bluuebunny/crossref_metadata_2025_split huggingface dataset:
A new energetics model for the assessment of the power‐duration relationship during over‐ground running
Authors: Vassallo Christian , Kilduff Liam P. , Cummins Cloe , Murphy Aron , Gray Adrian , Waldron Mark 
Published: May 2021

ABSTRACTWe evaluated the reliability of an over‐ground running three‐minute all‐out test (3MT) and compared this to traditional multiple‐visit testing to determine the critical speed (CS) and distance > CS (D´). Using a novel energetics model during the 3MT, critical power (CP) and work > CP (W´) were also evaluated for reliability and compared to the multiple‐visit tests. Over‐ground running speed was measured using Global Positioning Systems during fixed‐speed trials on a 400 m track to exhaustion, at four intensities corresponding to: (i) maximal oxygen uptake (Vmax), (ii) 110% , (iii) Δ70% (i.e. 70% of the difference between gas exchange threshold and Vmax) and (iv) Δ85%. The participants subsequently performed the 3MT across two days to determine its reliability. There were no differences between the multiple‐visit testing and the 3MT for CS (P = 0.328) and D´ (P = 0.919); however, CP (P = 0.02) and W´ (P < 0.001) were higher in the 3MT. The reliability of the 3MT was stable (P > 0.05) between trials for all variables, with coefficient of variation ranging from 2.0–8.1%. The current over‐ground energetics model can reliably estimate CP and W´ based on GPS speed data during the 3MT, which supports its use for most athletic training and monitoring purposes. The reliability of the over‐ground running 3MT for power‐ and speed‐related indices was sufficient to detect typical training adaptations; however, it may overestimate CP (∼ 25 W) and W´ (∼ 7 kJ) compared to multiple‐visit tests.
The astro-primordial black hole merger rates: a reappraisal
Authors: Kritos K. , De Luca V. , Franciolini G. , Kehagias A. , Riotto A. 
Published: May 2021

Abstract
Mainly motivated by the recent GW190521 mass gap event which we take as a benchmark point, we critically assess if binaries made of a primordial black hole and a black hole of astrophysical origin may form, merge in stellar clusters and reproduce the LIGO/Virgo detection rate.
While two previously studied mechanisms
— the direct capture and the three body induced — seem to be inefficient, we propose a new “catalysis” channel based on the idea that a subsequent chain of single-binary and binary-binary exchanges may lead to the formation of a high mass binary pairs and show that it may explain the recent GW190521 event if the local overdensity of primordial black holes in the globular cluster is larger than a few.
Bulk-edge correspondence in the Haldane phase of the bilinear-biquadratic spin-1 Hamiltonian
Authors: Roy Sudipto Singha , Santalla Silvia N , Rodríguez-Laguna Javier , Sierra Germán 
Published: May 2021

Abstract
The Haldane phase is the prototype of symmetry protected topological (SPT) phases of spin chain systems. It can be protected by several symmetries having in common the degeneracy of the entanglement spectrum (ES). Here we explore in depth this degeneracy for the spin-1 Affleck–Kennedy–Lieb–Tasaki and bilinear-biquadratic Hamiltonians and show the emergence of a bulk-edge correspondence that relates the low energy properties of the entanglement Hamiltonian of a periodic chain and that of the physical Hamiltonian of an open chain. We find that the ES can be described in terms of two spins-1/2 behaving as the effective spins at the end of the open chain. In the case of non-contiguous partitions, we find that the entanglement Hamiltonian is given by the spin-1/2 Heisenberg Hamiltonian, which suggests a relationship between SPT phases and conformal field theory. We finally investigate the string order parameter and the relation with the bulk-edge correspondence.
Solutions of the Yang–Baxter equation for (n + 1) (2n + 1)-vertex models using a differential approach
Authors: Vieira R S , Lima-Santos A 
Published: May 2021

