bluuebunny/crossref_metadata_2025_split huggingface dataset:
Solidification Behaviour of Sn-40Pb Lead Solder and Sn-0.7Cu Lead-free Solder
Authors: Teoh A L , Mohd Salleh M A A , Nazri S F , Halin D S C , Foo K L 
Published: July 2020

Abstract
Lead-free solder, especially Sn-0.7Cu has been evolving due to the restriction of the lead solder usage which is environmental and health unfriendly. However, most of the lead solder properties show a better result compared to the lead-free solder. To further improve the properties of lead-free solder, the solidification state of Sn-40Pb and Sn-0.7Cu, which is one of the important behaviour in thermal analysis that affects the solder properties and performance, was investigated and compared in this study by natural cooling curve method. The result showed that Sn-40Pb has two nucleation phase while Sn-0.7Cu has only one during the solidification. The primary lead-rich phase was first nucleated in Sn-40Pb following by the secondary tin-rich phase when cooling; while the phase of Cu6Sn5 was nucleated in Sn-0.7Cu. In addition, it is found that the undercooling of Sn-40Pb is lower than Sn-0.7Cu in the cooling curve.
Photocatalytic Activity of ZnO-doped Geopolymer Paste
Authors: Zailan S N , Mahmed N , Abdullah M M A 
Published: July 2020

Abstract
This study aims to investigate the photocatalytic activity of ZnO nanoparticles as photocatalyst material which was doped onto a geopolymer paste. ZnO-doped geopolymer paste were prepared by mixing Class F fly ash and various amount of ZnO nanoparticles with alkali activator, which is combination of sodium hydroxide solution with sodium silicate. Meanwhile, geopolymer paste without ZnO was produced by mixing Class F fly ash and alkali activator. Then, both samples were cured in room temperature and aged for 28 days. The photocatalytic activity for geopolymer paste with and without ZnO nanoparticles were evaluated and compared through photocatalytic testing and discolouration testing. The experimental results revealed that, as increasing the amount of addition ZnO nanoparticles, the degradation of methylene blue also was increased. However, mineralogical determination of ZnO-doped geopolymer paste were characterized using X-ray Diffraction (XRD).
Corrosion Control by Using Aluminium as Sacrificial Anode Cathodic Protection (SACP) in Geopolymer Reinforced Concrete
Authors: Farhana Zainal Farah , Hawani Hanisah Ismail Nur , Firdaus Abu Hashim Mohammad , Mat Daud Yusrina , Mustafa Al Bakri Abdullah Mohd , Hasri  , Hartati  
Published: July 2020

Abstract
This paper presents corrosion control by using Aluminium as Sacrificial Anode Cathodic Protection (SACP) in geopolymer reinforced concrete. Geopolymer concrete for this research are the combination and reaction between kaolin, which is acting as a binder, fine aggregates such as river sand, coarse aggregates and an alkaline activator which contain 12 M of sodium hydroxide (NaOH) solution and sodium silicate (Na2SiO3) solution with the ratio of NaOH/Na2SiO3 is 0.8. There are two types of sample preparation in this experiment which are the control sample without attaching with Aluminium and SACP sample that attach to Aluminium. Three testing were conducted in this research such as compressive strength, open circuit potential and gravimetric weight loss method and these results were observed after days 7 and 14. Compressive strength testing for this geopolymer concrete shows that the highest compressive strength was at sample 14 days which is 7.04 MPa while sample 7 days is 3.96 MPa. The result shows the potential values of SACP samples were lower than the control sample for both 7 and 14 days. The potential values for the SACP sample for 7 and 14 days are 0.0152 V and -0.037 V while for control sample was 0.048 V and 0.051 V respectively. From the Pourbaix diagram, the control sample was located in the passivity region while SACP sample was located in the immunity region. The corrosion rate of the reinforcement bar in concrete has been performed by the gravimetric weight loss method. Analysis of the resulting proved that the corrosion rate of SACP sample was lower than the control sample for both 7 and 14 days, which were 3.60 x 10−5 mm/yr and 1.427 x 10−5 mm/yr respectively. This is due to the presence of Aluminium which act as the sacrificial anode that protects reinforcement bar in geopolymer concrete from the corrosive agent.
Design and Development of Bird’s Eye Chili Stalk Separator Machine
Authors: Balli Bahril bin , Abd Halim Syahlan bin , Khairul Muzhafar bin Mohd Nor Mohd 
Published: July 2020

