bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of Liquid Feeding Rate on Carbonation of Precipitated Calcium Carbonate via Continuous Method
Authors: Salleh Emee Marina , Othman Rohaya , Mahim Zawawi , Sabri Siti Noorzidah 
Published: November 2021

Abstract
Precipitated calcium carbonate (PCC) is an innovative product generated from lime that significantly offers various functional characteristics in fulfilling numerous market demand. PCC is produced by hydrating high-calcium quicklime resulting slurry so-called milk-of-lime and reacting the slurry with carbon dioxide (CO2) via carbonation process. The resulting PCC product is extremely white and typically has a uniform narrow particle size distribution. PCC is available in various crystal morphologies and sizes, which can be tailored to optimize performance in a specific application. The final properties of the PCC can be diversified by controlling processing parameters. In this current work, effect of liquid air pressure corresponding to feeding rate on a formation of PCC was investigated. In enhancing the product yield, the quicklime was initially converted into a solution containing calcium ion (Ca2+) using natural promoter agent. Subsequently, CO2 gas was continuously supplied into the Ca-rich ionic solution, thus inducing carbonation reaction to form PCC. This present work showed the carbonation time of producing PCC was effectively reduced as a function of feeding rate from 15 minutes at 10 psi to only 7 minutes at 50 psi. The PCC yield slightly increased from 19 g to 23 g with increasing the feeding rate from 10 psi to 50 psi, respectively. Morphologically, the PCC particles were dominated by rhombohedral structures at various feeding rates with an indication of intergrowth mechanism. This current finding signified the increasing feeding rate offered a significant reduction of PCC production time that might be efficiently applied by the industrial manufacturers.
Effect of varying phosphate content on the structure and properties of sol-gel derived SiO2-CaO-P2O5 bio-glass
Authors: Syed Adam Syed Nuzul Fadzli , Zainuddin Firuz , Osman Azlin Fazlina 
Published: November 2021

Abstract
In this work, biocompatible glass (bioglass) particles were prepared by low temperature, acid catalysed sol-gel method. The effect of varying phosphate (P2O5) content (10, 15 and 20 mol %) in the sol-gel derived glass composition were studied. The sol-gel derived bioglass particles were compacted into cylindrical pellets via hydraulic press machine and sintered at 600°C for 3 hours. The bioglass particulates were analysed by x-ray fluorescence (XRF), Fourier Transformed Infrared (FTIR), X-Ray Diffraction (XRD) and nitrogen gas adsorption. Meanwhile, the sintered bioglass pellets were analysed by FTIR, XRD and FESEM-EDX. Furthermore, in vitro bioactivity analysis was performed by immersion in simulated body fluid (SBF) for 14 days. Bioglass particulates with high glassy phase, high surface area and high porosities were obtained for all compositions. Increasing of phosphate content to 20 mol% particularly reduced the porous characteristics of the bioglass particulates. Furthermore, leads to higher bridging oxygen (BO) atoms, higher amorphous silicate networks, lower glass crystallinity and higher number of phosphate crystallites within the amorphous glassy matrix. Increased to 20 mol% of phosphate also reduced the ability of the bioglass surface to induce carbonated apatite formation when immersed in simulated body fluid (SBF) solution.
Ultrasound-Assisted Surface Modifications on Ceramic Reinforcement for Lead-Free Composite Solders : Short Review
Authors: Leong Wai Keong , Mohamad Ahmad Azmin , Nazeri Muhammad Firdaus 
Published: November 2021

