bluuebunny/crossref_metadata_2025_split huggingface dataset:
Influence of magnetic field on the characteristics of n-type PSi prepared by photo-electro-chemical etching process
Authors: Khalaf Akram A. , Attallah Ali H. , Dheyab Amer B. , Alwan Alwan M. 
Published: July 2021

AbstractThe surface uniformity of porous silicon (PSi) morphologies will enhance the overall properties of the PSi layer. In this study, the role of perpendicular magnetic field (MF) on structural, optical, and electrical properties of (PSi) substrates are reported. The (PSi) is prepared with a photo-electrochemical etching process in the front-side illumination pathway with and without a perpendicular magnetic field (MF). The application of (MF) on the path of the electric charge carrier leads to modify the morphologies of PSi surface. The pores shape, sizes, orientation, and homogeneity, and electrical properties will vary with the (MF). The role of (MF) will contribute to an increase in the number of pores and decrease the overlapping process. And also, promotes the orientation of the relatively more defined pores across the Psi surface. The observed noticeable changes in PL spectra, electrical properties, and charge carrier transport mechanisms may be owing to the surface reconstruction process. The influence of (MF) on the characteristics of Au thin layer / PSi/c-Si/Al structures will lead to converting its behavior from the resistor to Schottky-like junction.
Computing the reliability of a complex network using two techniques
Authors: Abd Alsharify Fouad Hamza , Haddi Hassan Zahir Abdul 
Published: July 2021

Abstract
To find the reliability of any complex network, we need to convert it into a simple network to facilitate the process of reliability calculation. In this paper we simplify a complex network into a simple network by using two techniques, in the first technique “reduction method” the complex network was converted into a parallel network, while in the second technique “delta - star method”, the complex network has been transformed into a series network. The 2nd technique is based on the 1st technique in finding the reliability of a subnetwork. At the end of the research, a comparison between these two methods was made.
Atmospheric stability classes and its effect on co concentration emission around Kirkuk refinery
Authors: Saleh Sajjad H , Hassoon Ahmed F 
Published: July 2021

AbstractAtmospheric stability defines as the atmospheric tendency to reduce or intensify vertical motion, in other words, suppress or enhance existing turbulence, thus atmospheric stability play important role in transport and dispersion of air pollutant. In This study relationship between air pollutant of CO gases in 2019 resulted from burning three types of fuels (fuel gas, gas oil, naphtha) in 8 production units inside Kirkuk refinery (located in north-east of Iraq), and atmospheric stability analysis in different directions to know the effect of atmospheric stability classes on the emission of CO poison gas. Atmospheric element such as wind speed, cloud amount and solar altitude used by the Turner method to calculate seven stability classes, these classes are compared with CO pollutant at a different distance from the source point. From samples taken from stacks and fuels burned in a refinery, emission rate and exist velocity from 11 stacks calculated and used to estimated CO gas by Gaussian equation for dispersion at two months (January, July) in 2019. The comparison values of the concentrations with the distances from the point source for January and July was carefully examined, as it was noticed that the concentrations during the month’s classes B and F varieties in percent between January and July reach %120 - %170, while in the rest classes C, D, and G were close to 80% it decreases with the distance through (1000m– 10000m) by 81% - 59%, in Class A and E There is a difference in one of the two months.
Medical Image Authentication by Combining Hash Signature and Watermarking Based on Frequency Domains
Authors: Jabbar Amira K. , Hashim Ashwaq T. , Hassan Qussay F. 
Published: July 2021