Abstract
Chili-based products are increasingly in demand. Realizing this demand, many companies are taking the opportunity to run a chili processing business including turning it into a grind chili and instant chili paste in bottle packaging. The processing of this product goes through several stages, including the process of separating the chilies from the stalks, the cleaning process, grinding the chilies, and ending with the packing work. The main problem is during the process of separating the chilies from the stalks as it is still traditionally practiced by manually separating the stalks from the chilies by workers. It takes a lot of workforce and takes a long time to complete in large quantities. The researchers have carried out a prototype study by designing and building a machine that has been tested and has the ability to separate the chilies from the stalks. The sample of this research was the Sri Azwani Company which had successfully passed the screening by a panel of selected evaluators to obtain the PPRN grant award. The company had encountered problems during the process of separating the bird’s eye chilies from the stalks because it took a while to process 30kg-50kg of chilies for a mass production to produce 530-550 bottles at a time. The machine has a cylindrical main chamber that rotates according to the pre-determined resolution. The machine can process a maximum of 75kg-100kg per day of operation and it will impact the industry in terms of increased production volume, time savings, and cost.
The Influence of Reduced Graphene Oxide Nanoparticles (rGO NPs) on The Microstructure of Metakaolin Geopolymer
Authors: Irfanita R , Desa S S , Fahlefy M R , Wahyuni S , Athiyyah U , Amran  , Setiawan A , Subaer  
Published: July 2020

Abstract
Reduced graphene oxide nanoparticles (rGO NPs) is one of the advanced green nano-materials with valuable properties that offer promising novel applications particularly when it is combine with other materials. The main objective of this study was to investigate the influence of rGO addition on the microstructure character of metakaolin based geopolymer. Graphene oxide nanoparticles (GO NPs) was synthesized from graphite by using modified Hummer’s method and rGO NPs was produced from GO through thermal calcination at 160°C for 4 hours in an autoclave. Geopolymer paste was produced through alkali activation method of metakaolin and cured at temperature 70°C for 2 hours. rGO NPs was dispersed into geopolymer paste with various concentrations, 0, 3, 6 and 9% relative to the mass of metakaolin. The crystal structure and morphology of rGO NPS and geopolymer-rGO NPs composites were investigated by means of x-ray diffraction (XRD), Fourier Transform Infrared (FTIR), scanning electron microscopy (SEM) and The results indicated that rGO NPs as two-dimensional material were successfully produced and characterized. The addition of rGO NPs was found to form strong bond with geopolymer species and hence improve the microstructure character of geopolymer.
Smoothed Particle Hydrodynamics Simulation for Debris Flow: A Review
Authors: Khairi M A W , Rozainy M R , Ikhsan Jazaul 
Published: July 2020

Abstract
Debris flow is a kind of geological disasters occurred in a mountainous area and can cause serious impacts on human lives, infrastructure and houses. Therefore, the potential exposure to this hazard may occur in the surrounding area. This paper assesses some recent noncommercial Smoothed Particle Hydrodynamic (SPH) package for debris flow. SPH as a Lagrangian method, in recent decade SPH showed to be effective in solving in engineering problems involving numerical formulation. The paper considers the features and capabilities can be offer from the non-commercial SPH package that are available and accessible for researcher related to debris flow, solid fluid interaction and so on. Finally, researcher may consider the SPH package based on the suitability of the study as well as the accuracy of the experimental test that have been compared with SPH package.
A new application of deep eutectic solvent (DES) in fish preservation
Authors: Mohamed Hanaphi Roziana , Yusof Rizana , Nur Zubaidah Zakaria Siti , Mohd Saad Nadia 
Published: July 2020

