bluuebunny/crossref_metadata_2025 huggingface dataset:
Track propagation for different detector and magnetic field setups in Acts
Authors: Klimpel Fabian
Published: July 2020

Track finding and fitting are among the most complex parts of event reconstruction in high-energy physics, and usually dominate the computing time in a high luminosity environment. A central part of track reconstruction is the transport of a given track parametrisation (i.e. the parameter estimation and associated covariance matrices) through the detector, respecting the magnetic field setup and the traversed detector material. While track propagation in a sparse environment (e.g. tracking detector with layers) can be sufficiently well approximated by considering discrete interactions at several positions, the propagation in a material dense environment (e.g. calorimeters) is better served by a continuous application of material effects. Recently, a common tracking software project (Acts), originally from the Common Tracking code of the ATLAS experiment, has been developed in order to preserve the algorithmic concepts from the LHC start-up era and prepare them for the high luminosity era of the LHC and beyond. The software is designed in an abstract, detector independent way and prepared to allow highly parallelised execution of all involved software modules, including magnetic field access and alignment conditions. Therefore the propagation algorithm needs to be both flexible and adjustable. The implemented solution using a fourth order Runge-Kutta-Nyström integration and its extension with continuous material integration and eventual time propagation is presented and the navigation through different geometry setups involving different environments is demonstrated.
Flexible electromagnetic capturer with a rapid ejection feature inspired by a biological ballistic tongue
Authors: Kan Longxin , Lei Fengxiao , Song Bo , Su Bin , Shi Yusheng
Published: July 2020

Bionics is the inspiration resource of state-of-the-art science and technology. The chameleon can capture prey at great distances with the assistance of its highly stretchable and ballistic tongue. Inspired by this biological structure, here we demonstrate the fabrication of flexible electromagnetic manipulators. The as-prepared flexible electromagnetic manipulator can reach a maximum velocity of 8.1 m s−1 and acceleration of 627 m s−2 at an applied voltage of 360 V. The working mechanism of this flexible electromagnetic manipulator has been studied based on Maxwell and Abaqus simulations. Diverse parameters, including the lengths of the magnetic tube (the cylindrical magnet) and the whole manipulator and the applied voltage values, have been considered to tune the ejecting performance of the manipulator. Furthermore, flexible electromagnetic manipulators can be upgraded to capture various objects by attaching a mechanical force triggered gripper to their top pads. With this design, the velocity of the gripper can be significantly improved (the maximum is 8.1 m s−1, whereas soft grippers in previous research do not have the characteristic of fast movement), thus making it possible to get objects without approaching them; in other words, we can catch objects even though they are far away from us, which provides the possibility of long-distance capture. We believe this kind of bio-inspired fabrication is a powerful strategy to design and synthesize flexible even stretchable manipulators, extending the boundaries of conventional manipulators for soft robots.
Climate risks to Brazilian coffee production
Authors: Koh Ilyun , Garrett Rachael , Janetos Anthony , Mueller Nathaniel D
Published: July 2020

Brazil is the world’s leading coffee exporter, contributing billions of dollars to the global food economy. Yet, a majority of Brazilian coffee farms are operated by ‘smallholders’, producers with relatively small properties and primarily reliant on family labor. While previous work indicates that climate change will decrease the area suitable for coffee production in Brazil, no study has assessed the impacts of climate change on coffee yields or the relative exposure and vulnerability of coffee producing regions to changes in climate hazards (climate-associated losses in yield). To address these knowledge gaps, we assess the sensitivity of coffee yields to temperature and precipitation variation from 1974 to 2017 to map coffee climate hazards. Next, we identify which coffee producing regions in Brazil have the highest exposure to climate hazards due to high dependence of coffee production as a proportion of agricultural area. Finally, we generate a Vulnerability Index to identify which regions are theoretically least able to adapt to climate hazards. Our study finds that since 1974, temperatures in Brazilian coffee growing municipalities have been increasing by ∼0.25 °C per decade and annual precipitation has been decreasing during the blooming and ripening periods. This historical climate change has already resulted in reductions in coffee yield by more than 20% in the Southeast of Brazil. Minas Gerais, the largest coffee producing state in Brazil, has among the highest climate hazard and overall climate risk, exacerbated by ongoing coffee expansion. Additionally, many municipalities with the lowest adaptive capacity, including the country’s mountainous regions, also have high climate exposure and hazards. Negative climate hazard and exposure impacts for coffee producing regions could be potentially offset by targeting climate adaptation support to these high-risk regions, including research, extension, and credit subsidies for improved coffee varieties, irrigation, and agroforestry and diversifying agricultural production.
Potential impacts of cool and green roofs on temperature-related mortality in the Greater Boston region
Authors: He Cheng , He Li , Zhang Yan , Kinney Patrick L , Ma Weichun
Published: July 2020