Abstract
Medical images are transmitted to other remote places through the E-healthcare system. The protection of medical images is very crucial. Medical images need to be protected against any modification which the attacker may do through the unsecured channel. It is necessary for inspecting the integrity of the ROI (Region of Interest) of the received medical image prior to the adoption of any diagnostic decision to avoid a misdiagnosis. This paper aimed to confirm the integrity and authenticity of medical images by combining the hash signature with the watermarking technique based on the frequency domains. At first, the medical image is divided into ROI and RONI (Region of Non-Interest). The SLT and DCT transformations are employed together to extract the essential features set from ROI and then combined with EPR (Electronic Patient Registration) to produce a watermark, and then it is encoded by a chaotic map with a secret key to provide a signature. On the other hand, the RONI is mapping into randomly subblocks based on the linear system, and then the Signature is embedded in the chosen block using DWT. The hash code of the recovered image and EPR will be compared with the extracted watermark for integrity and authenticity. The experimental results demonstrate the watermark’s robustness against many of the more aggressive and geometric signal processing distortions without affecting the quality of the original medical image. In particular, compared with state-of-the-art technology, the proposed algorithm improves the average NC value larger than 0.90 under all types of attacks.
Investigation of properties of selective Laser sintering of Titanium alloy composite
Authors: Abdul Razzaq Ghassan Hassan , Jafar Saad A , Humadi Jasim I 
Published: July 2021

Abstract
A wide range of material utilized in Selective Laser Sintering (SLS) method opens the research thrust in the Additive Manufacturing (AM) or Solid Freeform Fabrication (SFF) technology for the researchers There are many works done on materials like polymer metal composite ceramics & sand under SLS method to enhance the quality & mechanical properties of parts described through optimizing the process parameters Still there is a wide scope to optimize the SLS process parameters which are using materials such as sand ceramics & metals Also among the different response variables available the impact of surface roughness on SLS stainless steel metal parts & the quality of sand mould casting parts have not yet been analyzed Further if the gap of the influencing process parameters on different materials is fulfilled, the operator can easily utilize the SLS process before carrying out the actual process The main objective of this s focuses on the design & investigation of SLS process parameter & final part properties Also a manual suggestive process parameter selection methodology has developed for the laser sintering processes.
Platforms of IoT for Detection and Diagnosis covid_19 :
Authors: Kadim Reham Basim , Ali Hussien Naseer 
Published: July 2021

Abstract
As a result of the spread of Coronavirus very quickly. The difficulty of controlling its spread. Moreover, the lack of a specific mechanism to limit the spread of the Coronavirus. The role of the Internet of Things has emerged in the fight against the Corona pandemic. This paper reviews the Internet platform, for things to diagnose and fight Coronavirus that help to control this disease with its sensors as well as various tools. that help to limit its spread also prevent human rapprochement. Furthermore, this paper discusses the most important approaches that assist in diagnosing this disease. In addition to networks, the role of the Internet in dealing with this virus is addressed at the end of this paper.
Forecasting neural networks, such as forecasting sale the plastic injection machine market
Authors: Khalid Hind 
Published: July 2021

Abstract
The aim of this research is to show what benefits the use of neural networks in forecasting processes can bring, among its development through out the years considering different kinds of mathematical methods. The software applications that have been developed recently for forecasting processes are neural and AI-based. Data entries from previous months are used in mathematical methods to calculate and predict sales in a company. By the use of these neural and AI-based processes, predictions of whether company sales will go up or down the next month can be made. This research will help to better understand the process behind these predictions and how the developments of neural networks come into place.
Development of Effectiveness Method of Wireless Segments in Information System
Authors: Mohammed Mohammed Q. , Muhamed Saif Q. , Taresh Ali Hasan 
Published: July 2021

Abstract
This research aiming is more efficient information system on the basis of the development and practical application of methods and models that enable the preliminary assessment of the feasibility of wireless segments (WS) or the choice of rational structure of WS. Thus, the comprehensive evaluation of the effectiveness of the proposed options for the structure to use the wireless segment in the information system that we consider is the actual problem. To Developing a method of assessing the efficacy of WS in the information system which is the basic method of evaluating options for the structures is the method of WS activity-based costing. By using developed and the proposed methods and models for reducing time-consuming complexity of work with a preliminary assessment of whether to apply a different option structures WS, increase the efficiency of the preparation of recommendations on the choice of rational structure of WS among the options for upgrading or development of IP business or organization. In this paper, methods have been used for assessing the efficacy of RBCs in the information system. The research focused on efficient information system on the basis of the development and practical application of methods and models that enable the preliminary assessment of the feasibility of WS or the choice of rational structure of WS.
Determining the excitation energies of 68Ni Nucleus a Function of the Coupling Angle ¸a,bBy Means of Modified Surface Delta-Interaction
Authors: Hameed Dalal Naji , Khalaf Hasan Ali 
Published: July 2021