Abstract
Technology in fish preservation had gone through various scope in food industry. Application of new green chemistry of deep eutectic solvent (DES) as preservative capable to help in the prevention of fish contamination by pathogenic bacteria. The aims of this study were including the synthesis of DES, the evaluation of antibacterial activity and sterility testing of the DES using fish samples. The synthesis of choline chloride-based DES was prepared by mixing with acetic acid and oxalic acid respectively. Further testing was done using disc diffusion method for the analysis of the solvent’s antibacterial activity towards E. coli, S. aureus, B. subtilis, S. Typhi and K. pneumonia. The sterility evaluation on the preservative solvent was carried out using fish samples in different temperature and time of storage. Results analysis showed potential of the DES in antibacterial activity even at low concentration of mixture. Sterility test showed promising result by maintaining pH of the solvent at 6-7. Reduction of bacteria concentration was found in the bacterial-spiked fish samples when preserved in the DES mixture. Thus, the study proved the potential of DES as a good preservative for fish compared with the controls from single component of choline chloride, acetic acid and oxalic acid respectively..
Macroeconomic Factors affecting CO2 Emissions in Malaysia: ARDL Approach
Authors: Shahidan Shaari Mohd , Masnan Faiz , Hidayah Harun Nor , Fadzilah Zainal Nor 
Published: July 2020

Abstract
Environmental degradation has always been discussed by previous studies. This is because environmental degradation can have impacts on human health. The global temperature is expected to continue to increase in the next 100 years. Therefore, it is important to investigate the determinants of CO2 emissions in the long run and short run in Malaysia. Data ranging from 1985 to 2014 were collected and the ARDL approach was employed. The results show that economic growth can be detrimental to the environment in both of the long run and short run. The results also show that population can have deleterious effects on the environment in the long run only. Therefore, enhancing economic growth and increasing the number of population should be controlled to ensure that the environment can be preserved.
An Introductory Review to Surface Reconstruction
Authors: Yew Tung Chee , Sallehuddin Roselina , Haron Habibollah , Malyshev Aleksandr 
Published: July 2020

Abstract
Surface reconstruction can be defined as the process of data retrieval via scanning of the object with certain device such as laser scanner and etc. as well as the process of reconstructing the object using the retrieved data. The process of surface reconstruction begins with the type of input data being collected. The types of input data can be unstructured or structured. Artefacts can be defined as the properties of the data retrieved and they indirectly affect the output obtained at the end of surface reconstruction. The different types of input data can be treated by selecting different methods for the process of surface reconstruction. These methods basically fall under the categories of implicit surface, explicit surface and lastly soft computing methods. However, each of these methods for the process of surface reconstruction had their own advantages and disadvantages but they are not discussed thoroughly here. The selection of methods for surface reconstruction lies solely in the interest of studies for other researchers as each method for the process of surface reconstruction can be explored and researched upon viably. This paper highlights a brief introduction and review on previous researches with the aim of providing basic knowledge involved in the process of surface reconstruction.
Development of Edge Detection for Image Segmentation
Authors: Zainal Abidin Z , Asmai S A , Abal Abas Z , Zakaria N A , Ibrahim S N 
Published: July 2020

Abstract
The edge detection technique is a fundamental phase of image segmentation. The purpose of the image segmentation algorithm is to distinguish the boundary of objects in different regions and it relies on discontinuities in image values between distinct regions. The objectives of this research are to a) develop an interface for image edge detection based on derivatives using MATLAB and b) measure the PSNR, SNR and MSE values for analysis based on experiments conducted. Results show that, Lena image produces PSNR values of 20.9 dB (Canny), 20.0 dB (Log), 20.1 dB (Prewitt), 20.0 dB (Sobel) and 20.0 dB (Robert). Meanwhile, MSE gives 80.5 dB (Canny), 83.1 dB (Log), 80.9 dB (Prewitt), 81.0 dB (Sobel) and 81.0 dB (Robert) after the edge detection process. The finding shows that Canny has given a winning performance in PSNR value and low in noise rate for JPEG type of image in image segmentation. Finally, the impact of edge detection techniques produces a better solution for image segmentation.
Feature Selection Using Multivariate Adaptive Regression Splines in Telecommunication Fraud Detection
Authors: Mohamed Amin Muhalim , Zainal Anazida , Firdaus Mohd. Azmi Nurulhuda , Azizah Ali Nor 
Published: July 2020

