bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fuzzy Analytic Hierarchy Process using Intuitive Vectorial Centroid for Eco-friendly Car Selection
Authors: Adli Aminuddin Adam Shariff , Ku Khalif Ku Muhammad Na’im , Jamil Fadhilah Che , Jaini Nor Izzati 
Published: November 2019

Abstract
Eco-friendly car is expected to be the next driving market force for global transportation and technology due to its paramount importance towards the sustainability of the environment and society. However, the actual sales of eco-friendly car are not that convincing and it is even decreasing because the consumer is still uncertain to consider eco-friendly as one of the criteria for them to buy their cars. This situation is worsen by the lack of information and awareness regarding sustainability transportation initiatives. Due to the uncertainty and vague understanding of the consumer about this problem, this paper attempts to investigate the current preference of consumer to buy their cars, and whether they really need to buy the eco-friendly car by using the Fuzzy Analytic Hierarchy Process (FAHP) which implements the Intuitive Vectorial Centroid (IVC). Based on FAHP, the imprecise or fuzzy judgment from the decision maker can be incorporated, to anticipate a better decision for eco-friendly car selection. The outcome of FAHP is compared with crisp Analytic Hierarchy Process (AHP), and the findings shows that FAHP can provide an accurate and consistent result with AHP, although it deals with fuzzy judgment inputs from multiple decision makers.
Efficient Quadrature Rules for Numerical Integration Based on Linear Legendre Multi-Wavelets
Authors: Alimin Nur Neesha , Nurullah Rasedee Ahmad Fadly , Abdul Sathar Mohammad Hasan , Ahmedov Anvarjon A. , Asbullah Muhammad Asyraf 
Published: November 2019

Abstract
In this work, generalize solution based on linear Legendre multi-wavelets are proposed for single, double and triple integrals with variable limits. To obtain the numerical approximations for integrals, an algorithm with the properties of linear Legendre multi-wavelets are applied. The main benefits of this method are its simple applicable and efficient. Furthermore, the error analysis for single, double and triple integrals is worked out to show the efficiency of the method. Numerical examples for the integrals are conducted by using linear Legendre multi-wavelets in order to validate the error estimation.
An experimental study of the modified accelerated overrelaxation (MAOR) scheme on stationary helmholtz equation
Authors: Syafiq N A , Othman M , Senu N , Ismail F 
Published: November 2019

Abstract
This research aims to experiment the Modified Accelerated Overrelaxation (MAOR) scheme on second order iterative method for solving two dimensional (2D) Helmholtz Equation. The equation is discretized using the standard second order (Full Sweep) finite difference method. Previous well known relaxation schemes includes the Gauss-Seidel (GS), Successive Overrelaxation (SOR), Modified SOR (MSOR) and Accelerated Overrelaxation (AOR) schemes. These schemes has at most two relaxation parameter while the MAOR scheme have more than two. Several numerical experiments were conducted on two different equations to test the feasibility and the superiority of the MAOR scheme compared to the previous schems on different mesh size.
Derivative Free Conjugate Gradient Method via Broyden’s Update for solving symmetric systems of nonlinear equations
Authors: Dauda M.K. , Mamat Mustafa , Mohamad Fatma Susilawati , Magaji Abubakar S. , Waziri M.Y. 
Published: November 2019

Abstract
The applications of mathematics in many areas of computing, scientific and engineering research mostly give rise to a systems of nonlinear equations. Various iterative methods have been developed to solve such equations, this includes Newton method, Quasi-Newton’s etc. Over the years, there has been significant theoretical study on quasi-Newton methods for solving such systems, but unfortunately the methods suffers setback. To overcome such problems, a Derivative free Method for Solving Symmetric Systems of Nonlinear Equations Using Broyden’s Update is presented. The modification is achieved by simply approximating the inverse Hessian matrix