Abstract
The purpose of this paper is to review and examine the effect of ultrasound-assisted surface modifications of ceramic reinforcements on the properties of lead-free solders. The discussion will highlight the fundamental understanding, main parameters, configurations, and recent surface-modified ceramic reinforced composite lead-free solder developments. The review also identified and summarized the advantages, current trends, and significant findings in this field. The ultrasound-assisted surface modification was found to provide a crucial improvement on the wettability properties of molten solders as the matrix phase on the ceramic reinforcement. Further, the excellent distribution of ceramic reinforcement in solder matrix was also seen after the surface modification process. This has led to significant improvements in mechanical properties such as hardness and strength. The pinning of dislocation movement was seen as the reason for improving the mechanical properties. This positive impact in enhancing the ceramic reinforcement-solder interfacial reaction allows more explicit future research directions and opportunities for composite solder applications.
The Effectivity of Oil Palm Inhibitor Processed by Aminolysis to Control Corrosion on Steel in Sodium Chloride Environment
Authors: Hastuty Sri , Prasetyo Himawan Agus , Kirana Norma Nindya , Nugroho Agung , Oktaviano Haryo Satriya , Awwaluddin Muhammad 
Published: November 2021

Abstract
A green inhibitor based on Palm kernel oil (PKO) was prepared to investigate its corrosion inhibition behaviour against steel ASTM A36 in sodium chloride solution. The aminolysis method was used to synthesize the green inhibitor and produced fatty acid diethanolamine. Afterwards, the mixture of PKO and diethanolamine of 1:6 and 1:20 were prepared. These mixtures were added into sodium chloride solution with concentration 50, 100, 500, and 1,000 ppm and they were used as working solution in corrosion testing. Corrosion testing was conducted using anodic polarization. The confirmation of microstructure of steels surfaces were done by optical microscope. The results obtained from corrosion testing showed that inhibitors of palm oil, especially palm kernel oil (PKO), provided a good corrosion protection effect. The present work provided very promising results in the preparation of green corrosion inhibitors.
The use of ground & ultrasonicated dolomite (GUD) for improving the tensile performance of Poly (ethylene-co-vinyl acetate) copolymer composite
Authors: Fauzi Asfa Amalia Ahmad , Osman Azlin Fazlina , Halim Khairul Anwar Abdul , Mustafa Zaleha , Alakrach Abdulkader M. , Salleh Mohd Nazry 
Published: November 2021

Abstract
The combination of the organic and inorganic materials to fabricate a new form of material called ‘composite’ has been performed since several decades ago. However, the strategy to improve the homogeneity of the resultant composite system is still being the main focus of current research. In this study, dolomite and poly (ethylene-co-vinyl acetate) (PEVAc) were employed as filler and matrix, respectively. Dolomite was ground and ultrasonicated before being used as filler. It can be observed that the size of dolomite particles has been reduced significantly upon the grinding and ultrasonication processes. The effect of ground and ultrasonicated dolomite (GUD) addition on the mechanical performance of the PEVAc copolymer was investigated. Results indicate that the GUD filler has successfully increased the tensile strength, elongation at break, modulus of elasticity and tensile toughness of the PEVAc copolymer when being employed in 1 wt%. However, the use of higher content of GUD resulted in the decreasing trend of those properties. This shows that the ground and ultrasonicated dolomite with smaller and higher surface area particles than its pristine form could bring improvement to the mechanical performance of the copolymer when being used in low loading as it can be more easily dispersed in the copolymer matrix.
Accuracy and Bias of the Rasch Rating Scale Person Estimates using Maximum Likelihood Approach: A Comparative Study of Various Sample Sizes
Authors: Azizan Nurul Hafizah , Mahmud Zamalia , Rambli Adzhar 
Published: November 2021

Abstract
The focus of this article is to evaluate the maximum likelihood estimation (MLE) performance in estimating the person parameters in the Rasch rating scale model (RRSM). For that purpose, 1000 iterations of the Markov Chain Monte Carlo (MCMC) simulation technique were performed based on a different number of sample sizes and several number of items. The performance of MLE in estimating the person parameters according to the different number of sample sizes was compared through accuracy and bias measures. Root mean square error (RMSE) and mean absolute error (MAE) were used to examine the accuracy of the estimates, while bias in estimation was assessed through the mean difference of estimates and true values of the person parameters. The simulated survey data sets in this study were generated according to the RRSM under the assumption of normality was satisfied. Results from the simulation analysis showed that in comparison to the larger sample sizes, smaller sample sizes tend to produce higher RMSE and MAE. In addition, the maximum likelihood estimates of the person parameters in smaller sample sizes also recorded a higher value of the mean difference of the person estimates and its true values compared to larger sample sizes. Findings from this study imply that the use of the MLE approach in small sample sizes results in less accurate and highly biased person estimates across the number of items.
The Effect of Chemical Parameters on Water Quality Index in Machine Learning Studies: A Meta-Analysis
Authors: Malek Nur Hanisah Abdul , Yaacob Wan Fairos Wan , Nasir Syerina Azlin Md , Shaadan Norshahida 
Published: November 2021

