bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Adoption of ICT in Libyan Higher Education Institutions (LHEIs): Theoretical Models and Challenges
Authors: Mhamed Alshref Halema H. , Abas Hafiza , Abu Bakar Nur Azaliah 
Published: May 2021

Abstract
The adoption of eLearning in developing countries is rare when a comparison is made against the developed nations. Therefore, this study answered calls from numerous literature demanding for more research to investigate the adoption, usage, and application of eLearning systems and applications in Libyan higher education institutions (LHEIs) to contribute to this crucial knowledge gap. Thus, a systematic literature review (SLR) was conducted focusing on the eLearning technology acceptance theories and models and open issues and challenges facing the LHEIs. Hence, the findings revealed that the technology acceptance model (TAM) is the most dominant theoretical model applied to test the adoption of eLearning in LHEIs. The finding further revealed that there are limited studies based on other technology acceptance theories such as the unified theory of acceptance and use of technology (UTAUT), the theory of reasoned action (TRA), and the theory of planned behavior (TPB). Hence, this study recommends the adoption of the UTAUT framework for future research due to its foundation from eight different technology acceptance models, including the dominant TAM theory, which could offer new insights. The findings of this study have the potential for academic researchers wanting to study the acceptance and use of technology for teaching and learning especially in developing countries.
Improving K-means clustering based on firefly algorithm
Authors: Al Radhwani Amal Mahmood Naji , Algamal Zakariya Yahya 
Published: May 2021

Abstract
Data clustering determines a group of patterns in a dataset which are homogeneous in nature. The objective is to develop an automatic algorithm which can accurately classify an unleveled dataset into groups. The K-means method is the most fundamental partitioned clustering concept. However, the performance of K-means method is fully depending on determining the number of clusters, K, and determining the optimal centroid for performing the clustering process. In this paper, an adaptive firefly optimization algorithm, which is a nature-inspired algorithm, is employed to improve the K-means clustering. The experimental results of clustering two real datasets show that the proposed method is able to effectively outperform other alternatives methods.
Shrinkage estimators for semiparametric regression model
Authors: Mohammed Hadi Salman , Algamal Zakariya Yahya 
Published: May 2021

Abstract
Semiparametric regression models are extensions of linear regression models to include a nonparametric function of some explanatory variables. In semiparametric regression model researchers often encounter the problem of multicollinearity. In the context of ridge estimator, the estimation of shrinkage parameter plays an important role in analyzing data. In this paper, numerous selection methods of the shrinkage parameter of ridge estimator are explored and investigated. Our Monte Carlo simulation results suggest that some estimators can bring significant improvement relative to others, in terms of mean squared error.
A New Left Truncated Gumbel Distribution: Properties and Estimation
Authors: Neamah M W , Qasim B A 
Published: May 2021

Abstract
Gumbel probability distribution is an important probability distribution that has wide applications in various fields such as engineering, physics, hydrology, geology, etc. The study aims to generate a new truncated distribution by truncate the probability density function of the first type Gumbel distribution from the left side to obtain the Truncated Gumbel distribution from the left side within the period (0, ∞). As we work in this paper on the derivation of the new truncated distribution formula and its characteristics. As well as discussing different methods of estimating its parameters, represented by the maximum likelihood method and Percentiles Estimation Method, then making a simulation of the comparison between methods of estimation.
Quantitative Structure-Activity Relationship Modeling Based on Improving Penalized Linear Regression Model
Authors: Shamany Rehad Emad , Algamal Zakariya Yahya 
Published: May 2021

AbstractOne of the powerful and a promising model which is used to understand the structural relationship between the chemical activity and the chemical compounds is the quantitative structure-activity relationship (QSAR). However, the huge in dimensionality is one of the major problems which affect the quality of the QSAR modeling. Penalized methods are an attractive framework that have been adapted and gained popularity among researchers as the key for performing descriptor selection and QSAR model estimation simultaneously. The choice of the tuning parameter of the penalized methods is critical. Our aim of this paper is to efficiently estimate such a tuning parameter by using bat algorithm (BA), which is a king of nature-inspired algorithms. Experimental results, obtained by running on two datasets, show that our proposed method performs better than other methods, in terms of prediction, number of selected descriptors, and running time. Further, the Y-randomization test and applicability domain confirm that the constructed QSAR model by BA method is reliable and robust.
Regularized MAVE through the elastic net with correlated predictors
Authors: Alkenani A , Rahman E 
Published: May 2021