Abstract
The formal derivatives of the Yang–Baxter equation with respect to its spectral parameters, evaluated at some fixed point of these parameters, provide us with two systems of differential equations. The derivatives of the R matrix elements, however, can be regarded as independent variables and eliminated from the systems, after which, two systems of polynomial equations are obtained in their place. In general, these polynomial systems have a non-zero Hilbert dimension, which means that not all elements of the R matrix can be fixed through them. Nevertheless, the remaining unknowns can be found by solving a few simple differential equations that arise as consistency conditions of the method. The branches of the solutions can also be easily analyzed by this method, which ensures the uniqueness and generality of the solutions. In this work, we consider the Yang–Baxter equation for (n + 1) (2n + 1)-vertex models with a generalization based on the A

n−1 symmetry. This differential approach allows us to solve the Yang–Baxter equation in a systematic way.
A combined model of aggregation, fragmentation, and exchange processes: insights from analytical calculations
Authors: Robson Dominic T , Baas Andreas C W , Annibale Alessia 
Published: May 2021

Abstract
We introduce a mean-field framework for the study of systems of interacting particles sharing a conserved quantity. The work generalises and unites the existing fields of asset-exchange models, often applied to socio-economic systems, and aggregation-fragmentation models, typically used in modelling the dynamics of clusters. An initial model includes only two-body collisions, which is then extended to include many-body collisions and spontaneous fragmentation. We derive self-consistency equations for the steady-state distribution, which can be solved using a population dynamics algorithm, as well as a full solution for the time evolution of the moments, corroborated with numerical simulations. The generality of the model makes it applicable to many problems and allows for the study of systems exhibiting more complex interactions that those typically considered. The work is relevant to the modelling of barchan dune fields in which interactions between the bedforms and spontaneous fragmentation due to changes in the wind are thought to lead to size-selection. Our work could also be applied in finding wealth distributions when agents can both combine assets as well as split into multiple subsidiaries.
Generalized Uniform Distribution Using the Exponential Quantile Function
Authors: Hussein Sarmad Rahman , Al-Kadim Kareema Abad 
Published: May 2021

Abstract
In Current research, the study suggested that distribution is using for the exponential quantile function to define the W distribution. Correspondingly, there are many general properties of T-X system of distributions are considered. As a result, this study was obtained a new aspect of distribution by deriving the T-X family equation. After that the study was covered different mathematical and statistical properties, as well as the moments Reliabilities Analysis,) failure, reverse hazard) rate of the distribution derived. The parameters were valued by the maximum likelihood method.
Estimation Parameters Of The Multiple Regression Using Bayesian Approach Based On The Normal Conjugate Function
Authors: Najm Adel Abbood , Abood Ahmed Hamza , Al-Sabbah Shrook A S 
Published: May 2021

Abstract
In this paper, we have been used Bayes Technique depending on the normal conjugate function to estimate parameters of the multiple regression model, and we have been tested significance of this model. The test showed in the application that the mean square error (MSE) for the used model was decreasing, also it showed that the determinant coefficient is increasing highly. In the same time, value of the computed F-test was significant according to the above we can consider that the model is significant
A New Hybrid Meta-Heuristics Algorithms to Solve APP Problems
Authors: Kalaf Bayda Atiya , Mohammed Ghadeer Jasim , Salman Muna D. 
Published: May 2021

Abstract
In this paper, a new hybrid algorithm for linear programming model based on Aggregate production planning problems is proposed. The new hybrid algorithm of a simulated annealing (SA) and particle swarm optimization (PSO) algorithms. PSO algorithm employed for a good balance between exploration and exploitation in SA in order to be effective and efficient (speed and quality) for solving linear programming model. Finding results show that the proposed approach is achieving within a reasonable computational time comparing with PSO and SA algorithms.
Stability of GARCH models for prediction the exchange rate based on machine learning with time-varying
Authors: Dikheel Tahir R , Sami sura H 
Published: May 2021

Abstract
Recently, machine learning methods such as regression trees, Support Vector Machine and lasso have been widely used in many scientific fields where the variance of the random errors is homogenous or constant. This issue is disagreement with the data that is based on the time, such as financial data which is analysis by using time series. Unfortunately, the financial time series is instable as a result of fluctuations that happen during different time periods between relative calm and high turbulence. A great effort was paid in the literature to tackle this problem by combining machine learning with GARCH model. In this paper, we suggest estimating the variance of varying-time and parameters of machine learning methods to predict the exchange rate of the Iraqi dinar (IQD) against (USD) with using an iterative procedure. Real data and simulation study are curried out to know the performance of our proposed procedure with others. The result shows that our proposed procedure outperforms than others.
Estimation the vasicek interest rate model driven by fractional Lévy processes with application
Authors: Al-Saadony M F , Al-Obaidi W J 
Published: May 2021