Many cities are developing mitigation plans in an effort to reduce the population health impacts from expected future increases in the frequency and intensity of heat waves. To inform heat mitigation and adaptation planning, information is needed on the extent to which available mitigation strategies, such as reflective and green roofs, could result in significant reductions in heat exposure. Using the Weather Research and Forecasting (WRF) model, we analysed the impact of green and cool (reflective) roofs on the urban heat island (UHI) and temperature-related deaths in the Greater Boston area (GBA) and New England area (NEA) in summer and winter. In the GBA, green and cool roofs reduced summertime population-weighted temperature by 0.35 °C and 0.40 °C, respectively. In winter, green roofs did not affect temperature, whereas cool roofs caused a temperature reduction of 0.40 °C. In the NEA, the cooler summers induced by green and cool roofs were estimated to reduce the heat-related mortality rates by 0.21% and 0.17%, respectively, compared to baseline. Cool-roof-induced temperature reduction in winter could increase the cold-related mortality rate by 0.096% compared to baseline. These results suggest that both green and cool roofing strategies have the potential to reduce the impact of heat on premature deaths. Additionally, the differing effects in winter suggest the need for a careful consideration of health trade-offs in choosing heat island mitigation strategies.
Fractional Brownian motion with random diffusivity: emerging residual nonergodicity below the correlation time
Authors: Wang Wei , Cherstvy Andrey G , Chechkin Aleksei V , Thapa Samudrajit , Seno Flavio , Liu Xianbin , Metzler Ralf
Published: July 2020

Numerous examples for a priori unexpected non-Gaussian behaviour for normal and anomalous diffusion have recently been reported in single-particle tracking experiments. Here, we address the case of non-Gaussian anomalous diffusion in terms of a random-diffusivity mechanism in the presence of power-law correlated fractional Gaussian noise. We study the ergodic properties of this model via examining the ensemble- and time-averaged mean-squared displacements as well as the ergodicity breaking parameter EB quantifying the trajectory-to-trajectory fluctuations of the latter. For long measurement times, interesting crossover behaviour is found as function of the correlation time τ characterising the diffusivity dynamics. We unveil that at short lag times the EB parameter reaches a universal plateau. The corresponding residual value of EB is shown to depend only on τ and the trajectory length. The EB parameter at long lag times, however, follows the same power-law scaling as for fractional Brownian motion. We also determine a corresponding plateau at short lag times for the discrete representation of fractional Brownian motion, absent in the continuous-time formulation. These analytical predictions are in excellent agreement with results of computer simulations of the underlying stochastic processes. Our findings can help distinguishing and categorising certain nonergodic and non-Gaussian features of particle displacements, as observed in recent single-particle tracking experiments.
Refined diamond norm bounds on the emergence of objectivity of observables
Authors: Colafranceschi Eugenia , Lami Ludovico , Adesso Gerardo , Tufarelli Tommaso
Published: July 2020

The theory of quantum Darwinism aims to explain how our objective classical reality arises from the quantum world, by analysing the distribution of information about a quantum system that is accessible to multiple observers, who probe the system by intercepting fragments of its environment. Previous work showed that, when the number of environmental fragments grows, the quantum channels modelling the information flow from system to observers become arbitrarily close—in terms of diamond norm distance—to ‘measure-and-prepare’ channels, ensuring objectivity of observables; the convergence is formalised by an upper bound on the diamond norm distance, which decreases with increasing number of fragments. Here, we derive tighter diamond norm bounds on the emergence of objectivity of observables for quantum systems of infinite dimension, providing an approach which can bridge between the finite- and the infinite-dimensional cases. Furthermore, we probe the tightness of our bounds by considering a specific model of a system-environment dynamics given by a pure loss channel. Finally, we generalise to infinite dimensions a result obtained by Brandão et al (2015 Nat. Commun.
6 7908), which provides an operational characterisation of quantum discord in terms of one-sided redistribution of correlations to many parties. Our results provide a unifying framework to benchmark quantitatively the rise of objectivity in the quantum-to-classical transition.
OGC Geospatial Coverages Data Cube Community Practice
Authors: Voidrot Marie-Francoise , Percivall George
Published: July 2020