Q

k
+
1

−
1

to

Q
k
I

with (δk
and I represents acceleration parameter and an identity matrix respectively) without computing any derivative. The method uses the symmetric structure of the system sufficiently and the generalized classical Broyden’s update method for unconstrained optimization problems. The squared norm merit function is used, both the direction and the line search technique are derivative-free, this attractive feature of the proposed method makes it to have a very low storage requirement thereby solving large scale problems successfully. In an effort to solve nonlinear problems of the form F(x) = 0, 0, x ∈ Rn
different initial starting points were used on a set of benchmark test problems, the output is based on number of iterations and CPU time. A comparison between the proposed method and the classical methods were made and found that the proposed method is efficient, robust and outperformed the existing method.
Measuring technical efficiency of dry bulk terminal performance using the frontier application of data envelopment analysis: A proposed framework
Authors: Suliman Khairul Rizuan , Rahim Suzari Abdul , Ramayah T , Degeras D Karunanithy 
Published: November 2019

Abstract
The usage of performance indicators in measuring seaport efficiency is undeniable especially towards increasing the port performance. There are numerous studies on applying data envelopment analysis (DEA) which demonstrates the relationship between technical efficiency and port performance. Conversely, there has been a significant problem of port inefficiency in terms of port performance. DEA application is being applied between the technical efficiency and port performance. It is important for indicators to be initiated on port efficiency which may lead to the increase of the port performance. However, the challenges to be implemented in the port as a whole will be difficult due to broad technical factors from various port activities. Implementation of DEA has been done commonly in container operations but not in dry bulk terminal area. Therefore, this conceptual paper discussed the potential of using the technical port indicators and DEA application specifically in dry bulk terminal.
Weighted support vector machine algorithm for efficient classification and prediction of binary response data
Authors: Banjoko A W , Yahya W B , Garba M K , Abdulazeez K O 
Published: November 2019

Abstract
This paper proposes a weighted Support Vector Machine (w-SVM) method for efficient class prediction in binary response data sets. The proposed method was obtained by introducing weights which utilizes the point biserial correlation between each of the predictors and the dichotomized response variable into the standard SVM algorithm to maximize the classification accuracy. The optimal value of the proposed w-SVM cost and each of the kernels parameters were determined by grid search in a 10-fold cross validation resampling method. Monte-Carlo Cross Validation method was employed to examine the predictive power of the proposed method by partitioning the data into train and test samples using different sampling splitting ratios. Application of the proposed method on the simulated data sets yielded high prediction accuracy on the test sample. Results from other performance indices further gave credence to the efficiency of the proposed method. The performance of the proposed method was compared with three of the state-of-the art machine learning methods including the standard SVM and the result showed the superiority of this method over others. Finally, the results generally show that the modified algorithm with Radial Basis Function (RBF) Kernel perform excellently and achieved the best predictive performance than any of the existing classifiers considered.
Stationary and Nonstationary Generalized Extreme Value Models for Monthly Maximum Rainfall in Sabah
Authors: Syafrina A H , Norzaida A , Jannatul Ain J 
Published: November 2019

Abstract
Generalized Extreme Value (GEV) model is the combination of three types of distribution class namely Gumbel, Fréchet and Weibull distributions of the Extreme Value Theory (EVT). In hydrological studies, GEV model is widely applied in the modelling of extreme rainfall. The nature of hydrological variables is highly complex, especially with the changing climate and frequent occurrences of extreme events. As such, some rainfall models assume rainfall series as stationary, while some as nonstationary. In this study, GEV models based on stationary and nonstationary data are used to assess monthly maximum rainfall data within Sabah, Malaysia and performance comparison between both GEV models is conducted. Theoretically both stationary and nonstationary GEV models are based on the same foundation, however nonstationary GEV model allows the location and scale parameters to be expressed as cyclic function of time. In this study, the stationary and the nonstationary GEV models are individually fitted to rainfall data at selected stations. Monthly maximum rainfall is blocked, and the estimated location (μ), scale (σ) and shape (ξ) parameters are estimated by using Maximum Likelihood Estimation method. Performance of both GEV models are compared based on the Akaike Information Criterion, Bayesian Information Criterion and the likelihood ratio goodness of fit tests. Results showed that nonstationary GEV model is the best fit. The inclusion of cyclic covariates in the GEV model gives improvement on the stationary GEV model at the study region. It is also concluded that, Gumbel is identified as the significant distribution for monthly maximum rainfall in Sabah at 5% significance level.
Modeling tuberculosis patients using loglinear models
Authors: Nasseruddin Noorliyana , Mahmud Zamalia , Md Isa Khairil Anuar 
Published: November 2019