Abstract
In this article, we present that fractional Lévy processes which is very an important field in both probability theory and its application in recent years. The fractional Brownian motion is suggested as the fractional Lévy processes in this article. We will make parameters estimate of the Vasicek process driven by fractional Brownian motion, that represented the short memory parameter (0 < H < ½) and the long memory parameter (½ < H < 1). So, Our aim is to study the behavior of stochastitc Vasicek Interest driven by fractional Brownian motion. We use maximum likelihood to estimate the drift, diffusion and Hurst parameters and generally the fractional Lévy processes. We illustrate our methods, and show the behavior of stochastic parameters using simulation and real data (ISX60).
Generalized ridge estimator in negative binomial regression model
Authors: Rashad Nadwa Khazaal , Hammood Nawal Mahmood , Algamal Zakariya Yahya 
Published: May 2021

Abstract
The ridge estimator has been consistently demonstrated to be an attractive shrinkage method to reduce the effects of multicollinearity. The negative binomial regression model (NBRM) is a well-known model in application when the response variable is a count data with overdispersion. However, it is known that the variance of maximum likelihood estimator (MLE) of the NBRM coefficients can negatively affected in the presence of multicollinearity. In this paper, the generalized ridge estimator is proposed to overcome the limitation of ridge estimator. Several methods for estimating the shrinkage matrix have been adapted. Our Monte Carlo simulation results suggest that the proposed estimator, regardless the type of estimating method of shrinkage matrix is better than the MLE estimator and ridge estimator, in terms of MSE. In addition, some estimating method of shrinkage matrix can bring significant improvement relative to others.
Compare Between Histogram Similarity and Histogram Differencing For More Brief Key Frames Extraction from Video Stream
Authors: Naser Ekhlas Falih 
Published: May 2021

Abstract
Speedy increase in the employ of the content of multimedia is very commonly perceived in existing generations. Video is one of the extreme exceedingly recovered data of multimedia which can provide quick fixes and immediate gratification for whole the kinds of user information willingness. Detection of Key frame from Videos and classification of videos are the necessary protocols in the complements tasks of video retrieval. The aim of this research is to compare between histogram similarity and histogram differencing for more brief key frames extraction from video stream. The suggested system for key frame extraction has three steps. Firstly, the video frames series will take and the characteristics for points of interest are elicited utilizing SUSAN detector. After eliciting interest characteristics from all video frames images, secondly, K-Means clustering technique was utilized for these features to construct the clusters with a number of interest points. Thirdly, a histogram builds for each video frame based on numbers of features in each cluster. X-axis of a histogram represents the cluster number and y-axis represents the number of features in each cluster. For key frames extraction, numbers for each cluster can be offered and a query histogram can be constructed based on entered clusters’ numbers. A query histogram was matched with every video frame histogram using Manhattan distance to discover the similar histogram to query histogram. After chosen similar histogram, it can extract all key frames from that video frames. The experimental results show that the number of key frames extracted from the video is very brief when using the histogram similarity compared to the histogram differencing. For example, the number of key frames extracted from a car video is 70 when using the histogram similarity, while it is 180 when using the histogram differencing.
Object tracking based stereo vision
Authors: Alsalhi Israa Nasir 
Published: May 2021

Abstract
In this paper, we described a new method for moving objects (detection and tracking). The first step to determine the object tracking is the segmentation process through getting a background image and then comparing it with the foreground image. Separation of the background image from the foreground image is the result of this step to obtain an object. In further step, enhance the segmentation operation by using morphology to remove small noise. Finally, select the largest object, center and radius of the largest. Therefore, we can detect the object perfectly and then the tracking of all objects. In this process for finding out the location of the target, we observed less error in detection and was very accurate.
A Review: Isolated Arabic Words Recognition Using Artificial Intelligent Techniques
Authors: Shareef S R , Irhayim Y F 
Published: May 2021