Data Cubes for geospatial information provide the means to integrate observations and other types of geospatial data for use in multiple applications through simplified access and efficient analytics. Acknowledging that diverse implementations already exist, this Community Best Practice, developed by the OGC members and supported by at least 6 independent implementations listed in the document, defines requirements for a core Geospatial Coverage Data Cube infrastructure and guidelines for enhancements and extensions to the basic core. With this paper and other activities, OGC is contributing to the advancement of Data Cubes more generally and as a foundation for federations of Data Cubes for geospatial information.
Heat Evolution of Class C Fly Ash Geopolymers with Different Molarity of Sodium Hydroxide: Nucleation Growth and Morphology Properties towards Early Strength Evaluation
Authors: Mohamed Rosnita , Abd Razak Rafiza , Mustafa Al Bakri Abdullah Mohd , Khimi Shuib Raa , Subaer  , Ahmad Romisuhani , Hakem Aziz Ikmal , Ahmad Sofri Liyana
Published: July 2020

The heat evolved during setting of class C fly ash geopolymers with different molarity of sodium hydroxide are discussed. The reaction kinetics and microstructure properties of geopolymers are studied towards the early strength development. Differential Scanning Calorimeter was applied to determine the heat evolved and Johnson-Mehl-Avrami-Kolmogrov Model was used to analyse the reaction kinetics during setting of the geopolymers. Morphology and strength development were monitored. The results revealed that the heat evolved increased proportionally with increasing molarity of sodium hydroxide. This indicated rapid reaction of geopolymerization due to the increasing of hydroxide ion content thus mainly affect dissolution process. It was also found that the geopolymerization during setting was governed by one-dimensional growth with instantaneous heterogeneous nucleation and this was supported by the morphology of the geopolymers observed. Among the activator molarities, the molarity of 12 (12M) was observed to be most influential based on its highest compressive strength (up to 46MPa at 7-days) and supported by the morphology properties results.
Correlation of Thermal Conductivity Versus Bulk Density, Porosity and Compressive Strength of Metakaolin Geopolymer
Authors: Ain Jaya Nur , Yun-Ming Liew , Cheng-Yong Heah , Mustafa Al Bakri Abdullah Mohd
Published: July 2020

This paper investigates the correlation of thermal conductivity versus bulk density, porosity and compressive strength of metakaolin geopolymer for different mixing parameters (that are, alkali concentration, activator (AA) ratio and metakaolin/activator (MK/AA) ratio). Metakaolin was alkali-activated with NaOH and Na2SiO3 solution to produce geopolymer. Varying NaOH concentration (6M, 8M, 10M, 12 M and 14M), AA ratio (0.4, 0.6, 0.8, 1.0 and 1.2) and MK/AA ratio (0.6, 0.7, 0.8, 0.9 and 1.0) were used to study the effect on bulk density, porosity, compressive strength and thermal conductivity. Result showed that metakaolin geopolymer with maximum compressive strength (33 MPa), bulk density of 1680 kg/m3, porosity of 18% and thermal conductivity of 0.40 W/mK is achieved with alkali concentration of 10M, AA ratio of 1.0 and MK/AA ratio of 0.8. From the gradation analysis of the strength result, AA ratio is the most influential mixing parameter in determining the compressive strength. In contrast, MK/AA ratio significantly affected the thermal conductivity. From the Pearson correlation coefficient, TC had strong relationship with bulk density and porosity and poor relationship with compressive strength.
Indoor Environment Quality (IEQ): Temperature and Indoor Air Quality (IAQ) Factors toward Occupants Satisfaction
Authors: Nur Aishah Mohd Noor Siti , Ding Ha Haw
Published: July 2020