Abstract
According to the World Health Organization (WHO), approximately 2 billion people worldwide use drinking water sources that are contaminated with faeces. This is a serious issue since contaminated water may lead to certain waterborne diseases such as cholera, hepatitis A, dysentery, jaundice, and typhoid fever. Therefore, many researchers around the world are interested in studying the water quality. One of the most commonly used approaches is by using machine learning. Machine learning approach has grabbed the interest of many researchers since the last several years due to its power to compute complicated mathematical computations on big data analysis. Therefore, this study explored the correlation between different water quality parameters and Water Quality Index (WQI) in water quality studies that used machine learning by using a meta-analysis approach. This study used estimated variance, heterogeneity index, Chi-squared heterogeneity test and the random effects model. Based on the selected articles, pH, dissolved oxygen (DO) and biochemical oxygen demand (BOD) are the parameters commonly used in water quality studies which use a machine learning approach. This study found that pH is the best chemical factor which greatly affects the Water Quality Index since it has the highest mean correlation and lowest estimated variance due to sampling error. The result showed that the correlation between pH and WQI are heterogeneous across studies based on the Chi-squared of heterogeneity, Q and heterogeneity index, I2
value. The 95% confidence interval of effect summary supports the findings that the correlation of pH is different among the studies. This study also found that there is no evidence of publication bias using Egger and Begg’s test. Therefore, in order to ensure good water quality supply, the local authorities and government agencies should give more attention to this parameter since pH of water plays an important role in determining the water quality status.
Identification of Inhomogeneous Temperature on Stainless Steel using Statistical Analysis
Authors: Afrianti Yuli Sri , Ardy Husaini , Pasaribu Udjianna Sekteria , Latief Fourier Dzar Eljabbar 
Published: November 2021

Abstract
Corrosion in stainless steel, abbreviated as SS, is still an exciting topic to study. Even though SS is a corrosion resistance material, this property will be degraded when exposed to high temperatures for a long time because of σ phase, such as a Fe-Cr compound, formation. The presence of this phase can be observed using a special chemical etchant solution that will give five specific colours to this phase: light brown, dark brown, bluish brown, light blue, and dark blue. In this study, the specimen sample is from ASTM A297. Furthermore, the metallography process is carried out to obtain microstructure images that describe the σ phase. Here, two grains were taken as objects to discretize with one of them was around the specimen sample center and the other was close to the boundary with the environment. The discretization resulted in a 2 x 5 frequency table, called contingency table, that is analysed by the independence χ2-test. The contingency table is also represented geometrically in cartesian. The study shows that two grains were not independent. The grain which was around the specimen sample center contained many σ phases dominated by light blue colour (43%). In other words, the prolonged heating did not give homogeneous corrosion level.
Global Warming in Cameron Highlands: Forecasting its Temperature Level via ARIMA vs ARAR
Authors: Zamri Nurzawanah Raihah , Azmi Nurul Nisa’ Khairol 
Published: November 2021

