bluuebunny/crossref_metadata_2025 huggingface dataset:
Road accidents analytics with data visualization: a case study in Shah Alam Malaysia
Authors: Shaadan N , Azhar Suhaimi M I K , Hazmir M I , Hamzah E N
Published: August 2021

Road accident has become a serious problem of concern due to the increasing trend of the occurrences in line with the increase in the number of registered vehicles in Malaysia year by year. Causes of road accidents may come from various factors. Information on the causes is important to increase knowledge in assisting various responsible bodies with the theory and framework for establishing appropriate regulation, policy as well as for intervention planning and purposes in controlling and managing road accidents problem. Thus, this study aims to produce a road accidents profile of Shah Alam based on secondary data from MIROS and PDRM using descriptive and inferential data analytics. The application of data visualization methodology and techniques have shown that among all states in Malaysia, Selangor having the highest frequency of road accidents. For the cases of Shah Alam, there exist a temporal time scale pattern of road accidents occurrence. More number of accidence happened during the day compared to night. The most critical time the accidence took place is during busy hours; between 8.00 to 10.00 am in the morning, during evening hours between 4.00 to 6.00 pm and night hours after 6.00 pm until 8.00 pm. The accidental death cases were found mostly come from motorbike with (90-250cc), followed by car and lorry and were found mostly occurred at straight-ahead road as well as municipal road. The most type of collision is straying, digressing, or skidding followed by back collision and side collision. The severity of accidents impact is found associated with drivers demographic factors in which accidental death cases involving male is higher than female with age group between 21 to 25 years old.
Correcting for risk premium on Extended Generalised Leland Models: an empirical study on Dow Jones Industrial Average (DJIA) index options
Authors: Harun H F , Abdullah M H
Published: August 2021

The relative option pricing performance of Extended Generalised Leland models is examined in this study. We generalise the extended Leland models based on the implied adjusted volatility introduced in the models. Non-parametric framework is fitted into parametric option-pricing framework based on the Leland models to achieve a more realistic option pricing. To reflect the real probability measure, the implied adjusted information is corrected in terms of risk premium. This study concentrates mainly in examining the option-implied information produced by the models after correcting for risk-premium. Data extracted from DJIA index options are employed in this study, which covers the period from January 2009 until the end of 2015. We discovered that the option-implied volatility, which is priced using the Extended Generalised Leland models, especially after being corrected for risk-premium factor improves the option valuation accuracy significantly.
The effects of a multiple solution method in mathematics learning for secondary schools
Authors: Yusof Amirah Aina , Hamid Nor Hafizah A , Othman Zarith Sofiah
Published: August 2021

Solving problems in mathematics does not involve a single method only. Using a multiple solution method can also assist students in seeking a solution. A multiple solution method is a method that can be applied in the process of teaching and learning in which students will learn a variety of methods to be applied in finding solutions for a single question. This paper reports a study conducted to review students’ views of the effects of the use of a multiple solution method in learning mathematics. The study used two approaches: the quantitative approach (Section A, B and C) and qualitative approach (Section D), in a questionnaire for collecting data. 100 students from a secondary school located in Klang, Selangor were selected as respondents in this study. The questionnaire focused on the perceptions of students in using a multiple solution method and consequently the effect towards students’ level of self-regulation. The Likert scale ranging from 1 (strongly disagree) to 4 (strongly agree) was used. All respondents were also instructed to indicate the challenges faced in the use of a multiple solution method in the open-ended questions. The results showed that students have a good perception on the use of a multiple solution method in mathematics learning. A multiple solution method can also affect students’ self-regulation. The findings of the open-ended questions show that which are the challenges faced by students when use multiple solution method are get confused because it has many methods, it is hard because students lack mathematics skill, and also involve time constraints because they need to memorize many methods.
Manager selection using Fuzzy TOPSIS method
Authors: Baharin Nur Hannani , Rashidi Nur Fazlin , Mahad Nor Faradilah
Published: August 2021

Due to increasing competition in the global market, companies need employees especially managers who are knowledgeable and skilful to compete in the world market. Proper selection of managers can ensure the accomplishment of company goals. This study aims to propose Fuzzy Technique for order preference by similarity to ideal solution (TOPSIS) method in hiring new personnel for the middle level manager position in a company. The aim of the study is to assess the alternatives and criteria weights for selecting the middle level manager in a company by using Fuzzy TOPSIS method. A real-life data about the middle level manager selection problem in a company is implemented to demonstrate the application of Fuzzy TOPSIS method. There are three decision makers, three selected alternatives (A1, A2, A3) and twelve chosen criteria in the study. The best alternative is the alternative which is close to fuzzy positive ideal solution (FPIS) and far from fuzzy negative ideal solution (FNIS). Other than that, the sensitivity analysis is performed to validate the results of the study by shifting the weight of each criterion to zero to check whether there is any influence on the final ranking of the alternatives. The findings showed that the ranking order is A1 > A2 > A3. This shows that A1 is the most preferable candidate for the middle level manager position in the company.
The application of AHP-PROMETHEE II for supplier selection
Authors: Isa Muhammad Akmal Md , Saharudin Nor Shahirah , Anuar Natasha Bella , Mahad Nor Faradilah
Published: August 2021