In Malaysia, the demand for green building kept rising from year to year. The design concept of the green building which provides better indoor environment to make occupant more comfortable and healthier. The Green Building Index (GBI) as a rating system in Malaysia was used to evaluate the environmental design and performance of a building by the occupant, due to that, it is used for this research to investigate the relationship between the indicator of the Indoor Environment Quality (IEQ) and occupant satisfaction’s element in a private university in Sarawak. The building occupants are the most important feedback to determine the occupant’s satisfaction level for IEQ within the campus. A quantitative method was applied to reach the objectives by using simple random sampling. A total of 254 copies of the questionnaire survey form were distributed to respondents at School of Business and Management (SBM) and School of Built Environment (SBE) in the university. However, there are only 238 responds are usable for this research. The result shows that the temperature (57.0%) and the indoor air quality (66.7) in IEQ’s indicator had moderate positive and significant relationship with thermal comfort, and ventilation respectively.
The Effect of Seawater on The Strength, Microstructure and Elemental Distribution of Fly Ash/ Kaolin Based Underwater Geopolymer
Authors: Hannanee Ahmad Zaidi Fakhryna , Ahmad Romisuhani , Mustafa Al Bakri Abdullah Mohd , Mastura Wan , Syauqi Ahmad
Published: July 2020

Concrete in seawater is subjected to various aggressive constituents in seawater commonly sulphate, chloride and carbonate. This paper investigates the potential effects towards mechanical and physical properties of geopolymer when used as underwater concreting material. Besides identifying the microstructure using Scanning Electron Microscopy (SEM), the sample is also characterized using Synchrotron based micro X-Ray Fluorescence (µ-XRF) to identify the elemental distribution that had occurred in the underwater geopolymer. Other essential properties for concrete such as compressive strength, water absorption and density were also determined. The compressive strength result indicates a slightly lower strength for underwater geopolymer (31.40 MPa) compared to normal geopolymer (35.91 MPa). Relevant to the strength, the water absorption and density also shows a slight difference between the geopolymer samples. The µ-XRF analysis shows the presence of chlorine (Cl) element only for underwater geopolymer which indicates that the are chloride penetration for underwater geopolymer. Additionally, other element distribution such as Silica (Si), Aluminum (Al) and Calcium (Ca) shows a different value when comparing normal geopolymer and underwater geopolymer. Despite the difference in elemental distribution between sample, geopolymer is proven to have the potential to be used as underwater material since it is able to retain at least 70% strength of the control sample.
Energy Priority Estimation Model for Quantitative Analysis of Potential Bioethanol Feedstock
Authors: Ye Ong Sin , Ilham Zul
Published: July 2020

Conventional energy sources depletion, energy insecurity, fluctuating petroleum prices and global climate change have driven countries worldwide to consider alternative and renewable energy options. The use of biofuel such as bioethanol is as an option over conventional petroleum and important for the development of sustainable and eco-friendly energy resources. However, bioethanol manufactured from various biomass resources is different in terms of its processing stages and the need for extra pre-treatments. This study aims to suggest the most feasible biomass resource for bioethanol generation by using Analytical Hierarchy Process (AHP), one of the multi-criteria decision-making methods based on priority estimation model. Among biomass resources, the issue of selecting the most feasible resource is evaluated, using numerous criteria influencing the biomass selection which are chosen through Focus Group Discussion (FGD) with experts in the biomass research field. Out of the five selected biomass resources, sugarcane is preferable as a bioethanol feedstock with an overall priority of 31.69%, followed by palm oil residues (overall priority= 23.51%), compared to corn (overall priority= 22.59%), rice straws (overall priority= 13.53%) and sugar beet (overall priority= 8.67%). Sugarcane is claimed to be the most feasible bioethanol feedstock due to its high availability over years, high energy ratio, high cellulose and hemicellulose content. Although sugarcane takes a longer time to grow, it is easier to be planted and harvested with the help of developed machineries. However, an ideal bioethanol-producing feedstock should not be food crops. Thus, as a suggestion for future research, more factors to determine the potential and suitability of the crops should be considered.
Removal of Organic Constituents and Bacteria Count Disinfection from Fish Processing Wastewater by Using Ionic Cupric Copper
Authors: Nasuha Nadhirah Nurul , Anuar Kamaruddin Mohamad , Nazmi Ismail Muhd
Published: July 2020

The increasing consumption of fisheries product causes large amount of wastewater produced from fish processing industry. General wastewater treatment includes the use of harmful chemical such as chlorine. This research opens a new platform to treat wastewater by using ionic cupric copper which is also known as copper nanoparticles (CuNP). Copper nanoparticles are synthesized through chemical reduction method by using Copper sulphate pentahydrate (CuSO4.5H2O) as precursor and Sodium hydroxide (NaOH) as reducing agent. The physical characterizations of CuNP are carried out by using SEM and the chemical characterizations are carried out by using XRD and FTIR. The efficiency of CuNP to treat wastewater from fish processing industry are determined by the removal of COD, Total coliform and E.Coli. The optimum concentration to reduce COD is 1000mg/L which causes 59.4% percentage removal of COD. The optimum concentration for COD removal is used to determine the volume of CuNP needed to remove total coliform and E.Coli. The optimum volume for removal of total coliform and E.Coli are 40µL and 30 µL respectively.
Metal Additives Influence in the Storing Stability Degradation of Biodiesel
Authors: Fazli Bin Mohd Ghazali Ahmad , Hadi Abdul
Published: July 2020