Abstract
Tuberculosis (TB) patients usually get infected by tuberculosis bacteria called Mycobacterium tuberculosis which can spread from one person to another through air. TB cases normally infect the lungs (Pulmonary TB) and in some other cases it infects other organs such as brain, heart, spine, lymph nodes, adrenal gland and intestines (Extrapulmonary TB). However, patients who are infected with tuberculosis bacteria may have complications due to other factors that can delay the process of healing. Using loglinear modelling, this study will examine whether types of TB is strongly associated with patient’s age, gender, whether or not they smoke, have HIV and into drug use. Records of 477 TB patients obtained from a previous related study are used in the modelling process where five loglinear models are compared to find the most parsimonious model that will determine the strength of the association between the variables. Likelihood ratio G
2, p-values, expected values and standardized residuals are used in the analysis. Based on the comparisons of the loglinear models, homogeneous model is found to be the most parsimonious compared to independence and joint models. The analysis based on the homogenous loglinear model show that that the estimated odds of patients who smoke is 2 times more likely to have a Pulmonary TB compared to the non-smokers. Also patients who are drug users are 8 times more likely to have a Pulmonary TB compared to patients who are non-drug users. Hence, a recommendation for the healthcare providers is to give more attention to patients in these categories.
Discrimination of Lard and other Edible Fats after Heating Treatments using Partial Least Square Regression (PLSR), Principal Component Regression (PCR) and Linear Support Vector Machine Regression (SVMR).
Authors: Mohd Salleh Nor Aishah , Hassan Mohd Sukri 
Published: November 2019

Abstract
Discrimination between lard and other edibles fats is a challenging task for halal determination especially after the fats were heated at high temperature for a long period. In this study, three multivariate regression models such as partial least square regression (PLSR), principal component regression (PCR) and support vector machine regression (SVMR) were applied to evaluate the spectral data of FTIR (n=195) obtained from lard, chicken, beef, mutton and vegetable fats after heated at different conditions (120-240°C and 0.5-3 hrs). The regression of the Y-binary matrix was used to discriminate lard (as 1) and the others edibles fats (as 0). Kennard Stone (KS) algorithm selected a subset of the training set (n=145) and test set (n=50). The test set was used to validate the prediction ability of the suggested models. The obtained results showed the ability of the three proposed models to discriminate the heated lard simultaneously. The values of the R2, adjusted R2, root-mean-square error (RMSE) and root-mean-square error of validation (RMSEV) showed a good results under Basic ATR correction transformation as PLSR (0.984, 0.977, 0.052 and 0.062); PCR (0.974, 0.971, 0.067 and 0.070), and SVMR (0.971, 0.959, 0.087 and 0.102) respectively. However, when using mean square error (MSE), it gives lower prediction error for PLSR (0.006), PCR (0.007) and SVMR (0.015). The results showed that PLSR as the best model for discrimination spectral data of lard and other edible fats after heating treatments for halal determination.
New model averaging approach in predicting mortality rate of intensive care unit patients
Authors: Mohd Padzil Siti Aisyah , Pillay Khuneswari Gopal , Rusiman Mohd Saifullah , Salleh Rohayu Mohd 
Published: November 2019

