Browse publications by year: 2020

Fulltext Exploring challenges faced by parents of children with tuberculosis in Klang and Petaling districts of Selangor state, Malaysia: A qualitative study

S Maria Awaluddin, Nurhuda Ismail, Siti Munira Yasin, Yuslina Zakaria, Norzila Mohamed Zainudin, Faridah Kusnin, et al.

Journal of Clinical and Health Sciences, 2020;5(2):46-56.
MyJurnal

Introduction: Parents play an essential role in their children’s tuberculosis (TB) treatment
success despite many challenges from the beginning of their children’s symptoms until
completion of the TB treatment. The challenges can be described as perceived barriers,
according to the Health Belief Model, a theory of behaviour change. This study aims to explore
parents’ experiences on the challenges in achieving a successful TB treatment for their child
in two districts of Selangor state, Malaysia. Methods: The research was carried out using a
phenomenology study design. In-depth interviews were conducted among purposively
sampled parents of children with TB disease who have completed TB treatment or still
undergoing treatment from MyTB version 2.1, a national TB surveillance database. The
collected data was considered as achieving its saturation level if no new themes arise from
the latest interviews’ session. The R-based Qualitative Data Analysis (RQDA) package
version 0.2-8 was used for the thematic data analysis. Results: The total number of
participants in this study was 15 mothers of children with TB disease; 12 (80%) of the children
had completed TB treatment. There were six subthemes identified from this study focusing on
the theme of multiple challenges, such as health symptoms challenges, TB investigation
challenges, personal challenges, healthcare facilities challenges, administration medication
challenges, and community challenges. Conclusions: Parents highlighted many challenges
during the child’s illness phase, and they should be given adequate education and appropriate
support to ensure TB treatment adherence. TB program managers should take action
following the relevant parents’ feedback regarding the quality of TB care in a healthcare
facility

MeSH terms: Child; Delivery of Health Care; Feedback; Female; Health Facilities; Humans; Malaysia; Mothers; Parents; Tuberculosis
Fulltext Endocrinopathies in HIV infected patients

Rosdina Zamrud Ahmad Akbar, Sharifah Faradila Wan Muhammad Hatta, Rosnida Mohd Noh, Fatimah Zaherah Mohd Shah, Thuhairah Abdul Rahman, Rohana Abdul Ghani, et al.

Journal of Clinical and Health Sciences, 2020;5(2):39-45.
MyJurnal

Introduction: Hormonal abnormality is one of many clinical manifestations of HIV infections
that is not well understood. However, the consequences could affect quality of life and are
potentially treatable. Thus, this study aimed to determine the prevalence and associated
factors of thyroid, adrenal and gonadal dysfunctions among HIV-infected patients. Methods:
This is a single centre cross-sectional study involving 150 HIV-infected patients attending the
HIV clinic. Each subject was required to answer specific symptoms questionnaire and their
medical records were reviewed for relevant clinical and biochemical data. Blood for was
collected and thyroid hormones, cortisol, ACTH, FSH, LH, testosterone and estradiol were
analysed using electrochemiluminescent immunoassay. Thyroid, adrenal and gonadal axes
abnormalities were identified. Results: Hypogonadism had the highest prevalence amongst
the endocrine abnormalities, which was detected in 23 patients (15.3%), followed by thyroid
dysfunction in 18 patients (12%) and hypocortisolism in 2 patients (1.3%). There was
significant correlation between CD4 count, BMI and age with the hormone levels. Conclusion:
Prevalence of endocrine abnormalities was low in these well-treated HIV-positive patients,
with hypogonadism being the most common. However, significant correlations between CD4
count, age and BMI with the hormonal levels were detected. Clinical symptoms in relation to
endocrinopathy are not specific as a screening tool thus underscoring the need for
biochemical tests to identify these treatable conditions.

MeSH terms: Addison Disease; Adrenocorticotropic Hormone; Cross-Sectional Studies; Endocrine System Diseases; Estradiol; Follicle Stimulating Hormone; Humans; Hydrocortisone; Hypogonadism; Immunoassay; Medical Records; Quality of Life; Surveys and Questionnaires; Testosterone; Thyroid Gland; Thyroid Hormones; HIV Infections; Body Mass Index; Prevalence; CD4 Lymphocyte Count
Fulltext Familial hypercholesterolaemia: an updated overall management

Noor Alicezah Mohd Kasim, Chua Yung An, Hapizah Nawawi

Journal of Clinical and Health Sciences, 2020;5(2):19-38.
MyJurnal

Familial hypercholesterolaemia (FH), the commonest and serious but potentially treatable
form of inherited dyslipidaemias, is characterised by severely elevated plasma low-density
lipoprotein-cholesterol (LDL-C) level, which subsequently leads to premature coronary artery
disease (pCAD). Effectiveness of FH early detection and treatment is supported by the
outcome of several international cohort studies. Optimal FH management relies on
prescription of statins either alone or together with other lipid-lowering therapies (LLT).
Intensive lifestyle intervention is required in parallel with LLT, which should be commenced at
diagnosis in adults and childhood. Treatment with high intensity statin should be started as
soon as possible. Combination with ezetimibe and/or bile acid sequestrants is indicated if
target LDL-C is not achieved. For FH patients in the very-high risk category, if their LDL-C
targets are not achieved, despite being on maximally tolerated statin dose and ezetimibe,
proprotein convertase subtilisin/kexin type1 inhibitor (PCSK9i) is recommended. In statin
intolerance, ezetimibe alone, or in combination with PCSK9i may be considered. Clinical
evaluation of response to treatment and safety are recommended to be done about 4-6 weeks
following initiation of treatment. Homozygous FH (HoFH) patients should be treated with
maximally tolerated intensive LLT and, when available, with lipoprotein apheresis. This review
highlights the overall management, and optimal treatment combinations in FH in adults and
children, newer LLT including PCSK9i, microsomal transfer protein inhibitor, allele-specific
oligonucleotide to ApoB100 and PCSK9 mRNA. Family cascade screening and/or screening
of high-risk individuals, is the most cost-effective way of identifying FH cases and initiating
early and adequate LLT.