Abstract
Feature selection determines the most significant features for a given task while rejecting the noisy, irrelevant and redundant features of the dataset that might mislead the classifier. Besides, the technique diminishes the dimensionality of the attribute of the dataset, thus reducing computation time and improving prediction performance. This paper aims to perform a feature selection for classification more accurately with an optimal features subset using Multivariate Adaptive Regression Splines (MARS) in Spline Model (SM) classifier. A comparative study of prediction performance was conducted with other classifiers including Decision Tree (DT), Neural Network (NN) and Support Vector Machine (SVM) with similar optimal feature subset produced by MARS. From the results, the MARS technique demonstrated the features reduction up to 87.76% and improved the classification accuracy. Based on the comparative analysis conducted, the Spline classifier shows better performance by achieving the highest accuracy (97.44%) compared to other classifiers.
A New Hybrid Algorithm Based on ABC and PSO for Function Optimization
Authors: Chen Chang-Feng , Mohd Zain Azlan , Mo Li-Ping , Zhou Kai-Qing 
Published: July 2020

Abstract
Artificial bee colony algorithm (ABC) and particle swarm optimization (PSO) are both famous optimization algorithms that have been successfully applied to various optimization problems, especially in function optimization. Those two algorithms have been attracting more and more research interest because of their efficiency and simplicity. However, PSO has poor exploration capabilities and thus is easy to fall into the local optimum; Likewise, ABC has low convergence speed. To address these shortcomings, firstly, we improved the ABC with the combination of greedy selection and crossover, secondly, a sine-cosine method will be used to help PSO jump into local optimal. Finally, a new hybrid algorithm based on improved ABC and PSO are proposed. Moreover, four functions are used to verify the effectiveness of the proposed algorithm, and the results show that, compared with other well-known algorithms, ABC-PSO is more efficient, faster and more robust in function optimization.
Adaptive Learning in Computing Education: A Systematic Mapping Study
Authors: Jamal Nurul N , Jawawi Dayang N A , Hassan Rohayanti , M Irsyad Kamil R 
Published: July 2020

Abstract
Adaptive learning has become popular among researches in the recent decade. It is believed in giving good benefits which promotes effective ways or methods to improve youth performance in education either for computing field or any non-computing fields. This study focuses on investigating the contribution of adaptive learning in computing education including the adaptation environment involved. This systematic mapping study was undertaken to analyse all relevant and related studies. A set of three research questions were defined in which 68 primary studies, dated from 2012-2020, were analysed and evaluated. The mapping shows the trends and the taxonomy of the contribution adaptive learning in computing education. However, the result also can be applied for non-computing education field. Most of the studied areas are on providing adaptive learning environment and investigating the suitability of learning contents for the youth in teaching and learning. This study summarized the existing research of adaptive learning over past seven years and there is a potential for more research in this area.
Comparison Study on Four Types Mathematical Model for Sand-Casting Process
Authors: Mohd Said Rahaini , Sallehuddin Roselina , Haizan Mohd Radzi Nor , Ridzuan Mohamad Kamal Mohamad , Erne Nazira Bazin Nor 
Published: July 2020

Abstract
Modelling and optimisation of sand-casting process have been widely studied in casting research. The present study was developed to compare the four types of mathematical model and find the best model used in the optimised process. The four types of mathematical model discussed in this paper were multiple linear regression model, full factorial model, fractional factorial model and response surface methodology model. The best model will used for the optimized process using soft computing technique. The input parameters of these models were silica sand, bentonite, water and coal dust. Meanwhile, permeability was the model output. The four types of mathematical model produced were statistically validated to test for model adequacy by using ANOVA and coefficient of determination. Each model was finally, validated by using mean square error (MSE) and root square error (RMSE). The research findings proved that respond surface methodology model was the best model as compared the other models, which was significant with p-values of less than 0.05. The model also produced the smallest MSE.
Facial Expression Transfer using Generative Adversarial Network : A Review
Authors: Adibah Najihah Mat Noor Noor , Mohd Suaib Norhaida 
Published: July 2020

