon training, could aid in the approximation of inverse functions (Goktepe, Agar & Lav, 2006). Goktepe, Agar and Lav (2005) observed that the approximation is achieved via repeated shows of forward problem solutions. Gopalakrishnan (2010) avowed that the leading advantage associated with artificial neural networks (ANN) concerns the aspect of speed.
An Examination Of a Mathematical Framework for Geogrid Reinforcement on Sub-Base Layers: Insights from the Context of Houston, Texas
Authors: mawlood Ahmad , abied Malath sagban 
Published: November 2019

Abstract
The concept of pavement management has evolved overtime owing to the need for roadway, pavement, and pavement network repair and maintenance. Pavement management has also evolved due to growing concerns about the alarming rates at which some pavement systems have deteriorated, a trend which also compromises their durability. One of the areas that have received growing scholarly interest and research is the role of expansive soils. Indeed, expansive soils or clays exhibit extensive strength and volume changes relative to the amount of moisture content. In this study, the main aim is to find out the impact of expansive soils on pavement deterioration and management, with specific insight gained from the context of Houston, Texas.
Reviewing the Role of Mathematical Models in Enhancing Regional Pavement Management
Authors: Ahmed Hiba A. , Majeed Abdulrahman H. 
Published: November 2019

Abstract
Pavement management refers to a process through which roadway networks or facility maintenance and repairs are planned. According Abdulaziz, Taha, Kenawi and Kamel (2013), the main aim of this process is to ensure that an entire network’s pavement conditions are optimized. According to Aiswarya and Deepthi (2015), pavement management also refers to a program through which the performance and quality of pavements are improved; with Alawi and Rajab (2013) documenting further that the practice strives to ensure that through good management practices costs are minimized.
Synthesis and Characterization Structure and Physical Properties [ 50-xTiNi – x Ag] Shape Memory Alloy
Authors: Farhan Fadhil K. , Mohammed Fadhil M. , Alsafy Ameer B. 
Published: November 2019

Abstract
In this research, a metal alloy was prepared and its structural and physiological properties were studied. The method of powder technology was used in mixing and mixing powders. The ratio of 1: 1 was mixed with 100 micron granular powder and nickel powder with granular size of 78 microns. The mixture was then reinforced with a nanocrystalline powder with a mixing ratio of 0%, 1%, 3%, 5% and 7%), where the powders were mixed in an effective mechanical mixing method at a rate of 350 rpm and 6 hours continuously. Physical tests (density, hardness, yield strength, young modulus) were performed. The electrical tests were carried out using four sensors (probs) such as resistivity and electrical conductivity, as well as structural tests such as X-ray diffraction and scanning electron microscopy. The results showed a significant improvement in the micro hardness values using Vickers hardness, which resulted in improved yield strength and young modulus respectively. The results of the test showed that the electrical conductivity properties showed a clear reduction in the resistivity values of the alloys supported by the nano-silver powder and an increase in the values of the electrical conductivity compared to the base alloy (nickel-titanium).
Compare Reflex-2D-dataanalysis with other programs in data processing
Authors: Al-Maqram Nisreen 
Published: November 2019

Abstract
This study was carried out through four tracks after adjusting the parameter parameters of the GPR device suitable for the soil quality to obtain the deepest possible depth, Three track, using an antenna (500 MHz) and one track using an antenna (250 MHz) In order to know the ability of the ground penetrating radar to detect and identify the features located under the ground of the university and knowledge The thickness of the pavement layers and the limitations of the site. The aim of the study was to compare Reflex program with the RAD Explorer program, This study demonstrated the efficiency of the RAD program for the Reflex program in data processing, detection of distortions accurately and also the technical efficiency (GPR) in the detection of erosion and soil-covered impacts without drilling.
Mechanical Properties of (PMMA/CaTiZrO5) the Biocompatible
Authors: Hattab Ali K. , Yusr Hashim Ali , Farhan Fadhil K. 
Published: November 2019

Abstract
In the present study, composites have been prepared with basis polymers reinforced with triple system of bio-ceramic (CaO, TiO2, ZrO2). The percentages of the weight have been ( 0%,2%,4%,6%,8% ). The method of mixing the manual fluid and the ultrasound technique to distribute the powder pre-prepared within the polymer to obtain the desired mechanical properties has been suitable for this purpose. Mechanical tests have been performed to determine the efficiency of the composites performance, the Included (Impact strength, hardness and wear resistance). The results have shown a significant improvement in the values of the impact energy and the hardness of the particulate as well as the high resistance to wear the composites compared to the base material. The results have been interpreted according to synthetic tests for the powder (X-ray, SEM, EDX).