The evaluation and selection of the best supplier is a crucial decision-making process as it can reduce the supply chain cost and increase the quality of items supplied to a company. Choosing suppliers solely based on their previous experiences may contribute to higher purchase risk. The decision-making process is usually influenced by a variety of criteria that are often in conflict. Thus, this study employs the integration of Analytic Hierarchy Process (AHP) method and Preference Ranking Organization Method for Enrichment of Evaluation (PROMETHEE) II to handle supplier selection issues. AHP method was adopted to evaluate the weights of criterion. PROMETHEE II is a Multi-Attribute Decision Making method that is based on a mutual comparison of each alternative pair with respect to each of the selected criterion allowing the rankings of the alternatives from the best to the worst. A real-life data about supplier selection for railways project was used to demonstrate the operation of AHP-PROMETHEE II method. The data involved four decision makers, five alternatives (SI, S2, S3, S4, S5) and eight criteria specifically; aspect of the items (C1), arrangement of time (C2), shipment accomplishment (C3), total price of the item (C4), way of payment (C5), relation with supplier (C6), scope of product (C7), and supplier’s professional ability (C8). The findings showed that C4 was the most preferred criterion among the chosen criteria. Thus, the ranking order for criteria was C4 > C8 > C1 > C2 > C5 > C7 > C6 > C3 while the ranking order for the alternatives was S2 > S1 > S4 > S3 > S5, respectively. The findings were then compared with the result from the previous research. The sensitivity analysis was conducted by reducing criteria weights to zero. In conclusion, AHP-PROMETHEE II can be used to analyse the perfect order from best to worst.
Linear Programming Model for Investment Problem in Maximizing the Total Return
Authors: Nordin Syarifah Zyurina , Johar Farhana , Abu Noratikah
Published: August 2021

In this paper, we concentrate on the investment problem of fixed deposit (FD). Our problem is to allocate the amount invested to a suitable tenure and obtain the optimal investment. There are two types of maturity that need to be considered which are short-term and long-term. Our objective is to maximize the total return of the total amount invested with a different percentage of annual return. A linear programming (LP) model is proposed to solve this investment problem using scheduling methodology. We conduct a computational experiment of a real case study for one company located in Kuala Lumpur with RM 20.6 million of investment to see the performance of the model by using the Excel Solver Parameter package. The results show that a significant improvement obtains by our model compared to the original investment practice by the company.
The n-th coprime probability and its graph for some dihedral groups
Authors: Zulkifli N , Mohd Ali N M , Bello M , Nawi A A
Published: August 2021

The coprime probability and graph have been studied for various groups by many researchers focusing on the generalization of the probability part. For the coprime graph, the types and properties of the graph have been investigated and the patterns that can be found within a group are analysed. The coprime probability of a group is defined as the probability that the order of a random pair of elements in the group are relatively prime or coprime. Meanwhile, the coprime graph can be explained as a graph whose vertices are elements of a group and two distinct vertices are adjacent if and only if the greatest common divisor of the order of the first vertex and order of the second vertex is equal to one. It was unfortunate that the exploration of probabilities and graphs of groups have not considered both then-th coprime probability and its graph that ultimately became the target in this research. Hence, the newly defined terms are then used to find the generalizations of then-th coprime probability and then-th coprime graphs for some dihedral groups. The types and properties of the graphs are also discussed in this research.
The perfect codes of commuting zero divisor graph of some matrices of dimension two
Authors: Zaid Nurhidayah , Sarmin Nor Haniza , Khasraw Sanhan Muhammad Salih , Gambo Ibrahim , Zai Nur Athirah Farhana Omar
Published: August 2021

The study of graph properties has gathered many attentions in the past years. The graph properties that are commonly studied include the chromatic number, the clique number and the domination number of a finite graph. In this study, a type of graph properties, which is the perfect code is studied. The perfect code is originally used in coding theory, then extended to other fields including graph theory. Hence, in this paper, the perfect code is determined for the commuting zero divisor graphs of some finite rings of matrices. First, the commuting zero divisor graph of the finite rings of matrices is constructed where its vertices are all zero divisors of the ring and two distinct vertices, say x and y, are adjacent if and only if xy = yx = 0. Then, from the vertex set of the graph, the neighborhood elements of the vertices are determined in order to compute the perfect codes of the graph.
Independence polynomial of the commuting and noncommuting graphs associated to the quasidihedral group
Authors: Najmuddin Nabilah , Sarmin Nor Haniza , Erfanian Ahmad
Published: August 2021

An independence polynomial is a type of graph polynomial from graph theory that store combinatorial information such as the graph properties or graph invariants. The independence polynomial of a graph contains coefficients that represent the number of independent sets of certain sizes and the degree of the polynomial denotes the independence number of the graph. A graph of group G is called commuting graph if the vertices are noncentral elements of G and two vertices are adjacent if and only if they commute in G. Meanwhile, a noncommuting graph of a group G has a vertex set that contains all noncentral elements of G and two vertices are adjacent if and only if they do not commute in G. Since the group properties can be presented as graph from graph theory, then the graph polynomial of such graph should also be identified. Therefore, in this research, the independence polynomials are determined for the commuting and noncommuting graphs that are associated to the quasidihedral group.
Coefficient problems of bi-univalent functions with respect to symmetric and symmetric conjugate points defined by the Al-Oboudi operator
Authors: Rossdy Munirah , Omar Rashidah , Soh Shaharuddin Cik
Published: August 2021