AbstractIn this article, we proposed a model-free variable selection method (SMAVE-EN). The concepts of sufficient dimension reduction (SDR) and regularization methods are combined to introduce SMAVE-EN. This method is proposed to produce a shrinkage estimation when the predictors are highly correlated under SDR settings. The advantage of SMAVE-EN is that SMAVE-EN extended Elastic net (EN) to nonlinear and multi-dimensional regression under SDR settings. From another side, the SMAVE-EN enables MAVE to work with problems were the predictors are highly correlated. In addition, SMAVE-EN can exhaustively estimate dimensions, while selecting informative covariates simultaneously under SDR framework. The effectiveness of SMAVE-EN is evaluated by both simulation and real data analysis.
A Suggested method for detecting outliers based on a particle swarm optimization algorithm
Authors: Merza Emad Obaid , Al-Anber Nashaat Jasim 
Published: May 2021

Abstract
The occurrence of tremendous developments in the field of data has led to the formation of huge volumes of data, and it is natural that this leads to the presence of outliers in this data for many reasons. The presence of outliers in the data affects the statistical analysis, so we must try to reduce their impact in various ways. On the other hand, the existence of outliers may be of great benefit in many application and of great importance in various fields. In this paper we propose a new method for detecting outliers based on the Particle Swarm Optimization algorithm (PSO). The new propose algorithm was compared with the normal distribution method, and the results obtained from the new method were very promising and encouraging.
Suggested Video Steganography Algorithm Based on Power Low Transform (PLT) Using IoTs
Authors: Ali Khodher Maisa’a Abid 
Published: May 2021

AbstractDatum embedding or information hiding is a method that accepted us to secret embedded and extracted data from any file, such as picture file, a video file, and sound file. The base algorithm in steganography is the embedded and extraction algorithms. The objective of this paper is hiding a secret message in video frame to prevent an attacker from accessing the message.This paper suggested new algorithm to hide secret message in video, after convert video to number of frames, it takes each video frame applied the power low transform (PLT) in 3 or 3.5 or 4. In this paper takes power low transform only 3.5 to hide secret message in each video frame uses the secret key, the secret key is curve of cosh-exponential, each point in curve selected the location in frame to hide one bit from frame video. It obtains stego-frame video to Transmitted the for IoTs, and save in database in IoTs, and any authors can be access to this stego-frame video in database to known secret key. The outcome of this algorithm is very good in steganography video, it uses power low transform to obtain the high security, transparency, high capacity in secret message and powerful. These results are obtaining many tests PSNR, MSE, Entropy, Correlation coefficient, Histogram, and Capacity.
Overview of Five Techniques Used for Security and Privacy Insurance in Smart Cities
Authors: Varfolomeev Alexander A , Alfarhani Liwa H , Oleiwi Zahraa Ch 
Published: May 2021

Abstract
Digitization and technological transformation in providing various services have become a goal for many countries in light of the current digital revolution to implement the concept of a smart city. Given the great importance of the smart city concept by researchers, the overriding concern is how to maintain data security and user privacy. These two criteria can or directly represent the strengths and weaknesses of such technology projects. This paper included a comprehensive study of the smart city, its concept and components. The research also included a detailed study of the most important applications included in smart city services and their working mechanisms and uses. The diversity of applications and services provided under the smart city environment is proof of the importance of this model. The paper also reviewed the security risks of data in all stages of work, data collection, data transfer and processing. Finally, the paper reviewed the five most important technologies used in a smart city to maintain information security and data privacy, their advantages, their internal methodology and algorithms. In the end, this paper aims to give a clear picture of all the details of the smart city and the technologies used for the purpose of ensuring information security and data privacy.
Improving penalized regression-based clustering model in big data
Authors: Mahmood Al-Kababchee Sarah Ghanim , Qasim Omar Saber , Algamal Zakariya Yahya 
Published: May 2021