Abstract
In this paper, the nuclear shell model SM was applied to study the energy levels of the nucleus the effect of orbit on energy levels was studied,we consider the residual interaction to be modified surface delta interaction MSDI. We have studied the excitation energies of the 68Ni a nucleus, which contain two neutrons outside closed shell of the 66Ni. the computation of eigenvalues of 68Ni is performed in the frame of (1 p1/2 0g9/2) and (1 _p1/2 0g9/2 0d5/2), we search the effect of the orbital 0d5/2 on the energy levels. The energy levels and angular momentum of all possible cases were investigated. Thus, we have worked on a theoretical process to discover the relation between the energy levels and the classical coupling angle ¸a,b at different orbital within neutron - neutron interaction. Accordingly, We have noticed that the energy levels manifest to follow two inclusive functions, which depend on the classical coupling angles, but are not constrained of angular momentum I. In conclusion, we conclude that our results agree with the experimental data.
Estimation of the reliability function of the Rayleigh distribution using some robust and kernel methods
Authors: AbdulMuttaleb Thaer Hashim , Talib Hayder Raaid , Hamdullah Ahmed Ali 
Published: July 2021

Abstract
The research presents the reliability. It is defined as the probability of accomplishing any part of the system within a specified time and under the same circumstances. On the theoretical side, the reliability, the reliability function, and the cumulative function of failure are studied within the one-parameter Raleigh distribution. This research aims to discover many factors that are missed the reliability evaluation which causes constant interruptions of the machines in addition to the problems of data. The problem of the research is that there are many methods for estimating the reliability function but no one has suitable qualifications for most of these methods in the data such as the presence of anomalous values or extreme values or the appropriate distribution of these data is unknown. Therefore, the data need methods through which can be dealt with this problem. Two of the estimation methods have been used: the robust (estimator M) method and the nonparametric Kernel method. These estimation methods are derived to arrive at the formulas of their capabilities. A comparison of these estimations is made using the simulation method as it is implemented. Simulation experiments using different sample sizes and each experiment is repeated (1000) times to achieve the objective. The results are compared by using one of the most important statistical measures which is the mean of error squares (MSE). The best estimation method has been reached is the robust (M estimator) method. It has been shown that the estimation of the reliability function gradually decreases with time, and this is identical to the properties of this function.
Effect of HCL Molarity on the Properties of PANI/MgO Nanocomposite Thin Films
Authors: Mohammed Sura S. , Alwan Tariq J. 
Published: July 2021

Abstract
In this work PANI/MgO nanocomposite thin films were prepared by situ oxidative polymerisation method under different hydrochloric acid (HCl) molarity. The PANI/MgO nanocomposite thin films were characterized by X-ray diffraction, field emission scanning electron microscope (FESEM) and Fourier transform infrared spectroscopy to study the effect of HCL molarity on structural properties and functional groups for the prepared samples. The electrical properties of the prepared samples were studied, and it was found that the best molarity of the preparation is 1.5M where the conductivity value became 2.25 S.cm−1.
Quantitative Analysis of heavy metals in gallstone Using LIBS
Authors: Naser Hawraa J. , Hamad Tagreed K. 
Published: July 2021