Abstract
Model Averaging (MA) is one of the well-known statistical modelling approach to produce a fitted model in applied research. Even though it was proposed to overcome underestimation of parameter estimates issues in Model Selection (MS), the final best model of MA includes insignificant variables. The goal of this research is to propose an New Model Averaging (NMA) method which is based on MA approach with elimination of insignificant variables. Data of Intensive Care Unit (ICU) was studied to highlight the most influential factor of mortality rate. ICU is commonly associated with a high mortality rate due of its complexity of treatments. The guidelines of NMA method on ICU patient’s data were presented and the models obtain were compared using 10-Fold Cross-Validation. The results reveals that the performance of NMA is slightly better than MA. The most significant factors for mortality of ICU patients were concluded to be patient’s age, SAPS II score discharge and whether or not the patients use ventilation machine. In conclusion, the study showed that the elderly patients have a greater risk of mortality after discharge from the hospital and SAPS II score provide a good indication in predicting hospital mortality.
Conversion coefficients from kerma to ambient dose and personal dose for X-ray spectra
Authors: Otto T. 
Published: November 2019

In radiation protection, the protection quantity for whole-body exposure is effective doseE. Effective dose cannot be measured and operational quantities have been introduced for dose measurement and calibration of dosimeters and survey instruments. To overcome some shortcomings of the presently used operational quantities, ICRU Report Committee 26 introduces two new quantities for whole body exposure, ambient doseH*for prospective dose assessment and personal doseHp(α) for retrospective measurements with personal dosimeters. Dosimeters and survey instruments are calibrated in reference fields, realised with radioisotopes and with well-defined X-ray spectra. In this paper, the spectrum-averaged conversion coefficients from kerma in airKato the new quantities ambient dose and personal dose are calculated and compared with the published coefficients for the present operational quantities. Especially at low energies (Eph < 40 keV), the new quantities are significantly lower than the present ones, thus correcting a strong overestimate of effective dose.
On-line profiling of volatile compounds produced in vitro by pathogenic oral bacteria
Authors: Roslund Kajsa , Lehto Markku , Pussinen Pirkko , Groop Per-Henrik , Halonen Lauri , Metsälä Markus 
Published: November 2019

Abstract
Infections by oral pathogens are one of the most common health problems worldwide. Due to the intimate connection between exhaled breath and the oral cavity, breath analysis could potentially be used to diagnose these infections. However, little is known about the volatile emissions of important oral pathogens that are connected with gingivitis and periodontitis. In this study, we have performed in vitro headspace measurements on four important oral pathogens (P. gingivalis, T. forsythia, P. intermedia and P. nigrescens) using proton transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS). Some of the most abundant compounds produced by the bacteria include hydrogen sulphide, methanethiol, acetone, dimethylsulphide, isoprene, cyclopentanone and indole as tentatively assigned from the mass spectra. Several other abundant mass signals were recorded but the assignment of these is less certain. Some of the bacterial species can be separated from each other by the emitted volatile fingerprints. The results of this study can be used in potential development of a diagnostic breath test for oral infections. In addition, as several of the measured compounds are known to be toxic, the results point to an intriguing possibility of studying the connection between the bacterial virulence and the emitted volatile compounds.
Physical quality change of rose tea during freeze drying
Authors: Imaniar D I , Karyadi J N W , Marfu’ah S , Akbar M A 
Published: November 2019