Abstract
Clustering is the main procedure for data mining with a wide application such as gene analysis. Clustering is a method of separates (grouping) previously unclassified data on the basis of its features, and it is an unsupervised learning problem that divides that data into groups in such a way that it makes those data in the same group more similar to each other compared to in other groups. Penalized regression-based clustering is an extension of the “Sum Of Norms” clustering model. In this paper, the nature-inspired algorithm is employed to improve the penalized regression-based clustering to better estimation. The real data application on gene expression data results suggests that our proposed improvement can bring significant improvement relative to others.
Some Properties in Grill–Topological Open and Closed Sets
Authors: Mustafa M O , Esmaeel R B 
Published: May 2021

Abstract
The aim of this research is to study the modern sort of open sets that is said 𝔾-g-closed. Some functions by this notion was explained and the relationships among them like continuous function 𝔾g-continuous function strongly- 𝔾g-continuous function and 𝔾g-irresolute function.
A Study on the Approximations of Bounded Functions in the Locally Global Spaces (L
δ

,P
), (0 < P ≤ 1)
Authors: Mohamed Nadia J 
Published: May 2021

Abstract
The purpose of the present paper is to evaluate the error of the approximation of the function
F
defined in [0,1] by Bernstein polynomial in
L

P

space (0 < P ≤ 1).
We study the direct relation between the degrees of approximation of Riemann integrable functions with respect to algebraic polynomials with average modulus of smoothness

τ

2

(
f
,
Δ

1

j

)

the locally global spaces (Lδ,P
), (0 < P ≤ 1) wich is importance for the approximations theory.
The Computational Complexity of the Elliptic Curve Factorization Algorithm over Real Field
Authors: Hashim Hashim Madlool , Ajeena Ruma Kareem K. 
Published: May 2021

Abstract
Several mathematical concepts from analytics number theory, especially the counting functions (CFs) are employed to solve some modern problems in mathematics, computer sciences, engineering and others. One of them is the factorization problem for integers into two primes. This work proposes an extended factorization problem using the CFs, as main part from analytics number theory, to factor a real number r into two primes p and q. The computations of the points doubling and addition on the elliptic curves E modulo a composite number n are also used in this extension to give new two versions of the factorization over real field R. On the first version, the primes are obtained from doubling and addition on elliptic curve points that are computed modulo composite number which is resulting as output of the CFs algorithm with the input r. Whereas, the primes, on the second version, are got directly from applying the CFs algorithm with r as input. The successful computation of the scalar multiplication kP on the elliptic curve E modulo primes are determined. The computational complexities of extended elliptic curve factorization versions are determined using the counting operations. These operations are elliptic curve and finite field operations. New numerical results on two versions are computed as study cases. The elliptic curve factorization algorithm over R (ECF-R) with two versions, is more efficient for factoring-based cryptography in comparing to the original ECM.
On Fuzzy (p, α, pα)-compact subspaces
Authors: Jaber S. M. , Mohsin M. Y. 
Published: May 2021

Abstract
In this paper, we study the relationships among fuzzy (compact, pre-compact, α-compact and pα-compact) subspaces; also we will discuss the relationships between fuzzy (compact, p-compact, α-compact and pα-compact) spaces and fuzzy (compact, precompact, α-compact and pα-compact) subspaces.
Wyle’s Vanishing Tensor of Nearly Cosymplectic Manifold
Authors: Mohammed Nawaf Jaber 
Published: May 2021