Abstract
Concentrations of heavy metals in gallstones samples gathered from different hospital were estimated via laser induced breakdown spectroscopy (LIBS (.Quantitative and qualitative analysis of the gallstone samples were achieved by using the locally developed LIBS set up equipped with Nd: YAG laser (Q-switched) at 1064 nm, pulse duration 9 ns and pulse energy 300 mJ. Quantitative analysis was performed for Cr, Cd, Zn, Pb, Cu and As based on calibration curve constructed from the correlation between the intensity of the LIBS emission lines and the concentration of each element measured by AAS. It was noticed that the percentage of copper, zinc, and manganese was higher in pigment samples higher than in mixed samples, and that it was not present in the cholesterol samples. However, chromium and cadmium elements were present in a high percentage in cholesterol samples and higher than other types of gallstones. The most important conclusion was that heavy elements such as Pb and As were present in the samples of smoking patients. The relative errors for all samples were in the range of (1.5-7.8) %.
Lora in a campus: Outdoor Environment Accurate Modelling Based on Particle Swarm Optimization at 435MHz
Authors: Kurji Ali S. , Al-Nakkash Aseel H. , Hussein Osama Abbas 
Published: July 2021

Abstract
Path Loss (PL) models are an essential factor affecting the network design and its operation. With different environmental conditions, interpreting the PL characteristics in an open environment is a complex problem. In this work, the propagation of LoRa technology in a campus is investigated in order to propose an accurate PL model. The measurements are taken place in two outdoor regions of the Electrical Engineering Technical College in Baghdad, Iraq. Measured field data correlates with global propagation models, demonstrating that ERICSON model results after an evaluation are likely to produce positive results. Different environment conditions make the global PL models difficult to generalize, yield some errors between the measured and estimated PL. For addressing this downside, Particle Swarm Optimization (PSO) has been based to develop the model parameters, hence matching the model to reality. The ERICSON model’s parameters have been improved to the best fit with measured data, and the lowest Root Mean Square Error (RMSE) is gained equals to 3.7168dB and 5.4030dB for the two adopted regions.
Convergence of random iterative scheme to a common random fixed points
Authors: Malih Sabah Hassan , Abed Salwa Salman 
Published: July 2021

AbstractIn the context of uniformly convex separable Banach spaces, we implement an iterations scheme under Fibonacci sequence for approximating common random fixed points of two asymptotically nonexpansive random operators, and define weak and strong convergence results for common random fixed points of asymptotically nonexpansive random operator.
Photocatalytic Activity of CdS Nanosheets Prepared by Chemical Bath Deposition Method
Authors: Ali Marwa M. , Kudhier Muhsin A. , Sabry Raad S. 
Published: July 2021

Abstract
CdS nanosheets are synthesized via the chemical bath deposition method (CBD) using three different Cd/S molar ratios for the photocatalytic degradation of methylene blue (MB), as an example of an organic pollutant. The resulting nanosheets were characterized by XRD, FESEM, and UV-VIS spectroscopy. The XRD data analysis for prepared powder resulted in mixed phases of zinc-blende and wurtzite in all different Cd/S molar ratios with average crystalline size increased from (50.9 nm to 59.7 nm). The as-prepared CdS shows an absorbance edge increased from (340 nm, to 490). The value of the bandgap decreased from (2.6 eV to 2.3 eV) with an increasing molar ratio. Increasing molar ratio also leads to high and stable photocatalytic with high degradation efficiency (92.7-98.4) % after 150 min of sunlight irradiation.
Graphical Abstract
Generalized Γ-n-Derivations on Prime Γ-Near-Rings
Authors: Ahmed Hiba A. , Majeed Abdulrahman H. 
Published: July 2021

Abstract
The main purpose of this paper is to define generalized Γ-n-derivation, study and investigate some results of generalized Γ-n-derivation on prime Γ-near-ring G and K be a nonzero semi-group ideal of G which force G to be a commutative ring.
Asymptotic Behavior Criteria for Solutions Second Order Half Linear Neutral Differential Equation
Authors: Ketab Sattar Naser , Abdullah Banen Wafaa 
Published: July 2021

Abstract
In this paper the we study the oscillation and asymptotic behavior of second-order Half linear neutral differential equations. some basic and necessary and sufficient condition are established for every solution of

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Comparison of tow two cryptocurrencies: Bitcoin and Litecoin
Authors: Jumaili Mustafa Lateef Fadhil , Karim Sulaiman M. 
Published: July 2021