We present and investigate two additional subclasses of bi-univalent functions corresponding to symmetric and symmetric conjugate points in the open unit disc employing the Al-Oboudi operator. The initial coefficients of functions assigned to these classes are estimated.
New Class of 2-Partition Poisson Quadratic Stochastic Operators on Countable State Space
Authors: Karim Siti Nurlaili , Hamzah Nur Zatul Akmar , Fauzi Nurfarhana Nisa Muhammad , Ganikhodjaev Nasir
Published: August 2021

The idea of quadratic stochastic operator (QSO) which was originally introduced by Bernstein in the early 20th century through his work on population genetics has been significantly developed for decades to describe dynamical systems in many areas. In this research we construct the dynamical systems generated by a new class of 2-partition of Poisson QSO defined on countable state space, X = {0,1,2,…}. Our main goal is to investigate the trajectory behavior of such operators by reducing its infinite variables into a one-dimensional setting that correspond to the number of defined partitions. We present some cases of 2-measurable partition with singleton and two points of two different parameters. Measure and probability theory alongside the functional analysis will be applied to investigate the limit behavior and characteristics of fixed points. These results suggest that the QSO generated by a 2-measurable partition defined on countable state space for both singleton and two points of two different parameters is a regular transformation for some values of parameters.
Deoxyribonucleic Acid (DNA) Splicing System from Graph Theoretic Perspective
Authors: Ruslim Nooradelena Mohd , Elizabeth Marta , Yusof Yuhani , Mohamad Mohd Sham , Adzhar Noraziah
Published: August 2021

In 1987, Head introduced the recombinant process of deoxyribonucleic acid (DNA) splicing system through a framework of Formal Language Theory. To express this phenomenon, a comprehensive writing system of the rule sets, proper terms and definitions pioneerly introduced by Head. The analysis on the recombinant behavior of double-stranded DNA molecules, characteristics and various type of splicing systems has sparks the researcher to explore more splicing mechanism extensively. The aim of this paper is to give an exhaustive review on the application of graph in DNA splicing system.
Existence of quasidouble lines of a pair

(f15,Δ(135))

in Euclidean space E5
Authors: Matieva Gulbadan , Abdullayeva Cholpon , Artykova Zhyldyz
Published: August 2021

The domain Ω⊂ E5 is considered a set of smooth lines such that through a point X⊂Ω passed one line of a given set. The moving frame

ℜ

(

X
,

e
→

i

)

,

(

i
,
j
,
k
=
1
,
2
,
3
,
4

)

is a frame of Frenet for the line ω
1 of the given set. Integral lines of the vector fields

e
→

i

are formed in the net Σ5 of Frenet. There exist a point

F
1
5

∈

(

X
,

e
→

1

)

on the tangent of the line ω
1. When the point X is shifted in the domain Ω, the point

F
1
5

. describes it’s domain

Ω
1
5

in E
5. The partial mapping is defined as

f
1
5

:
Ω
→

Ω
1
5

such that

f
1
5

(
X
)

=

F
1
5

. Necessary and sufficient conditions in so that the line γ belong to the three-dimensional distribution

Δ

(

135

)

=

(

X
,

e
→

1

,

e
→

3

,

e
→

5

)

is a quasi-double line of the pair

Δ

(

135

)

=

(

F
1
5

,

Δ

(

135

)

)

is established.
Identifying rainfall patterns using Fourier series: A case of daily rainfall data in Sarawak, Malaysia
Authors: Asmat Aszila , Wahid Sharifah Norhuda Syed , Deni Sayang Mohd
Published: August 2021

The a im for this paper is to fit Fourier series on the daily rainfall data to describe the rainfall patterns and to identify the time frame of the wettest and the driest period for the studied stations. The estimated parameter of the Fourier series in modelling the mean daily rainfall amount received were obtained using the method of Generalized Linear Model and the performance was evaluated using the analysis of deviance. Following the objective, the daily rainfall data ranges from 41 to 58 years over four stations in Sarawak namely Kuching, Miri, Bintulu a nd Sibu are studied. Results showed three harmonics is appropriate in modelling the mean daily rainfall received for Kuching, Sibu and Miri stations. However, only two harmonics was found to be fitted the mean daily rainfall amount received significantly for Bintulu station. The wettest month of the studied stations wa s estimated to occur in late December to early January, whereas the driest month is in March for Miri station, April for Bintulu, July for Kuching a nd June for Sibu station. The information gained from this study can be used to monitor the occurrence of flood and drought events in the area so that future action can be taken to reduce the impacts.
Does trade openness explain the deviation of purchasing power parity and exchange rate movement?
Authors: Ang A L , Thum Y T , Sek S K
Published: August 2021