AbstractThe present paper focuses on the geometry of Wyle’s tensor of nearly cosymplecticb manifold. Inbparticular, the flatnessb properties of Wyle’s tensorb were traded. These propertiesb facilitated us tob identifyb the necessaryb and sufficient conditionb for nearly cosymplectic manifoldb to be an Einsteinb manifold.
Development of the complementary method to solve fractional linear programming problems.
Authors: Jaber Waleed Khalid , Hassan Isra’a H. , Khraibet Tahani Jabbar 
Published: May 2021

Abstract
In this paper we development of the complementary method to Solve Fractional Linear Programming Problems (FLPP), Instead of taking the Numerator and denominator elements and set them in in tables as D1 and D2, then calculating its value and the value of (Ze), hence we could minimize the tables and calculations in this method quickly and with fewer tables.
An Efficient Shrinkage Estimators For Generalized Inverse Rayleigh Distribution Based On Bounded And Series Stress-Strength Models
Authors: Jebur Iman Ghaji , Kalaf Bayda Atiya , Salman Abbas N. 
Published: May 2021

AbstractIn this paper, we investigate two stress-strength models (Bounded and Series) in systems reliability based on Generalized Inverse Rayleigh distribution. To obtain some estimates of shrinkage estimators, Bayesian methods under informative and non-informative assumptions are used. For comparison of the presented methods, Monte Carlo simulations based on the Mean squared Error criteria are applied.
Some Conceptions of Soft Topological Transitivity
Authors: Saied. A. J. , Baraa. A. B. 
Published: May 2021

Abstract
This paper is a summarized study of a soft transitivity and soft sensitivity of a soft continuous mappings on a soft topological spaces, where this study was confined to the purely soft topological aspect. Also, we discuss some basic soft topological techniques used soft-orbitity and soft-periodicity of a soft-point. On one hand, introduced a soft transitivity of a soft continuous mappings and provide a simplified overview of results on the topic, but on the other hand, it covers some of the recent developments. Finally, we introduce a new soft topology related to the soft transitivity of a soft continuous mappings on a soft compact soft set and the quest of soft density of soft-orbitity (soft density of periodicity) and using these notions, which are main results of our paper.
Transitions probabilities B(E2), B(M1) and B(E0) in 130Ba isotope
Authors: Muttaleb Mohsin Kadhim 
Published: May 2021

Abstract
Nuclear structure for even-even 130Ba isotope have been investigated. They examined carefully with IBM1 and IBM2. Low lying energy levels for even even positive parity states, reduced electric quadruple transitions probabilities B(E2), branching ratios, reduced magnetic dipole transitions probability B(M1), reduced electric monopole transitions probability B(E0), and mixing ratio X(E0/E2) have been studied.
In the framework of IBM1 noted the competition between the two parameters (a
0 and a
2) in 130Ba isotope was the increases of a0 associated with decreases of a2 which mean that the γ-unstable features in IBM2 χπ and χν were (-1.3 and 0.7) which signified similarity with IBM1 expected.130Ba isotope described to be transitional nucleus, transitional between SU(3) and O(6) features.
Study of Method to Booking e-tickets for Iraqi Stadiums using the Smartphone
Authors: Abed Qusay Abdullah 
Published: May 2021

Abstract
Currently, manual system is being used for the matches booking is too old which need great time and efforts from both of the customers whom used to wait in long queues to get their tickets and the stadium staff whom also spend a lot of time trying to organize the booking process. In addition, cash payment with all of its disadvantages is accepted. The proposed mobile ticketing system will provide an easy way for users to booking their e-tickets for their favorite matches from anywhere and anytime, only it needs to a personal computer or a smartphone and connect to an internet. Therefore, without the need to wait in long queues for a long time. The user will get his e-ticket in a way that will gain a lot of time and efforts for both of the users and the staff. In this study, “the Method of Booking e-tickets for Iraqi Stadiums using the Smartphone” will be introduce. The study has been implemented using five major steps. The prototype will go through Awareness of the problem that will happen through the interview with the person who is in charge at stadium, and the problems that you are trying to solve as well. The main interface of the system will contain some of the box to enter the information about the customers, thus they can make the booking easily. Development, evaluation are the last steps to finalize the system usefulness to be implement in real life. Nowadays, the mobile becomes the most important thing that plays main role in many activities that we need it in daily life. Therefore, this study will depend on a mobile phone application, which is expect to give ease and effectiveness to the users and the administrator’s requirements in saving time, cost and efforts.
Improved Random Forest Algorithm Performance For Big Data
Authors: Saadoon Yousif Abdulsattar , Abdulamir Riam Hossam 
Published: May 2021