Abstract
The average global temperature has increased at a rapid rate over the past 50 years leading to global warming. The impact of climate change can be felt across the continents. In this research, analysis was conducted to model and forecast the monthly temperature of Cameron Highlands in 2020 and 2021, against its historical monthly average temperature from January 1990 until December 2019. Two (2) methods namely (i) Seasonal Autoregressive Integrated Moving Average (SARIMA) model and (ii) Autoregressive Autoregressive (ARAR) algorithm were compared to determine the best model to forecast the monthly temperature of Cameron Highlands. SARIMA (1,1,2)(1,1,1)12 was found to be the best at forecasting the monthly temperature in Cameron Highlands as RMSE and MAPE values were lower than ARAR. In year 2021, the temperature in Cameron Highlands is estimated to increase by 1.6 °C. The result of the forecast showed that its monthly temperature was expected to increase in the next two (2) years. Hence, this calls for serious action to be taken by higher authorities.
Machine Learning Models for COVID-19 Confirmed Cases Prediction: A Meta-Analysis Approach
Authors: Yaacob Wan Fairos Wan , Sobri Norafefah Mohamad , Nasir Syerina Azlin Md , Nordin Noor Ilanie , Yaacob Wan Faizah Wan , Mukhaiyar Utriweni 
Published: November 2021

Abstract
COVID-19, CoronaVirus Disease – 2019, belongs to the genus of Coronaviridae. COVID-19 is no longer pandemic but rather endemic with the number of deaths around the world of more than 3,166,516 cases. This reality has placed a massive burden on limited healthcare systems. Thus, many researchers try to develop a prediction model to further understand this phenomenon. One of the recent methods used is machine learning models that learn from the historical data and make predictions about the events. These data mining techniques have been used to predict the number of confirmed cases of COVID-19. This paper investigated the variability of the effect size on the correlation performance of machine learning models in predicting confirmed cases of COVID-19 using meta-analysis. It explored the correlation between actual and predicted COVID-19 cases from different Neural Network machine learning models by means of estimated variance, chi-square heterogeneity (Q), heterogeneity index (I2) and random effect model. The results gave a good summary effect of 95% confidence interval. Based on chi-square heterogeneity (Q) and heterogeneity index (I2), it was found that the correlations were heterogeneous among the studies. The 95% confidence interval of effect summary also supported the difference in correlation between actual and predicted number of confirmed COVID-19 cases among the studies. There was no evidence of publication bias based on funnel plot and Egger and Begg’s test. Hence, findings from this study provide evidence of good prediction performance from the Neural Network model based on a combination of studies that can later serve in the prediction of COVID-19 confirmed cases.
Ethnomathematics values in Temple of Heaven: An Imperial Sacrificial Altar in Beijing, China
Authors: Zhang Cheng , Wijaya Tommy Tanu , Zhou Ying , Chen Jihe , Ning Yimin 
Published: November 2021

Abstract
Many studies are proving that learning mathematics with an ethnomathematical approach can improve students’ mathematical skills. Developing and using ethnomathematics concepts are important to raise history and cultural awareness of mathematics. This study aims to analyse the ethnomathematics values of the Temple of Heaven. Temple of Heaven is one of the famous heritage sites in Beijing, China, which bears many ethnomathematics concepts. The researchers applied a qualitative method in this study. The subject of this research is the Temple of Heaven building that is located in Beijing, China. Researchers identified the geometrical concept present in the exterior, interior design, and building structure of the Temple of Heaven building. This research shows the existence of mathematical concepts in the architecture of the Temple of Heaven. This research result can help teachers in making mathematical practice questions with ethnomathematics concepts.
Analysing an Optimal Angle in Basketball Free Throw
Authors: Nor-Al-Din Siti Musliha , Shamsuddin Nik Nur Sharina , Noor Khairiah Razali , Sukri Nursyazni Mohamad 
Published: November 2021

Abstract
Basketball is a sport, played worldwide by people of all ages, from young to old. The most important skill that a football player should have is shooting. Shooting the ball into the hoop involves projectile motion. The ability of a player to shoot will determine the scores of his/her team. The angle and initial velocity taken during the shooting, plays a vital role, so that a perfect shooting could be achieved. This work has been conducted to determine the optimal throwing angle and initial velocity that a player should take in order to get the best shooting. The relationship of these factors were investigated: the throwing angle and player’s height, initial velocity with the player’s height, as well as the throwing angles versus time taken for the ball to reach the hoop. Our focus is to maximize the height of the ball, before it is thrown. Newton’s law and the concept of projectile motion were applied using a calculus-based model. Relationship between the player’s height with the initial velocity, optimal throwing angle and time taken for the ball to reach the hoop were discussed. Perfect optimal release angle were determined for thirty data of NBA players. It shows that the player’s height is inversely proportional to the initial velocity and the optimal throwing angle. The obtained results also concluded that the optimal throwing angle is directly proportional to the time taken for a ball to reach its maximum height.
Cubic Curve Fitting Method in Reconstruction of Chinese Calligraphy Outline
Authors: Razali Noor Khairiah Binti , Draman Nur Nabilah Binti Che , Nor-Al-Din Siti Musliha Binti , Sukri Nursyazni Binti Mohamad 
Published: November 2021

