bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of Model Scenarios for Forecasting Food Production and Consumption in Asia in Context of Solving Global Food Problem
Authors: Stezhko Nadiia 
Published: March 2021

Abstract
The article investigates the prospects of solving the global food problem by using trend, adaptive and integrated autoregressive models (Box-Jenkins and GLM models). The used models meet the criteria of statistical reliability and accuracy, which confirms the objectivity of the obtained estimates. Calculations have been performed world-wide, for Asia, West Asia and Iraq. The obtained results of the calculations show that in Asia, due to domestic resources, the population is provided with opportunities to meet the demand (according to the WHO standards) for cereals, fish and fish products, eggs and sugar plants. The volume of vegetable oils has almost reached parity; there is a slight excess of production, from 2.0% to 7.6%. At the same time, there is a significant shortage of potatoes, meat, milk, and vegetables, provided that the production maintains the trends which have developed in the last ten years. A rather difficult situation with the possibility of providing basic food products by the domestic market at the expense of own resources has developed in the countries of Western Asia. As for the most of basic products according to estimated assessment there has been a significant food deficit of food products. A particularly unfavorable and alarming situation might develop in Iraq. The results of calculations for all food products have shown, that there is no possibility to meet the needs of the population at the expense of own production. It requires the development of modern strategies for solving the global food problem and providing more favorable conditions for access to the world food market by improving the mechanism of regulating international food trade.
Influence of Heat and Mass Transfer on Peristaltic Transport of Viscoplastic Fluid in Presence of Magnetic Field through Symmetric Channel with Porous Medium
Authors: Murad Mohammed Ali , Abdulhadi Ahmed M 
Published: March 2021

AbstractIn the present paper, we discussed the influence of heat and mass transfer on peristaltic transport of viscoplastic fluid in presence of magnetic field through symmetric channel with porous medium. The constitutive equation of Bingham plastic model is chosen to describe viscoplastic material. The nonlinear partial differential equations that described the motion of flow are simplified under assumptions of low Reynolds number and long wavelength. These equations are solved by mean of the regular perturbation method which is restricted to the smaller values of Bingham and Grashof numbers. Series solution for the axial velocity, temperature and concentration distribution have been computed. The flow quantities have been illustrated graphically for different interesting parameters. The pressure rise and trapping phenomena are also examined graphically. MATHEMATICA software is used to plot all figures.
The use of the spatial trend surface model to predict the distribution of health cadres from pharmacists in Wasit Governorate
Authors: Al-Anbagy Ass. Professor D. Auday Taha Raheem , manhal Sjad hade 
Published: March 2021

Abstract
Wasit governorate suffers from a poor distribution of health personnel from pharmacists, their concentration in some aspects, and their lack of others. In order to determine the pattern and distribution of the cadres of pharmacists, some of the spatial inference models were used in the prediction process to reach a fair distribution for pharmacists in the governorate, which is the trend surface model of the first, second and third degrees, reviewing the results using the Geo Data program. We estimated the trend surface model after assuming a certain spatial covariance function. In terms of parameters called covariance components, the components were estimated using the MLE method that adopted the Newton-Raphson iterative algorithm Then we compared these models to determine the best model that represents these data, using the criteria (AIC, BIC R2) and we concluded that the best model is the first-order trend surface model. To find out whether there is fairness in the distribution of pharmacists in the governorate the two statistical indicators were calculated the Lorenz curve and the Gini coefficient for the original and predicted data using the i-xplore program. The Lorenz curve showed the lack of equality in the distribution of pharmacists in the governorate and this was confirmed by the Gini coefficient, either for The data predicted, the Lorenz curve showed that there is fairness in the distribution of pharmacists within the governorate, and that the Gini coefficient proved that there is no discrepancy in the distribution.
Bayesian Computational Methods of the Logistic Regression Model
Authors: Al-Khairullah Najla A. , Al-Baldawi Tasnim H. K. 
Published: March 2021

Abstract
In this paper, we will discuss the performance of Bayesian computational approaches for estimating the parameters of a Logistic Regression model. Markov Chain Monte Carlo (MCMC) algorithms was the base estimation procedure. We present two algorithms: Random Walk Metropolis (RWM) and Hamiltonian Monte Carlo (HMC). We also applied these approaches to a real data set.
Essential T-small quasi-Dedekind modules
Authors: Fandi Firas sh. , Yaseen Sahira M. 
Published: March 2021