Real exchange rate movements are important in determining a country’s competitiveness and trade flows. The real exchange rate also plays an important role in postulating a relationship between exchange rates and prices as explained in the theory of purchasing power parity (PPP). In this study, we examine the validity of PPP theory in four groups of economies (developed, developing, high, and low trade openness economies) from 1980 to 2016. Our main objective is to examine if trade openness matters in determining the validity of PPP. The study applied the panel unit-root tests to test for the PPP theory. Besides, a static panel threshold regression is applied to investigate the main determinants of real exchange rate movements besides testing the relative PPP theory. The panel unit-root tests revealed the validity of relative PPP theory in all cases. However, the threshold regression reported that the PPP condition may not hold in all regimes when a nonlinearity relationship exists. Foreign and domestic prices are influential in determining the PPP relationship.
Modeling the distribution of duration time for unhealthy air pollution events
Authors: Masseran N , Safari M A M , Hussain S I
Published: August 2021

The information about how long a severe unhealthy air pollution event will last is crucial for the purpose of planning a possible measure to mitigate its risk. Thus, analyzing the distribution of duration data on the past occurrences of air pollution events is important. This study analyzes the hourly data of air pollution index (API) in Klang City, Malaysia from 1997 to 2018. Air pollution duration data are determined from the period when API > 100, preceded and followed by periods when API < 100. In this study, four types of statistical distributions, namely, Exponential, Gamma, Lognormal, and Weibull are proposed as practical models. Goodness-of-fit measures are compared for each distribution to determine the best fitted one to describe the observed data. Results indicate that the Lognormal distribution provides the best fitted model among others.
The prevalence of Helicobacter pylori in referral population of Turkey
Authors: Usarov Komiljon , Ahmedov Anvarjon , Abasiyanik Mustafa Fatih , Khalif Ku Muhammad Na’im Ku , Akhmedov Abdulkasim
Published: August 2021

Helicobacter pylori infection is commonly associated with gastroduodenal diseases in humans, such as chronic gastritis and peptic ulcers, gastric mucosa-associated lymphoid tissue lymphoma, and even gastric cancer, which leads to high cost to society for treatment and even to death many people, when people do not know early of the infection prevalence. In this work we proposed a forecasting model to predict the infection prevalence. Based on our results society can make simple early prevention acts against the infection. The early prevention acts decrease the cost of treatment and save many people’s lives in the world.
Model fitting for Malaysian mortality rate: Comparison of Heligman-Pollard and P-splines smoothing
Authors: Edrus Robiaatul Adawiah , Siri Zailan , Haron Mohd Azmi , Safari Muhammad Aslam Mohd
Published: August 2021

Malaysia has been experiencing longevity risk since the last decade due to improvements of mortality rates. Longevity risk refers to the probability of a person living longer than expected. According to the Department of Statistics Malaysia, a baby born in the year 2018 is predicted to live an average life of 75 years. Since the minimum retirement age policy of 60 years had come into force in 2012, the 2018 baby would live approximately 15 more years after retirement. Therefore, this study aims to compare the Heligman-Pollard and P-splines smoothing for fitting the Malaysian mortality rate. This model fitting will give a clear picture of the mortality pattern in predicting the mortality rate accurately, especially for the baby boomer generation. The data obtained from the Department of Statistics Malaysia are split into groups of five years, from 0 to 75 years old, and time ranges from 1995 to 2018. The data set from 1995 to 2010, known as the training set is used to fit the mortality rate. After fitting the mortality rate for both methods, this study will measure the performance in the testing set from 2011 until 2018. This study uses the mean absolute percentage error (MAPE) to identify the better method to fit the Malaysian mortality rate. Based on the MAPE values, P-splines smoothing gives a relatively smaller value compared to the Heligman-Pollard. For overall performance from 1995 to 2018, P-spline smoothing has proven to fit the Malaysian data well.
Comparison of Robust Estimators for Detecting Outliers in Multivariate Datasets
Authors: Mutalib Sharifah Sakinah Syed Abd , Satari Siti Zanariah , Yusoff Wan Nur Syahidah Wan
Published: August 2021

Detecting outliers for multivariate data is difficult and does not work by visual inspection. Mahalanobis distance (MD) has been a classical method to detect outliers in multivariate data. However, classical mean and covariance matrix in MD suffer from masking and swamping effects. Masking effects happened when outliers are not identified and swamping effects happened when inliers are identified as outliers. Hence, robust estimators have been proposed to overcome these problems. In this study, the performance of a new robust estimator named Test on Covariance (TOC) is tested and compared with other robust estimators which are Fast Minimum Covariance Determinant (FMCD), Minimum Vector Variance (MVV), Covariance Matrix Equality (CME) and Index Set Equality (ISE). These five robust estimators’ performance is being tested on five real multivariate datasets. Brain and weight, Hawkins-Bradu Kass, Stackloss, Bushfire and Milk datasets were used as these five real datasets are well-known in most outlier detection studies. Results show that TOC has proven to be able in detecting outliers, does not have a masking effect and has the same performance as other robust estimators in all datasets.
Modelling wind direction data of Langkawi Island during Southwest monsoon in 2019 to 2020 using bivariate linear functional relationship model with von Mises distribution
Authors: Mokhtar Nurkhairany Amyra , Zubairi Yong Zulina , Hussin Abdul Ghapor , Badyalina Basri , Ghazali Ahmad Faiz , Ya’acob Fatin Farazh , Shamala Palaniappan , Kerk Lee Chang
Published: August 2021