Abstract
The increasing daily use of virtual currency (cryptocurrency) is being adopted worldwide for many legal and illegal transactions. Cryptocurrency technology operates on a network that allows people to make payments around the world without any middleman. Since the technology was first developed, it became popular, and the price of cryptocurrencies started to rise and became unstable. In terms of the returns gained from investing in cryptocurrencies, they have been huge in recent times, but there has always been a question about their existence and reliability. A cryptocurrency is a digital process that relies on the use of an encryption system for security primarily. Despite the challenges and problems facing cryptocurrencies, the success of Bitcoin has led several companies to search for alternative digital currencies. This paper tries to compare two cryptocurrencies - Bitcoin (BTC) and Litecoin (LTC) with respect to their stability and understanding its trends in the recent period.
Energy-Efficient Load Balancing Technique to optimize Average response time and Data Center Processing Time in Cloud Computing Environment
Authors: Jeyalaksshmi S. , Anita Smiles J. , Akila D. , Mukherjee Dibyendu , Obaid Ahmed J. 
Published: July 2021

Abstract
Cloud infrastructure is a modern computing system in which pooled services are made available to users at various times depending on their demands. The process of distributing workload among computing system nodes is known as load balancing. Loads include things like CPU power; ram capacity, and network traffic. A well-balanced load avoids the situation when some nodes are fully loaded while others are inactive or not working. Where there are many tasks in a virtual machine (VM), these tasks are delegated to underutilize VMs in the same or a separate datacenter. Modified Round Robin and Modified Honey Bee Algorithms are proposed in this article for effective load balancing based on honey bee and Round Robin foraging activity to control load through VMs. Tasks taken from VMs that are crowded are viewed as honey bees. In the suggested method which is a circular ribbon, filled VMs are considered. In order to ensure a fast responding time and a minimum number of task migrations, the planned protocol also explores the aims of tasks in VM queues. The results of the test indicate that the quality of service has improved considerably (QoS).
Ion Trajectory Analysis in FIB Microscope to Study the Dielectric Constant using Mirror Method
Authors: Hazime Luna Basil , Zoory Muayyed Jabar 
Published: July 2021

Abstract
The current work used the same mathematical model that was used to study the behavior of an accelerated probing electron in order to create electron-mirror images [1]. Using straightforward trigonometry, this mathematical model was used to investigate the properties of the polymer PMMA as a result of the ion mirror effect phenomenon. This work also considers determining the influence of dielectric constant, which is one of the most important electrical properties of the material by using MATLAB simulation to help the practical results that we obtained and comparing it to the findings obtained for the electron mirror. The obtained results indicate that the presented methodology can be used to explain, interpret, and add further detail to the understanding of the ion mirror effect for future studies.
Replicating the MAP Kinase Cascade in Membrane Computing
Authors: Mohan Bareq Shaalan , Mahmood Ali A. , Mohammed Mohammed Q. , Zaki Nashwan Dheyaa 
Published: July 2021

Abstract
Membrane Computing (MC) is defined as one of the main areas in computer sciences; MC has the aim of discovering novel computational models from studying biological cells, specifically the cellular membranes. Mitogen-Activated Protein Kinases (MAPK) cascade was the subject of research in the areas of modeling and simulation. Various software tools such as Performance Evaluation Process Algebra (PEPA) have been used to solve the MAPK cascade for the purpose of improving the effectiveness of signaling. In this study, the MAPK cascade is modeled by using MC. The models of Membrane Computing could be totally fully utilized by applying parallel computing platforms. P-Lingua can be defined as a programming language for MeCoSim and MC, where MC simulators are used to model and simulate MAPK. P-Lingua will be applied to structure, develop and examine the implementation of MAPK cascades in membrane computing. MeCoSim supports charts, outputs, and inputs which have been adapted to MC. The simulation results have been put to comparison with PEPA model. The results indicate that MC improves the MAPK implementation compared to PEPA. This study showed that MC, with its biological characteristics, could improve the implementation regarding biological processes including MAPK.