Abstract
Let M be an R-module, where R be a commutative; ring with identity. In this paper, we defined a new kind of submodules, namely T-small quasi-Dedekind module(T-small Q-D-M) and essential T-small quasi-Dedekind module(ET-small Q-D-M). Let T be a proper submodule of an R-module M, M is called an (T-small Q-D-M) if, for all f ∊ End(M), f ≠ 0, implies Kerf is an T-small submodule of M (Kerf«T
M), if T≠ 0 then T ⊈ Kerf. In case Kerf is an essential T-small submodule of M (Kerf <<
ETM), Then M is called (ET-small Q-D-M). We illustrate them by some examples and discuss some of the basic properties of this types of modules and we present some relationships between this types of modules and other modules such as, T-hollow modules and T-generalized hopfian (T-gH ) modules.
Moduli of Smoothness for Weighted Lp
,0 < p < 1 Approximation
Authors: Sharba Zainab Abdulmunim , Bhaya Eman Samir 
Published: March 2021

Abstract
Moduli of smoothness are intended for mathematicians working in approximation theory, numerical analysis and real analysis. Measuring the smoothness of a function by differentiability is too crude for many purposes in approximation theory. For many purposes many authors defined many types of moduli of smoothness. For easier work and for weighted approximation, we introduce some types of moduli of smoothness. In this paper we introduce a new moduli of smoothness for functions ƒ Lp
[-1,1] n Cr_1 (-1,1), 0 < p < 1, r ≥ 1, that have an (r — 1)st locally bsolutely cotinous derivative in (-1,1), and such that φrfris in Lp
[-1,1], where φ(x)= (1 - x
2)1/2. These moduli of smoothness are used to describe the smoothness of the derivative of functions in Lp
spaces for 0 < p < 1, also it is equivalent to specific “weighted Ditzian-Totik (DT) moduli” of smoothness, but our definition is more straightforward and easier. we also introduce some relate properties with some relations and we prove the equivalence to “K- functional”
Accuracy Comparison of 30m Resolution SRTM and ASTER Derived Digital Elevation Models over AL-khamisah Region Using RTK-DGPS Data
Authors: Hamid Huda M. 
Published: March 2021

Abstract
Digital elevation models are topographic models of the Earth’s terrain that have had the heights of vegetation, and other cultural landscapes digitally removed. The accuracy and morphologic details of the height models represent the quality. DEMS provide one of the must usefule digital data sets for a wide range of users. This study is aimed at comparing and validating (in terms of elevation accuracy) SRTM and ASTER Global Digital Elevation Model (GDEM) with DGPS Points for AL-Khamisah region. Root-Mean-Square Error (RMSE) is used as the standard measure of accuracy for feature positioning. The results, of this study showed that vertical (RMSE) for ASTER DEM 4.92 m and for SRTM 2.10 m. The objectives of this study are to effectively evaluate the accuracy of ASTER and SRTM DEM datasets and determine which DEM most accurately represents low relief terrain. Findings of this analysis may be used as resources to determine the relevance of a particular DEM dataset in low relief terrain.
Growth and experimental evidences for doped nanofilms by X-ray photoemission spectroscopy data analyses
Authors: Hamodi A. , Hökelek Tuncer , Mahmood Natheer B. , Hamodi Y. I. , Bdair T. , Salih A. T. , Naji K. K. 
Published: March 2021

Abstract
By using the molecular beam epitaxy growth technique, the impacts of growth temperatures for Bi2Te3 thin films were investigated, besides of the substrate temperatures on growth. Moreover, the full width half maximums, based on the X-ray photoemission spectroscopy measurements, have been shown clear results for Cr-Te bonds in chromium doped Bi2Te3 thin films. The current aim is a spotlight on enlightening how chromium is joined within Bi2Te3 epitaxial thin films in the process of doping concentration by providing detailed experimental evidences through the systematic structure and electronic investigations of the compound.
Commutativity of Prime Γ-Semirings with Derivations and Generalized Derivations
Authors: Hamil Shahed A. 
Published: March 2021