The weather in Malaysia is characterised by two monsoons, namely, the southwest monsoon from May to September, and the northeast monsoon from November to March. Wind direction is essential in observing the weather patterns and global climate. In this study, our interest is on investigating the relationship of the wind direction data of Langkawi Island in Malaysia during the southwest monsoon from year 2019 to 2020. It is essential to highlight that wind direction data that is circular and this requires different statistical techniques from the techniques that are used to analyse linear data. In this paper, we model the relationship of wind direction data by using the bivariate functional relationship model with von Mises distribution. The magnificence of this model is that the existence of error terms in all variables is considered. When modelling the data, outliers of the wind direction data are identified by using thecovratiomethod that considers row deletion. The covariance matrix of the parameter estimates of the data is obtained by using the Fisher information matrix. Also, the result is supported by the Q-Q plots of the von Mises that indicate the goodness-of-fit of the wind direction data to the von Mises distribution. Then, maximum likelihood estimation is used in obtaining the parameter estimates of the data and hence, the model of the wind direction data is attained. The implications of this study provides an improved comprehension of the behaviour of wind direction and may be used for the prediction of wind energy in future.
Evaluation of generated bootstrap weight in layer perceptron for Southeast Asia visitors during COVID19 outbreak
Authors: Fatihah C O S , Hila N Z , Shaharudin S M , Tarmizi R A , Romli N
Published: August 2021

The pandemic COVID-19 effected the global business sector include the tourism industry. Forecasting the visitor arrival from Southeast Asia is a vital for organized the economy impact at Malaysia state, particularly during this outbreak. Neural network family has been substantial approaches in tourism and the economy. The layer perceptron is a part of the neural network model which is used to produce accurate forecasting. However, the inherent biasness in the perceptron algorithm could lead to an underfitting problem which eventually leads to poor performance of forecast accuracy. The motivation of this study is to improve the accuracy of single-layer perceptron in forecasting the Southeast Asia visitors in Malaysia during COVID19. In this study, the bootstrap weights are generated at the hidden layer to reduce the biasness in output layer. The forecasting result of generated bootstrap weight model is compared with conventional perceptron model in terms of small bias estimation. The statistical results revealed that the generated bootstrap weight in perceptron provides accurate forecasting for Southeast Asia visitors during COVID-19.
Geographically Weighted Regression on dengue epidemic in Peninsular Malaysia
Authors: Sulekan Ayuna , Suhaila Jamaludin , Wahid Nurmarni Athirah Abdul
Published: August 2021

Dengue has been a global epidemic since World War II, with millions of individuals being infected every year. Repetitive dengue epidemic is one of the main health problems that, due to its rapid spread and geographically widespread, has become a major concern for the government authorities in dealing with this disease. In Malaysia, cases of dengue are reported annually. To keep cases under control, it is important to examine the possible factors that help the growth of the virus. Climatological factors such as rainfall, temperature, wind speed, and humidity are expected to have high potential to increase the growth of the virus in this study, and their spatial variation is associated with cases of dengue. The result revealed that Ordinary Least Square was not an effective method for modelling the relationships between dengue cases and climate variables, as climate variables in different spatial regions act differently. During the analysis, there could be some issues of non-stationarity since the geographical aspect and spatial data were involved. Hence, the Geographically Weighted Regression (GWR) is implemented due to its capability to identify the spatial non-stationarity behavior of influencing factors on dengue incidence and integrate the geographical location and altitude for the spatial analysis. GWR analysis found that the influenced factors exhibited a significant relationship with dengue incidence. GWR also shows a significant improvement in Akaike Information Criteria (AIC) values with the lowest value and the highest adjusted R square. It is expected that the developed model can help the local hygienic authorities design better strategies for preventing and controlling this epidemic in Malaysia.
COVRATIO statistic for replicated linear functional relationship model
Authors: Mohd Arif A , Zubairi Y Z , Hussin A G
Published: August 2021

Replicated linear functional relationship model (LFRM) can be categorized under the errors-in-variables model where variables involved are measured with error. However, the presence of outliers in dataset significantly impacts the parameter estimation. We extend the use of the COVRATIO statistic which has been successfully used in unreplicated LFRM for detecting the outliers. A simulation study is used to obtain the cut-off point at 10% upper percentiles. An illustration of this procedure is presented for its potential in a real data set. The procedure successfully identifies the outlier present in the data set.
Priors comparison in Bayesian Models of risk factor of Malaysian coronary artery disease male patients
Authors: Juhan Nurliyana , Zubairi Yong Zulina , Zuhdi Ahmad Syadi Mahmood , Khalid Zarina Mohd
Published: August 2021