Recently, biodiesel is used as an alternative fuel to reduce the air pollution. However, storage stability comes as it reduces the biodiesel properties after it been stored for a long period. This study was conducted to investigate the effect of storage duration on the stability degradation of biodiesel and the influence of metal additives nanoparticles blend to retard the deterioration of biodiesel. Biodiesel was synthesized using transesterification of waste cooking oil Gas Chromatography was performed to characterized the elements of biodiesel. Silver, manganese and iron nanoparticles were synthesized following sol-gel method. Nanoparticles were blended with biodiesel in concentration of 100 and 500 ppm using the ultrasonicator bath. Storage stability observation was performed according to ASTM4625 method which is 43 °C for one week. Gas Chromatography peaks shows similar components as standard biodiesel such as methyl palmitate, methyl stearate and methyl linoleate. Density and acid value were sis results proved that nanoparticles can help to retard the stability degradation of biodiesel.
Accelerates High Temperature Oxidation due to the Change of Schottky’s Barrier Height of Cr2O3 Layer in Humid Condition
Authors: Ani M. H. , Zaharudin M. Z. , Anhar Z. , Musa M. , Hamid M.
Published: July 2020

Development of the new generation of Ultra Supercritical (USC) power plant that has successfully achieved the targeted working temperature of 970 K. Nonetheless, increasing the operating temperature will further accelerate the high temperature oxidation of ferritic alloys of the boiler. Furthermore, water vapour in humid environment will make it easier for the alloy to further oxidize at high temperature. It is hypothesized that water vapour provides hydrogen that dissolves into the ferritic alloy susbstrate, hence altering their electronic state at the metal-semiconductor (oxide) interface. This study aims to measure Schottky Barrier Height (SBH) in dry and wet environment and relates it with acclerated oxidation behaviour. The Schottky Barrier was prepared by sputtering Cr2O3 onto the T91 boiler tube in high vacuum condition of 0.4 Pa, RF power 150W for an hour. The existance of Cr2O3 / Fe junction was confirmed by XRD analysis. The junction was then connected with platinum wire to act as the electrode for the current-voltage, I-V and capacitance-voltage, C-V test at high temperature. From the I-V graph, the reversed saturated current, Io was estimated and the SBH was calculated from the results. The SBH increased as the conductivity increased with the increment of temperature. From the C-V plots the value of Vbi was determined and used to calculate the SBH. The SBH increased with the increased of built in voltage. The result obtained from the two method agrees with one another. SBH value in wet condition is higher than that in dry condition. This is explained by the formation of space charge layer at metal/oxide interface due to dissolved hydrogen in metal, thus may change the transport property and accelerate the oxidation rate in water vapor.
A Study on Torrefaction of Empty Fruit Bunch and Its Impact on Lignocellulosic Structure
Authors: Rashid S.R.M , Samad N.A.F.A , Saleh S.
Published: July 2020

Torrefaction is a thermal treatment process used for upgrading lignocellulosic biomass properties into a promising renewable energy, which is performed under inert condition at a temperature range of 200 - 300°C between 15 – 60 minutes residence times. The aim of this study was to investigate the effect of torrefaction treatment on chemical composition and energy properties at different temperature 240, 270, 300 and 330°C with different residence time at 15, 30 and 60 minutes for oil palm biomass (empty fruit bunch). The analysis demonstrated an increase degradation of biomass hence an increase of mass loss was observed due to the combined effect of temperature and treatment duration. Higher heating values was increased by 55% which attributes the energy generations from the torrefied materials. Hemicellulose and cellulose content degraded as temperature and treatment duration increased, while lignin content increased due to the decomposition of hemicellulose and cellulose which accumulated the lignin content in the torrefied biomass. This study proves that torrefied biomass can be used as biofuel as it has higher heating value, and improved the chemical and physical properties of biomass.
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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

There 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

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

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.