Abstract
The concept of Γ-semiring is a generalization of semiring. Two important mappings of Γ-semirings are derivations and generalized derivations. The commutativity of prime Γ-semiring with derivation and generalized derivation f associated with the d derivation is discussed in this article.
Generalized Reverse Derivations and Commutativity of Prime Γ-Semirings
Authors: Hamil Shahed A. 
Published: March 2021

Abstract
We present the notion of generalized reverse derivation on Γ-semiring in this article and we prove that a prime Γ-semiring with center CΓ stratifying assumption (*) aαbβc = aβbαc, for all a, b, c S and α, Γ and I be a non-zero right ideal of S such that S admits a generalized reverse derivation f associated with a reverse derivation d satisfying d(CΓ) ≠ 0, if S satisfies any one of the properties:
(i) f(aαb) + aαb Γ
(ii) f([a, b]α) + [f(a), b]α Γ
(iii) f([a, b]α) + [f(a), f(b)]α Γ
(iv) [f(a), b]α + [a, f(b)]α Γ
For of the all a, b I and α Γ, then S is commutative.
Comparative Study of QPSO and other methods in Blind Source Separation
Authors: Salman Hussein M. , Abbas Nidaa A. 
Published: March 2021

Abstract
Many techniques are introduced as solutions of the Blind Source Separation mechanisms, as an Independent Component Analysis (ICA), which became most commonly used in this field. ICA methods exploit one of two properties: sample independency and/or non-Gaussianity. In our study, cocktail-party problem processed using ICA method. In this paper, we studied the performance of three technics with independent component analysis are standard FastICA, PSO, and QPSO; and compare the results of each algorithm with others according to the number of metrics (objective as SNR and SDR and subjective as signals plotting and playing). The implement of these algorithms were be made with two source signals and three source signals. As in evaluation process, the QPSO gives more accuracy results than other technics in the signals separation process. Many input speech signals of sampling frequency 8KHz, that achieve IID. also well condition, were tested for different speeches for men and/or women, also music.
A New Modified TR Algorithm with Adaptive Radius to Solve a Nonlinear Systems of Equations
Authors: Dwail Hasan H. , Mahdi Mohammed M. , Wasi H. A. , Hashim Karrar H. , Dreeb Nabiha k. , Hussein Hussein A. , Shiker Mushtak A. K. 
Published: March 2021

Abstract
The trust region method (TRM) is a very important technique to solve both of linear and nonlinear systems of equations. In this work, a new modified algorithm of a TRM with adaptive radius is introduced in purpose of solving systems of nonlinear equations. At each iteration, the new algorithm changes the trust region radius (TRR) automatically to reduce the subproblems resolving number when the current radius is rejected. The global convergence results of the new procedure under some appropriate conditions is established. The numerical effects indicate that the suggested algorithm is interesting and robustness.
A Survey Paper on Image Mining Techniques and Classification Brain Tumor
Authors: Jasm Dhamea A. , Hamad Murtadha M , Alrawi Azmi Tawfek Hussein 
Published: March 2021

Abstract
Image mining is a method of searching and discovering the valuable information and knowledge from a set of huge image data. Image mining essentially depends on the data mining, digital image processing, machine learning, image retrieval, and artificial intelligence. Image mining is a process which is conducted to extract the hidden information such as image data and the additional pattern that could not be observed from the image. The main problems could face the mining of the collected images can be summarized in two main points: first is the image must be suitable for the mining process and second is the image’s chosen objects and features in order to be treated to extract the most effective route to save the time, and to save the effort. This paper is a survey presents the steps of the image mining process and represented an intensive view on using the image mining to the classify the brain tumors. In addition, it’s proposed a general scheme to accomplish the processes and to analysis the latest techniques which have been used to classify the brain tumors with comparison to the training groups and the amount of accuracy that obtained from the analysis. In addition, the paper compares the relevant and most recent published literature. The high published accuracy claim to be 98% which was obtained using the Deep convolutional neural network (DCNN).
A Combination Techniques of Intrusion Prevention and Detection for Cloud Computing
Authors: Alturfi Sabah M. , Muhsen Dena Kadhim , Mohammed Mohammed A. , Aziz Israa T. , Aljshamee Mustafa 
Published: March 2021