Coronary artery disease (CAD) continues to be one of the leading causes of morbidity and mortality globally. Of particular relevance for this issue is that major efforts should be focused on understanding the risk factor involved. In this study, three types of Bayesian models, each with different prior distribution were considered to identify associated risk factors in CAD among Malaysian male patients presenting with ST-Elevation Myocardial Infarction (STEMI) and to obtain a feasible model to fit the data. The results of the three models were compared to find the best model. A total of 7180 STEMI male patients from the National Cardiovascular Disease Database-Acute Coronary Syndrome (NCVD-ACS) registry year 2006-2013 were analysed. Univariate and multivariate analyses for the three models were performed using one of the Bayesian Markov Chain Monte Carlo (MCMC) simulation approach known as Gibbs sampling. Models’ performances are evaluated through overall model fit. Bayesian model C which used both Beta and Dirichlet prior distributions, consisted of six significant variables namely diabetes mellitus, family history of cardiovascular disease, chronic lung disease, renal disease, Killip class and age group was considered as the best model. The same set of variables that were observed to be significant in the Bayesian model C was also found to be significant in models A and B which used single prior distribution, respectively. Model C has a better fit than models A and B as the deviance value produced was the smallest. This study showed that posterior estimation was mostly influenced by the existing prior knowledge. Though applying the non-informative prior which were both Beta and Dirichlet distribution priors, model C can minimise uncertainty in making effective clinical decisions and provides better parameters estimates of the posterior distribution.
Effect of climate factors on Hand-Foot-Mouth Disease: A generalized additive model approach
Authors: Wahid N A A , Suhaila J , Rahman H A , Sulekan A
Published: August 2021

Hand, foot, and mouth disease (HFMD) has become an endemic childhood disease in Asia, including Malaysia, over the last few decades. This infectious disease caused by the Entero and Coxsackie viruses has been a major public health threat in Malaysia since 1997. Climate change has been considered an influential factor in HFMD cases and has been explored in other countries using various statistical analyses. The most popular is the Generalized Linear Model (GLM). However, GLM often fails to capture the non-linearity effect of the variables. The study, therefore, proposes to use the Generalized Additive Model (GAM) to analyse the non-linear effects of temperature, humidity, rainfall, and wind speed at varying time lags of HFMD in Selangor. In summary, the result indicates that the weekly temperature, humidity, and rainfall were significantly associated with HFMD cases in Selangor and clarified with two weeks of lag time. This disease’s risk increased in the subsequent two weeks with a temperature range of 27°C to 30°C, 70% to 85% of humidity, and 5mm to 20mm of rainfall. Besides, this study also found that the seasonal distribution of HFMD in Selangor has a large peak during the Southwest monsoon. A small peak was observed at the end of the year during the Northeast monsoon. The findings of this study could be a practical guide for HFMD intervention strategies, especially in Malaysia.
Piecewise linear modelling and change-point analysis of COVID-19 outbreak in Malaysia
Authors: Phang P , Abdul Taib N A , Safii R , Labadin J
Published: August 2021

In Malaysia, COVID-19 were first detected as imported cases on 25 January and as local infection on 4 February 2020. A surge of positive cases ensued by March 2020 which led to a series of countrywide containment and mitigation measures known as Movement Control Order (MCO). We study the direct effects of MCO on the course of epidemic by analyzing the cumulative and daily infection cases of COVID-19 up to 31 December 2020 in Malaysia and its states using piecewise linear regression and segment neighborhoods algorithm of change-point analysis, respectively. Through piecewise regression on nationwide cases, MCO were likely to almost flatten the epidemic curve in just one month after it was first initiated. While for stateswise cases, the average length of series of concave downward is six months before it turn to concave upward, indicating the period of which deceleration of new cases can be expected. However, the starting of this wave of COVID-19 can be relatively vary for three months in different states and federal territories. Together with change-point analysis on daily cases, the statewise epidemic phases could be subdivided into two to four regimes, whereby the majority of phase transitions fall in April and last quarter of 2020. Overall, the statistical modelling shows that the immediate effect of MCO appears to be effective.
Assessing the adequacy of the gompertz regression model in the presence of right censored data
Authors: Maarof Nur Niswah Naslina Azid @ , Arasan Jayanthi , Zulkafli Hani Syahida , Adam Mohd Bakri
Published: August 2021

The Gompertz distribution is often used to model human mortality and establish actuarial tables. Cox-Snell residual is the most general practice to evaluate the model adequacy. However, standard statistical procedures are not amenable to handle the censored observations. Therefore, this research investigates the adequacy of the two parameter Gompertz parametric survival model that was extended to incorporate with fixed covariate in the presence of right censored data. Performance of the model is assessed and compared at various combinations of sample sizes and censoring proportions via simulation study. The newly proposed modifications to the Cox-Snell residuals based on the geometric mean and harmonic mean as well as the jackknife means were compared with Cox-Snell and Modified Cox-Snell residuals via simulation studies at different settings. The log-cumulative hazard plot of residuals is obtained by plotting the proposed residuals against the cumulative hazard function to assess the model’s fit. Based on the model adequacy study, we found out that jackknife geometric mean and jackknife harmonic mean outperform CS, MCS, GMCS and HMCS residuals.
Effects of climate and irrigation on GRACE-based estimates of water storage changes in major US aquifers
Authors: Scanlon Bridget R , Rateb Ashraf , Pool Donald R , Sanford Ward , Save Himanshu , Sun Alexander , Long Di , Fuchs Brian
Published: August 2021