Abstract
Curve plays a significant role in CAGD and brings the good impact of computers to manufacturing industries in designing 2 and 3-dimensional shapes and objects. Reconstruction of Chinese calligraphy outline based on the actual character is presented in this paper. Chinese calligraphy is the stylized artistic writings of Chinese characters. It is believed that this writing may help to express the feelings and ideas of the writers, which are difficult to be described. The shapes, smooth lines, and perfect curves are among the important qualities which are particularly emphasized in selecting good Chinese calligraphy. The Cubic B-Spline, Cubic Trigonometric Spline, and Cubic Trigonometric Bezier were used to generate the curves. The factors that have influenced the effects of the curves modifications were examined based on the changes of control polygon and the values of shape parameter. The fastest approach was then chosen by measuring the processing time required to construct the complete design. Results show the Cubic Trigonometric Bezier curve produced the closest curves to the control polygon, accurate to the actual character with λ = 1 and CPU time taken is 2.032 seconds. This is followed by Cubic Trigonometric Spline and Cubic B-Spline.
Aerodynamic investigation on shifted-back vertical stroke plane of flapping wing in forward flight
Authors: Han Jong-Seob , Breitsamter Christian 
Published: November 2021

Abstract
In order to properly understand aerodynamic characteristics in a flapping wing in forward flight, additional aerodynamic parameters apart from those in hover—an inclined stroke plane, a shifted-back stroke plane, and an advance ratio—must be comprehended in advance. This paper deals with the aerodynamic characteristics of a flapping wing in a shifted-back vertical stroke plane in freestream. A scaled-up robotic arm in a water towing tank was used to collect time-varying forces of a model flapping wing, and a semi-empirical quasi-steady aerodynamic model, which can decompose the forces into steady, quasi-steady, and unsteady components, was used to estimate the forces of the model flapping wing. It was found that the shifted-back stroke plane left a part of freestream as a non-perpendicular component, giving rise to a time-course change in the aerodynamic forces during the stroke. This also brought out two quasi-steady components (rotational and added-mass forces) apart from the steady one, even the wing moved with a constant stroke velocity. The aerodynamic model underestimated the actual forces of the model flapping wing even it can cover the increasingly distributed angle of attack of the vertical stroke plane with a blade element theory. The locations of the centers of pressure suggested a greater pressure gradient and an elongated leading-edge vortex along a wingspan than that of the estimation, which may explain the higher actual force in forward flight.
Equilibria and condensates in Rossby and drift wave turbulence
Authors: Skipp Jonathan , Nazarenko Sergey 
Published: November 2021

Abstract
We study the thermodynamic equilibrium spectra of the Charney–Hasegawa–Mima (CHM) equation in its weakly nonlinear limit. In this limit, the equation has three adiabatic invariants, in contrast to the two invariants of the 2D Euler or Gross–Pitaevskii equations, which are examples for comparison. We explore how the third invariant considerably enriches the variety of equilibrium spectra that the CHM system can access. In particular we characterise the singular limits of these spectra in which condensates occur, i.e. a single Fourier mode (or pair of modes) accumulate(s) a macroscopic fraction of the total invariants. We show that these equilibrium condensates provide a simple explanation for the characteristic structures observed in CHM systems of finite size: highly anisotropic zonal flows, large-scale isotropic vortices, and vortices at small scale. We show how these condensates are associated with combinations of negative thermodynamic potentials (e.g. temperature).