Abstract
Cloud computing provides scalable, on-demand, and highly available computing services over the Internet to both the public and organizations on a pay-per-use basis. It provides a variety of services such as networking, storage space, and applications. The key issue for cloud computing is ensuring the confidentiality and privacy of cloud resources and data. Enticing the user to purchase cloud services requires their trust which cannot be guaranteed unless the infrastructure is effectively protected because attacks at this level will threaten the whole system. To this end, we propose the Integrated Intrusion Prevention and Detection System (IIPDS) to prevent and detect different types of attacks to the infrastructure level of the cloud system. The proposed design uses Trusted Third Party (TTP) services and SSL/TLS protocols as intrusion prevention methods to secure the communication between the cloud provider and the user. It also uses multiple Intrusion Detection Systems (IDS) distributed over multiple cloud regions. The IDS system is capable of detecting known and unknown attacks using anomaly and rule-based (signature) intrusion detection techniques. The simulation results proved the efficiency of the system in detecting a wide range of attacks with low false positive alerts and low computational overhead.
A Dual-Polarized MIMO Array Antenna System for Future Smartphone
Authors: Khalil Al-Ani Nada M. , Shareef Al-Ani Oras A. , Mosleh Mahmood F. , Abd-Alhameed Read A. 
Published: March 2021

Abstract
In this paper, a dual-polarization four antennas Multiple Input Multiple Output (MIMO) scheme is proposed. The four elements are arranged over a surface area of 67×139mm2 printed circuit board (PCB) using dielectric substrate FR-4 with epsilon 4.4 and thermal conductivity 0.025. A circular slot radiator is etched in ground plane in order to improve the radiation characteristics. To mitigate the mutual coupling in the proposed MIMO scheme, two rectangular parasitics with one open rib are embedded across square slot radiator. The proposed single antenna model covers a frequency range of 5.81-6.66 GHz at -10dB impedance bandwidth. However, the bandwidth is raised up to 1.47 MHz (5.48-6.95) GHz at -6dB. The results show that -20 dB return losses can be obtained, while -45 dB isolation was achieved for a dual microstrip line. The proposed antenna can be integrated with new smart-mobile devices for future 5G wireless communications.
Network Performance Evaluation of Different MANET Routing Protocols Configured on Heterogeneous Nodes
Authors: Alturfi Sabah M. , Muhsen Dena Kadhim , Mohammed Mohammed A. 
Published: March 2021

Abstract
The recent communication technology tends to be wirelessly for the mobility reason. Mobile Ad-hoc Network (MANET) can be established without any infrastructure or centralized controller. It can be constructed quickly in rural areas, military zones, and in emergency cases like earthquake. Three different types of routing protocols were categorized according to their work’s nature, which are Proactive, Reactive and Hybrid routing protocols. Due to the mobility characteristic of MANET nodes, routing protocols play important role in determining the network efficiency where the network topology is changed frequently. Many studies are conducted to analyze network performance and specify the best routing protocol using different simulation tools. In this paper, the performance of network is analyzed and evaluated when heterogeneous nodes are configured with these three types of protocols under heavy traffic load (VOIP). The result of our simulation shows that OLSR protocol has the highest throughput among others while DSR protocol shows the best performance in terms of Network load. Generally, the performance of routing protocol differs depending on the network type and use.
Fixed Point Theorems of A Set-Valued Integral Type Mapping in Complete Partial IMetric Spaces
Authors: khaleel Liqaa J. , Ahmed Buthainah A. A. 
Published: March 2021

Abstract
In our paper we prove that the set valued mappings of integral type with lower semi continuous non-negative lebesgue integrable mapping have a fixed point in complete partial metric spaces. The same result was proved without needed to the lower semi continuous condition. We give two examples to illustrating the necessity for non-negative and lower semi continuous conditions.
An Interactive Network security for Evaluating Linear Regression Models in Cancer Mortality Analysis and Self-Correlation of Errors by Using Durbin-Watson Tests in Babylon/Iraq
Authors: Ashoor Asmaa Shaker , Kazem Ali Abdul Karim , Gore Sharad 
Published: March 2021