Abstract
Rose tea began to be widely developed since it has advantages in the form of high antioxidant content, and fragrant aroma. Currently, rose tea production uses manual dryers in the form of sunlight energy, which might reduce the physical and chemical quality of rose tea. The low temperature drying is expected to be able to maintain the quality of rose tea. The aim of the study was to determine the drying characteristics of rose tea using a freeze dryer machine. The material used is a local type of rose petals from the Malang region with a water content of 86.76%. The tool used is 1 unit freeze dryer capacity of 1.5 kg with freezing temperature of -18oC, and with a pressure of -76 cm Hg. The drying chamber is made of stainless steel equipped with three heater plates with a total power of 500 watts. The experimental design uses variations in drying time, namely 0, 12, 18, 24, 30, and 36 hours. Parameters measured were water content, color, weight loss, and antioxidant content in the form of flavonoids. The experimental results showed that the final moisture content of roses using drying freeze dryer was 9.54% with a drying rate of freeze dryer of 2.14% per hour. Rose color has decreased from L * value of 27.37 to 8.87 a * value of 52.81 to 14.84 and b * value of 26.19 to -0.77. Based on this, compared to drying with sunlight and cabinet dryers, drying with a freeze dryer is better at drying roses into rose tea.
Fast and robust quality assessment of honeys using near infrared spectroscopy
Authors: Munawar A A , Syah H , Yusmanizar  
Published: November 2019

Abstract
In this present study, near infrared spectroscopy (NIRS) is employed to detect adulteration and predict soluble solids content (SSC) of raw honey samples based on reflectance spectral data. Diffuse reflectance near infrared data were acquired in wavelength range from 1000 to 2500 nm. Adulterated honey, made by mixing pure honey with commercial sugars, was detected and classified using principal component analysis (PCA). On the other hand, SSC content as predicted from pure honey samples using partial least square regression (PLSR). Standard normal variate (SNV) was applied as spectra correction method. The results showed that PCA based on spectra data, can accurately detect adulteration and classify honey samples with total explained variance from 2 principal components is 97%. Moreover, SSC of pure honey samples can be predicted with achieved correlation coefficient (r) of 0.96 and residual predictive deviation (RPD) index of 2.88 for raw un-corrected spectra, while r = 0.98 and RPD = 3.67 for corrected SNV spectra data. It may conclude that near infrared spectroscopy, can be used as fast and robust method to evaluate quality of raw honey samples.
The influence mechanism research of inflow temperature in different time scale on the water temperature structure
Authors: Chen H , Yao L , Fitri A 
Published: November 2019

Abstract
A 3D hydraulic-thermodynamic mathematical model is established to predict the temporal and spatial distribution of temperature in a large reservoir in different time scale inflow temperature condition, and a further research on the influence mechanism of inflow temperature on the water temperature structure is made. it is found that the convection current between the upper and the lower of the reservoir always appear when the storage heat in a reservoir decreases; the stratification phenomenon appears in most time of a year in a large reservoir which is controlled by the climate, and there is a close relationship between the water temperature distribution and the inflow temperature. Different inflow temperature has different affected area where the density current propagates, in the affected area, the difference of water temperature distribution occurs by the cumulative effect of the previous months, for the other area, the more detailed the inflow temperature is, the more accurate the simulation results are.
Cradle to gate LCA to enhance program for pollution control, evaluation and rating (PROPER) in palm oil industry
Authors: Kurniawan M P , Guritno A D , Purwantana B , Supartono W 
Published: November 2019

Abstract
The achievements of the palm oil industry as a strategic commodity of Indonesia need to be followed in responsibility, efficiency and sustainability. Indonesia government continues to encourage oil palm industry to obey in pollution reduction, environmental management, and implementation of standards for palm oil plantation to reduce environment impacts, climate change, biodiversity and tropical forests protection. The Program for Pollution Control, Evaluation and Rating (PROPER) seeks to harmonize aspects through increasing capability in reporting and competent and certified human resources. This research was conducted through observation, interviews, and integrating LCA in the PROPER program to assist in the development of scientific data on emissions and can be accounted. Life cycle assessment (LCA) provides an overview of used natural resources, waste disposal to environment, evaluating and applying continuous improvements. Total emissions as output of the palm oil industry must be calculated based on real activities on palm oil plantations and mills. The results showed the need for integration of life cycle inventory with reporting information systems of environment management system, control of water pollution, control of air pollution, and management of hazardous waste and use of energy. Life cycle impact and interpretation play important role as knowledge management through of responsibility, efficiency, and sustainability (RES) approach to contribute for national database system.