Understanding climate and human impacts on water storage is critical for sustainable water-resources management. Here we assessed climate and human drivers of total water storage (TWS) variability from Gravity Recovery and Climate Experiment (GRACE) satellites compared with drought severity and irrigation water use in 14 major aquifers in the United States. Results show that long-term variability in TWS tracked by GRACE satellites is dominated by interannual variability in most of the 14 major US aquifers. Low TWS trends in the humid eastern U.S. are linked to low drought intensity. Although irrigation pumpage in the humid Mississippi Embayment aquifer exceeded that in the semi-arid California Central Valley, a surprising lack of TWS depletion in the Mississippi Embayment aquifer is attributed to extensive streamflow capture. Marked storage depletion in the semi-arid southwestern Central Valley and south-central High Plains totaled ∼90 km3, about three times greater than the capacity of Lake Mead, the largest U.S. reservoir. Depletion in the Central Valley was driven by long-term droughts (⩽5 yr) amplified by switching from mostly surface water to groundwater irrigation. Low or slightly rising TWS trends in the northwestern (Columbia and Snake Basins) US are attributed to dampening drought impacts by mostly surface water irrigation. GRACE satellite data highlight synergies between climate and irrigation, resulting in little impact on TWS in the humid east, amplified TWS depletion in the semi-arid southwest and southcentral US, and dampened TWS deletion in the northwest and north central US Sustainable groundwater management benefits from conjunctive use of surface water and groundwater, inefficient surface water irrigation promoting groundwater recharge, efficient groundwater irrigation minimizing depletion, and increasing managed aquifer recharge. This study has important implications for sustainable water development in many regions globally.
Elevated risk of tropical cyclone precipitation and pluvial flood in Houston under global warming
Authors: Zhu Laiyin , Emanuel Kerry , Quiring Steven M
Published: August 2021

Pluvial floods generated by tropical cyclones (TCs) are one of the major concerns for coastal communities. Choosing Houston as an example, we demonstrate that there will be significantly elevated risk of TC rainfall and flood in the future warming world by coupling downscaled TCs from Model Intercomparison Project Phase 6 models with physical hydrological models. We find that slower TC translation speed, more frequent stalling, greater TC frequency, and increased rain rate are major contributors to increased TC rainfall risk and flood risk. The TC flood risk increases more than the rainfall. Smaller watersheds with a high degree of urbanization are particularly vulnerable to future changes in TC floods in a warming world.
A vital option for food security and greenhouse gases mitigation: planting elite super rice in double- to single-rice cropping fields in China
Authors: Fan Dongli , Fan Yidan , Tian Zhan , Li Xiubin , Jiang Min , Sun Laixiang , Zhong Honglin , Wang Kai , Wang Xiangyi , Jiang Luguang
Published: August 2021

Double-rice cropping (DRC) in southern China has made outstanding contributions to ensuring food security, along with a large amount of greenhouse gas (GHG) emissions. The observed significant shift from double- to single-rice (DtS) cropping since 1990 in southern China has led to great concerns on food security, despite its contribution to GHG emissions reduction. How to ensure food security without compromising the goal of mitigating GHG emission requires innovative thinking and a comprehensive tradeoff analysis of all plausible options. This study adopts a multi-model coupling method to simulate the yield and GHG emissions trade-offs across grid-cells by incorporating the option of planting elite super rice in the DtS areas. The simulation results indicate that planting elite super rice with longer growth period in the DtS areas has the potential to compensate the annual yield loss caused by the DtS shift while significantly mitigating GHG emissions in comparison with the conventional DRC. In more detail, while the yield and GHG emissions of prevailing single-rice cropping are 48% (±2%) and 54% (±4%) lower than the corresponding (two-season sums) figures of conventional DRC under the current irrigation practice of midseason drainage, the yield and GHG emissions of super rice are 15% (±4%) and 44% (±6%) lower than the above reference figures if the emerging irrigation regime of alternate wetting and drying is adopted. Furthermore, our modeling simulations demonstrate the feasibility of promoting elite super rice cultivars across southern China. The research suggests a viable option for China to balance the trade-off between food security and GHG mitigation.
Assessment of wind energy potential of Hat Yai (Songkhla), Thailand
Authors: Kamdar I , Taweekun J
Published: August 2021