Abstract
In recent few years, deep learning has fast growing in many fields as natural language processing, image recognition, handwriting recognition, computer vision, and speech recognition. Automatic speech recognition (ASR) is a technique that refers to translating spoken words from an acoustic waveform into a text equivalent to what the speaker says. More recently, the advances in deep learning can support ASR in improving the performance of systems accuracies. Arabic is a Semitic language, one of the oldest used and most communicated languages in the world. But, it least concentrated in the case of Arabic speech recognition and under-resourced languages. This paper presents a survey that focuses on an automatic speech recognition system based on isolating words technique for Arabic speech. It also highlights the facilities and tools for developing speech recognition systems. This work is intended to be a useful starting point for those who are interested in ASR.
Using Artificial Intelligence Methods For Diagnosis Of Gingivitis Diseases
Authors: Khaleel Baydaa I. , Aziz Mohammad Salim 
Published: May 2021

Abstract
Artificial Intelligence Techniques, and image processing are playing a major role in medical science. In this paper, several methods of artificial intelligence techniques were used to diagnose Gingivitis disease. The Bat swarm algorithm, the Self-Organizing Map(SOM) algorithm and the Fuzzy Self-Organizing Map (FSOM)network algorithm were used to diagnose Gingivitis disease. Also, was used the traditional algorithm, which is the Principal Component Analysis (PCA) algorithm, for Feature Extraction of Gingivitis disease images. We compute the diagnostic accuracy on this images dataset. Next, we compared the final results of these three methods used and applied to this data. In this paper the best of these methods is the BAT, because in testing state the BAT was obtained higher accuracy for diagnose of Gingivitis disease equal (97.942%).
Improved variational iteration method with the trapezoidal rule to solve fractional ordinary differential equations
Authors: Hamed Almutasim Abdulmuhsin , Entesar Ahmed , Al-Rawi Ekhlass S 
Published: May 2021

Abstract
In this work, a combined technique the Variation Iteration Method (VIM) with the Trapezoidal Rule (TR) was recommend to solve linear and nonlinear fractional ordinary differential equations (F.O.D.E.), where the results obtained from the Variation Iteration method were improved, and numerical results were obtained by determining the maximum absolute errors (MAE) and mean square error (MSE) for the given examples. As the results It is proved that that the proposed method is better than the default method.
Nano αg
Ị-open set
Authors: Esmaeel R B , Saeed Sufyan G 
Published: May 2021

Abstract
The main objective of this paper is define the notion Nano-αg
Ị-open set by using nano topological space and some properties of this set are studied also, nano-αg
Ị-β set and nano-αg
Ị-θ-closed set are two concepts that are defied by using Nano-αg
Ị-open set many examples have been cited two indicate that the reverse of the proposition and remarks is not true. Also an applied example was presented explains how to benefit from nano-αg
Ị- set.
On Soft Pre-Generalized-Closed Sets with New near Soft function
Authors: Hammood A A , Esmaeel R B 
Published: May 2021

Abstract
The aim of this work is to study new sets of soft closed and soft open sets by using soft pre-open sets with collection of a soft ideal which is said to be an a soft-ᶅ-pre-g-closed and soft-ᶅ- pre-g-open sets with some properties, examples and relationships between these concepts with soft pre-g * - closed and soft pre-g *-open.
New concepts of soft open and soft closed functions are defined by using these sets with some examples and scheme. Also, many continuous function by using these with examples and schemes are explained.
The Stability Analysis of the diseased predator-prey model incorporating migration in the contaminated environment
Authors: Abdulkadhim Murtadha M , Al-Husseiny Hassan Fadhil 
Published: May 2021

Abstract
We proposed and analyzed a predator–prey model. The disease effects in predator due to pollution in environment, as well the immigration factor effected is discussed. We assumed that, the population are divided into three parts prey, susceptible predator and infected predator. Firstly, the existence, uniqueness and bounded-ness of the solution of the model are discussed. Secondly, we studied the existence and local stability of all equilibrium points. Furthermore, some of the Sufficient conditions of the global stability of the positive equilibrium are established using suitable Lyapunov functions. Finally, those theoretical results are demonstrated with numerical simulations.
Metrizability of Pseudo Topological Vector Spaces
Authors: Harbi Intesar , Al-Nafie Z D 
Published: May 2021