AbstractIn this paper, the effectiveness of using random forest algorithm in the big data is studied. The reason for choosing this algorithm is because of its effective results in many previous studies, so it was chosen. The random forest algorithm was applied to the big data Internet of Things (IoT) dataset, with size 150,000 instances. After applying the algorithm, it gave an Accuracy score of 99.976%, and this indicates the effectiveness of the random forest algorithm in the big data. This result made the researcher search for one of the ways that increases the value of Accuracy, knowing that it is an excellent result. And use a filter to remove frequent values, and this helps reduce data volume and keep related data. After applying the filter with the random forest algorithm, the Accuracy value appeared at 99.998%, which indicates that it improved the random forest algorithm’s performance in the big data.
Effect of Square Shaped Acousto–Optic Modulators on the Bragg Diffraction
Authors: Khorsheed S M , Yaseen N M 
Published: May 2021

Abstract
The COMOSOL multiphysicsis used to design various optical systems, including the design of the acousto-optic modulator system. Its work depends on the special inputs of the program, such as the characteristics of the laser used and the frequencies of the sound waves. A square modulator was designed with dimensions 3x3 mm, and a quartz crystal was used, in which the interaction of light and sound occurs. Different number of orders diffraction are generated called the Bragg angle, and their number varies with different inputs. The modulator is created by entering the value of the radio frequency up to 100 volts. Through our results, the efficiency increases at the frequency of 400 kHz after changing the frequencies of 200, 300 and 400 kHz. The values of the stress are: 1.24 × 106
P
a, 1× 106
P
a, 3.8× 106
P
a, and the estimated shift is about 0.7, 0.4 and 0.9 mm, there were three frequency values considered: 200, 300, and 400 kHz. respectively. The far field shape show two orders are appeared at 200 kHz and 300 kHz frequencies they are: zero order and first order but they are different in the value of Bragg angles but in 400 kHz shown approximate three orders, they are: zero, first, and new generation of second order with the different in the value of Bragg angles.
Investigation The Quantum Chemical Parameters and Electronic Transition States for Suggested Platinum Metal Complex
Authors: Irzooqi Wisam Shareef , Sarsoh Shakir Diwan , Abbood Hamid Ibrahim 
Published: May 2021

Abstract
SDD basis sets were used in current work together with the hybrid B3LYP functional to investigate of suggested platinum metal complex. The results showed the complex under study likes the cisplatin complex in many of it is properties, they have large band gap with low electrochemical hardness and electronic softness. Based of cis-platin, the substitute of iso-indene rings in place of amine groups in cis-platin unaffected on the geometrical parameters of bonding the central platinum metal with chlorine atoms and the ligands, the suggested platinum complex keeps the coordination of metal complex with values of frontier molecular orbitals close to those for cisplatin. π →π* transition of states were appeared in the behavior of absorption spectrum for the complex under study.
Internet of Things for Education Field
Authors: Mohammed Ali Sura I. , Nihad Marwah 
Published: May 2021

Abstract
Tracking student attendance and location information are at the heart of a pervasive internet thing. Several approaches are used to identify student locations in the classroom, Infrastructure and increased services are considered expensive requirements and hardly meets the need for the required room-level location accuracy. An accuracy of specifying the student’s location by Smart Entity (inertial sensors on hand) of improving the quality of service. Location information forms a core context to determine student location. The location of classroom access control using different parameters provides useful information and improves teaching and learning in the educational organization. Based on the recent IoT integration of smart entities and sensors, this paper uses new value-added proposals to monitor the actions of students inside the classroom location.