Due to environmental problems associated with fossil fuels and rising need for energy, wind power renewable energy will play a vital role in transformation of future energy structure in Thailand. Exploitation of wind energy for sustainable development, wind resource assessment plays an important role in wind power utilization. This case study presents wind resource assessment using the wind atlas analysis and application program (WAsP), in order to assess the potential of wind energy in Hat Yai, Thailand. Ten-minutes interval wind data observed by the Thai Meteorological Department recorded during the period 2017-2019, have been used to harness adequate wind power density and wind energy potential. The annual mean wind speed is 3.5 m/s at 10 m height above the ground. The prevailing direction southwest, south and northeast of the wind rose are very pronounced. The WAsP analysis estimates about 2,731.28 MWh of the total net annual energy production for the specific sites using the Enercon E-18 (80 kW) wind turbine of 1.92 MW capacity. The findings of this study indicate the possibility of the small-scale wind farm project for electricity generation in future.
Effect of pour point depressants and diluents on exergy destruction during pipeline transportation of crude oil
Authors: Kulkarni A D , Wani K S
Published: August 2021

Exergy destruction in pipeline flow of crude oils mixed with pour point depressants (PPD) and diluents has been investigated. Ethylene vinyl acetate with vinyl acetate content of 18% and 28% (EVA-18 and EVA-28) and Polymethyl methacrylate (PMMA) with concentrations of 200 ppm, 1000 ppm and 1500 ppm were chosen as the PPDs for this purpose. Four different diluents were considered viz. n-hexane, cyclohexane, n-butanol and toluene representing paraffins, naphthenes, alcohols and aromatics respectively. The viscosity reduction was found out experimentally. Using these results for a hypothetical pipeline, the effect of API gravity of crude oil, pipeline diameter, Reynolds number, PPD concentration and diluent type on exergy destruction was investigated. These findings would help in making a prudent choice of PPD and diluents for efficient transportation of crude oil through pipelines.
An Investigation of Factors Affecting Measurement Accuracy of Nanoparticles Real-time Sensor using Corona Discharge integrated with Quartz Crystal Microbalance
Authors: Vichayarom Nichakran , Jaruwongrangsri Kata , Tekasakul Perapong , Dejchanchaiwong Racha
Published: August 2021

A nanoparticles real-time sensor in the present study was designed using corona discharge integrated with quartz crystal microbalance (QCM) or Nano-QCM detector. We investigated the following factors affecting the measurement accuracy of the detector; needle to plate distance, flow rate, and number of particles on QCM. DC high voltage power supply of 7 kV was used to maintain the positive corona voltages difference in the charger. The mass sensitivity of 10 MHz AT-cut QCMs coated by plate rigid gold film were investigated. The monodisperse aerosol particles smaller than 300 nm were initially used for the testing of the system. They were charged with negative corona voltages and then deposited on the surface of QCM electrode. Sauerbrey equation was used to describe the frequency-mass relationship at the QCM surface. Results show that the above factors significantly affect the accuracy of the detector measurement. The particles can be collected on a QCM electrode using the partial breakdown high voltage (reach to breakdown points) in terms of needle-to-plate corona discharge. The optimal needle-to-plate distance is 6 mm with maximum mass change (frequency shift) on QCM electrode of 0.607μg/min. The QCM collection efficiency of nanoparticles on the QCM electrode surface using corona discharge technique can be as high as 95% of total particles. Collection efficiency of PM0.1 is under investigation.
Design of Fixture for Welding
Authors: Naksri Chanada , Chuchom Somchai , Chaiprapat Supapan
Published: August 2021

Defects commonly found in welding include distortion, overlapping, warping, and misalignment. Welders probably observe more frequent problems as such if lacking proper fixturing devices. Existing fixture designs are tedious to use, and they could induce even more defects. In this study, four design alternatives of a welding fixture were initially conceptualized from a survey of 25 experienced welders before the best one was selected based on reliability, rigidity, and ease of use. The design was made of SS400 steel because of its exceptional mechanical and thermal properties. A structural analysis was performed using the finite element method to evaluate the strength and stability of the design while in use. Experimental results revealed that this fixturing device could withstand forces exerted vertically from screw clamping. It could also tolerate high temperature from a welding arc and restrain the workpiece as deformed by the heat. This novel design will minimize set-up time, chances of defect formation, and a need for post-welding quality improvement.
Optimization of operating parameters for rubber sheet fast drying in a forced-convection rubber smoking room
Authors: Intararak Pennung , Dejchanchaiwong Racha , Tekasakul Perapong
Published: August 2021

A new design of a rubber smoking room for fast drying based on conventional rubber smoking room was tested. Effects of the operating parameters for the fast drying of rubber in a forced-convection rubber smoking room were investigated. Temperature distribution, moisture content, thermal efficiency, specific fuelwood, electricity and energy consumption were evaluated for drying of 1,500 rubber sheets. The suitable operating condition from the experiment is 60°C and 12 m/s for the temperature and velocity. The rubber sheet moisture content was reduced to 0.4% db within 36 hours, i.e. 36 hours less than conventional smoke drying. The variation temperature inside the rubber smoking room was near uniform with a maximum of 8.0°C. The temperatures ranges were 38.9-64.6°C at the front plane, 40.4-65.0°C at the middle plane, and 36.7-62.9°C at the rear plane. A new rubber smoking room can save up to 49.3% in fuelwood consumption as compared to conventional rubber smoking room. Hence, the new rubber smoke drying system is capable of enhancing thermal efficiency and saving energy compared to existing rubber smoking room.