AbstractThere is high demand of realistic facial expression in current computer graphics and multimedia research. Realistic and accurate facial expression can guarantee the animated character to deliver the expression correctly. However, generating facial expression requires hard work, effort and time since high realism of facial expression need to be in details. There are some available methods in current research area such as face warping to the target, re-use the existing images and also models for generating facial image with certain attribute. Based on literature reviews, current trend for facial expression is using the deep learning method such as generative model like Generative Adversarial Network (GANs). Some of GANs that recently available are Conditional Generative Adversarial Network (cGANs), Double Encoder Conditional GAN (DECGAN), Conditional Difference Adversarial AutoEncoder (CDAAE), Geometry-Guided Generative Adversarial Network (G2GAN), and Geometry-Contrastive Generative Adversarial Network (GC-GAN). These methods actually helped in creating more realistic images, reaching out the realistic facial expression and good identity preservation. This paper aims to review available GANs, find out related features to these methods and also performance of these methods that are useful in facial expression transfer process
Development Of Non Circular Iris Segmentation Using Modified Snake Algorithm
Authors: Zainal Abidin Z , Abal Abas Z , Zakaria N A , Shaharin Z Z 
Published: July 2020

Abstract
The importance of this study is to identify a human’s almost round iris shape since the existing technique of iris recognition detects human iris using a circular segmentation method. However, the circular segmentation has limitations to detect and acquire iris in non-ideal conditions. In the non-ideal condition, the location of the iris is situated at a different angle and the information acquired may not be about the iris template. Thus, the non-ideal condition produces less accurate information about the iris template and creates a “not match” situation during verification since the information of the iris template acquired is not similar to the previous iris template. To overcome the problem, this paper proposes the development of the Modified Snake algorithm. The experiment results show that the Modified Snake algorithm reduced the influence of noise in iris images, good execution in learning the edge of images since the number of iteration reduced or maintain based on the iris image since iris image contains high noise. As a conclusion, the experiment used the public iris image database from the Center for Biometrics and Security Research for non-bias evaluation and demonstrates an efficient performance.
Pre-processing Streamflow Data through Singular Spectrum Analysis with Fuzzy C-Means Clustering
Authors: Nasir Najah , Samsudin Ruhaidah , Shabri Ani 
Published: July 2020

Abstract
One approach to improve water resource management is by making use of streamflow forecasts. In this study, eigenvector pairs were clustered by employing fuzzy c-means (FCM) during the grouping stage as an enhancement to the singular spectrum analysis (SSA) technique for data pre-processing. The FCM-SSA pre-processed streamflow data was then supplied to an auto-regressive integrated moving average (ARIMA) model for forecasting. The Department of Irrigation and Drainage Malaysia provided the monthly streamflow records of Sungai Muda (Jambatan Syed Omar) and Sungai Muda (Jeniang) for this research, wherein each was split into training (90%) and testing (10%) sets. The R software was the platform for building every FCM-SSA-ARIMA, SSA-ARIMA and ARIMA model, while the root mean squared errors and mean absolute errors were used to compare the performance between those models. The proposed FCM-SSA-ARIMA was discovered to be capable of surpassing the SSA-ARIMA and ARIMA models.
Hybrid Firefly Algorithm with Artificial Neural Network (FA-ANN) Classification Model for Handwritten Character Recognition
Authors: Mohamad M.A. , Haron H. 
Published: July 2020

Abstract
This paper acknowledged the issues regarding HCR performances particularly in the classification stage. It is generally agreed that one of the main factors influencing performance in HCR is the development of classification model. As for the classification stage, the problems identified are related to classification model particularly in Artificial Neural Network (ANN) learning problem that results in low accuracy of handwritten character recognition. Thus, the aim of this study is to develop and enhance the ANN classification model in order to identify the handwritten character better. This paper proposed the hybrid Firefly Algorithm with Artificial Neural Network (FA-ANN) classification model for handwritten character. Firefly algorithm acts as optimisation approach in enhancing ANN particularly by optimize network training process of ANN. National Institute of Standards and Technology (NIST) handwritten character database was applied in the experiment.