Abstract
In the present work, we introduce the notion of pseudo-seminorm, then we established, a criterion for the metrizability of a pseudo vector space 𝛯 with a pseudo topology 𝜏. It is specified, that for the metrizability of 𝛯 is necessary and sufficient that 𝛯 is first countable. Moreover, a sufficient condition for existence a base for the filter of neighborhoods of zero is proved and demonstrated that this condition introduces a compatible pseudo topology with the algebraic vector space structures.
Peristaltic Transport and Heat and Mass Transfer on a Power-law Fluid Flow in an Elastic Tapered Tube with Variable Cross-Section Induced by Dilating Peristaltic Wave
Authors: Murad Mohammed Ali , Abdulhadi Ahmed M 
Published: May 2021

Abstract
Peristaltic transport and heat and mass transfer on a power-law fluid flow in an elastic tapered tube with variable cross-section induced by dilating peristaltic wave was illustrated in this paper. Problem was studied under the assumption of long wavelength (δ ≪ 1) and low Reynolds number (Re ≪ 1). The different emerging parameters effect are explained graphically for the exact solutions of the temperature distribution, heat transfer coefficient, rate of heat transfer and concentration of particles. The results showed that the temperature distribution and heat transfer coefficient are an increasing functions of the parameters power-law index n, dilation parameter k, amplitude ratio ϕ and volume of flow rate F whereas they are decreasing functions when the non-uniform parameter b increases. It is noted an opposite behaviour for the rate of heat transfer and concentration distribution. MATHEMATICA software is used to plot all figures.
Mn – polynomials of general thorn path graph
Authors: Mustafa Raghad A , Ali Ahmed M , Khidhir Abdul Sattar M 
Published: May 2021

Abstract
Let G = (V(G), E(G)) be any connected simple graph and S be any subset of V(G) such that the cardinality of S is n – 1, n ≥ 3. The maximum distance between a vertex ν, ν ∈ V(G) and S(S ⊆ V (G) is the maximum distance between ν and u for all u ∈ S such that the vertex ν is not belong to S, that is:

d

max

(
v
,
S
)
=
max
{
d
(
v
,
u
)
:
u
∈
S
}
,

|

S

|

=
n
−
1
,
3
≤
n
≤
p
,
v
∉
S
.

.
The maximum polynomial “Mn
– polynomial” of G which denoted by Mn (G;x) and defined by:

M

n

(
G
;
x
)

=

∑

k
=
m

δ

max
⁡

(
G
,
n
)

C

n

(
G
,
k
)

x

K

,

, where m = min{d

max
(ν,S),ν ∈ V – S, S ⊆ V} and C
n(G,K) be the number of pairs (ν,S), S ⊆ V(G), |S| = n – 1,3 ≤ n ≤ p, p = |V(G)| such that d

max
(ν,S) = k, for each m ≤ k ≤ δ

max
(G,n) and δ
max (G,n) = max

u∈V
{d

max
(u,S)}.
In this paper, we find the Mn
–polynomial and Hosoya polynomial for general thorn path and obtained some results.
Parameter estimation of a truncated regression model based on improving numerical optimization algorithms
Authors: Jameel Marwan Saleh , Basheer Ghalya Tawfeeq , Al-Bayati Abbas Y. , Algamal Zakariya Yahya 
Published: May 2021

Abstract
Limited dependent variable models, including truncated regression models, have traditionally been estimated by the method of maximum likelihood. The conventional optimization algorithms; which is known as Quasi-Newton algorithm namely BFGS Quasi-Newton algorithm is used to reach the optimum values for estimated parameters. In this paper, the nature-inspired algorithm is employed to improve the numerical optimization algorithms to better estimation. Our Monte Carlo simulation results suggest that our proposed improving can bring significant improvement relative to others, in terms of mean squared error and prediction mean squared error.
Common Fixed Point for a Pair of Asymptotically Nonexpansive and Multivalued Mapping Under Fibonacci Iteration Sequence in CAT (0) Space
Authors: Malih Sabah Hassan 
Published: May 2021

Abstract
In this paper, we present a new iterations scheme for△ - convergence theorems of asymptotically and multivalued nonexpansive mapping in𝐶𝐴𝑇(0) spaces under the Fibonacci sequence