Abstract
The present study addresses Interactive Network security of the model of simple and frequent linear regression constructing method in describing the phenomenon of deaths of patients with cancer for the time variable in two aspects, one of which provides a theoretical background of the construction of the model of simple linear regression and the adoption of the principle of errors in the description of the standard deviation between the estimated value of the model and its true value, the other one is practical which shows the mechanism of building the model of simple linear regression and multiplexing and analysis of the results using two programs ( SPSS and Minitab ). And the study of the behaviour of errors for each model and drawn in the form of normal probability plot was also used the coefficient of selection R2 and Coefficient Selection Factor(adj) R2 in comparing the models and determining the best model in explaining the growth phenomenon of cancer deaths.
The Waikato Open Source Frameworks (WEKA and MOA) for Machine Learning Techniques
Authors: Hammoodi Mahmood Shakir , Essa Hasanain Ali Al , Hanon Wial Abbas 
Published: March 2021

Abstract
WEKA and MOA are a free open-source software project specific for data mining and data stream mining, respectively. They are written in Java and developed at the University of Waikato, New Zealand. This research paper presents a comprehensive study of both consists of algorithms, evaluation, visualization, correlation between WEKA and MOA, workflow of implementation, and the classification accuracy.
Distributed Denial of Service Attacks Detection System by Machine Learning Based on Dimensionality Reduction
Authors: Abbas Sara Abdalelah , Almhanna Mahdi S. 
Published: March 2021

Abstract
Data mining algorithms have essential methods and rules that can contribute in detecting and preventing various types of network attacks. These methods are utilized with the intrusion detection systems that can be designed and developed preserve the information in organizations from damage. Specifically, the data mining technique allows users to effectively distinguish between normal and malicious traffic with good accuracy. In this paper, a methodology for revealing and detecting (DDOS) network attack was suggested using DM algorithms. The utilized methodology is divided especially into four parts, each part has its own rules, as the following: First one is the pre-processing which consists of three sub-steps: (i) encoding, (ii) log2, and (iii) PCA. Encoding is used by converting the original nominal packets into numeric features. Standardization of data was performed using logarithmic algorithm. Finally the PCA technique is applied eight times for several different features to reduce the dimensions of the dataset. The second stage is an anomaly detection model, (RF) algorithm is implemented for the extraction of data patterns while classification the types of the given features in training step, (NB) algorithm was also used in classifying the data to compare the results of its classification with the results of using the classifier (RF). In the third stage, the outcomes were tested by implementing the already trained datasets. In the fourth stage, the proposed system performance evaluation metrics were collected such as the rates of accuracy, false alarm, detection, precision, and F.measure.
MIX dataset were utilized to train and test the proposed model which resulted from merging two datasets (PORTMAP+LDAP), which are used from the CICDDOS2019 datasets, each consisting of several types of attack packets, and benign packets.
Several metrics were utilized in the evaluation of the proposed system. The best outcomes were obtained for detection by using the log2 algorithm and PCA technique in the preprocessing step and using (RF)classifier to classify the dataset. the accuracy when using MIX dataset was 99.9764%, the detection rate was 100%, false alarm rate ≍ 0, and the F.measure was 99.9% when PCA = 25.
Arabic voice system to help illiterate or blind for using computer
Authors: Ali Shaker K. , Mahdi Zahraa M. 
Published: March 2021

Abstract
Speech recognition is one type of technology, which make a computer to recognize the voice of words that an individual speaks through a microphone and convert it into the written text. In this paper, the proposed system for helping illiterate and blind peoples to open applications with them voices.
The proposed system includes two parts; the first part is the training part while the second part is used for the testing. The system contains seven-steps; the first step is the recording of voices and the second step is voice pre-processing. The third step is the feature extraction using MFCC (Mel Frequency Cepstrum Coefficient) method that involves seven steps. The fourth step is for classification voices, there are 1400 voices samples used in training by using a Naïve Bayesian method as a classifier. The fifth step is the matching step using the Correlation Coefficient, there are 200 voices samples in testing. The sixth step was to convert voice into text and the seventh step for execution one of 20 commands.
The accuracy of results from using the Naïve Bayesian algorithm in the training phase gives (100 %) while the accuracy of results in the testing phase using Correlation Coefficient gives (98%).