MeSH terms: Ezetimibe; Adult; Alleles; Hypolipidemic Agents; Bile Acids and Salts; Blood Component Removal; Child; Coronary Vessels; Cost-Benefit Analysis; Humans; Hyperlipoproteinemia Type II; Life Style; Cholesterol, LDL; Oligonucleotides; Plasma; RNA, Messenger; Hydroxymethylglutaryl-CoA Reductase Inhibitors; Subtilisin; Dyslipidemias; Prescriptions; Proprotein Convertase 9
Fulltext Are our healthcare workers well protected during COVID-19? learning from current experiences and challenges

Siti Munira Yasin,, Kamarulzaman Muzaini, Ely Zarina Samsudin, Mohamad Ikhsan Selamat, Zaliha Ismail

Journal of Clinical and Health Sciences, 2020;5(2):4-18.
MyJurnal

The outbreak of novel coronavirus disease 2019 (COVID-19) has been declared a Public
Health Emergency of International Concern by the World Health Organization. The incidence
of this pandemic continues to rise, with 40,665,438 confirmed cases and 1,121,843 deaths
worldwide by 21 October 2020. During this public health crisis, healthcare workers are at the
frontline of the COVID-19 outbreak response, and as such are at risk of being infected and
developing job burnout while in the line of duty. This study reviews the history of COVID-19
outbreak, infection control measures in hospitals during COVID-19 outbreak, healthcare
workers’ risk of infection and other health effects from battling COVID-19, and challenges and
recommendations for protecting healthcare workers during this pandemic. At present,
healthcare workers are every country’s most valuable resources, and their safety must thus
be ensured. Strong medical leadership, clear pandemic planning, policies and protocols,
continuous educational training, adequate provision of personal protective equipment,
psychological support, and the provision of food, rest, and family support for healthcare
workers would augment a climate of safety in the workplace, ensure their wellbeing, and
improve their capacity to battle this ongoing pandemic.

MeSH terms: Personal Protective Equipment; Burnout, Professional; Delivery of Health Care; Disease Outbreaks; Health Personnel; Hospitals; Humans; Leadership; Public Health; World Health Organization; Incidence; Infection Control; Workplace; Coronavirus; Policy; Pandemics
Fulltext Minimally invasive coronary artery bypass graft surgery: personal perspective

Mohd Zamrin Dimon

Journal of Clinical and Health Sciences, 2020;5(2):1-3.
MyJurnal

-
Fulltext Mapping the Age of Laboratory Rabbit Strains to Human

Sengupta P, Dutta S

Int J Prev Med, 2020;11:194.
PMID: 33815718 DOI: 10.4103/ijpvm.IJPVM_530_18

Rabbit strains find immense application in biomedical research with every strain having their discrete advantage in specific research endeavor. Acceptability of rabbit strains as laboratory animals owes to their breeding ease, availability, cost-effectiveness, ethical conveniences, larger size, compared to rats and mice, and responsiveness. With respect to different life phases, the article displays that one human year is equivalent to: (1) in developmental phase, 56.77 days for New Zealand White (NZW) and New Zealand Red (NZR) rabbits, 71.01 days for Dutch belted and Polish rabbits, and 85.28 days for Californian rabbits; (2) in the prepubertal phase, 13.04 days for NZW and Dutch belted, 15.65 days for NZR and Californian, and 10.43 days for Polish rabbits; (3) in the adult phase, 18.25 days for NZW and Californian rabbits, 22.75 days for NZR, and 12 days for Dutch Belted and Polish rabbits; (4) during reproductive senescence, 42.94 days for NZW, NZR and Californian rabbits, 28.62 days for Dutch belted, and 25.05 days for Polish rabbits; (5) in the post-senescence phase, 50.34 days for NZW, 25.17 days for NZR, Dutch Belted and Californian and 31.46 days for Polish rabbits. The laboratory rabbit strains differ in various physiological, developmental and genetic make-ups, which also reflect upon the correlation of their age at different life stages with that of a human. The present article aids selection of laboratory rabbit strain of accurate age as per experimental need, by precisely relating the same with age of human considering different life stages.

MeSH terms: Adult; Animals; Animals, Laboratory; Breeding; Climacteric; Cost-Benefit Analysis; Humans; Laboratories; Menopause; New Zealand; Poland; Rabbits; Biomedical Research; Mice; Rats
Fulltext Devastating urban flooding and dengue outbreak during the COVID-19 pandemic in Pakistan

Junaid Tahir M, Rizwan Siddiqi A, Ullah I, Ahmed A, Dujaili J, Saqlain M

Med J Islam Repub Iran, 2020;34:169.
PMID: 33816368 DOI: 10.47176/mjiri.34.169

Pakistan has recently been overwhelmed by extreme torrential rains, with its most populous city of Karachi experiencing its worst floods in almost a century. Poor flood control and water disposal facilities have led to an immense risk of another dengue outbreak, with multiple cases being reported recently. The enormous accumulation of stagnant water in urban areas is a major source of mosquito breeding and transmission. Historical data has shown the correlation between the number of dengue cases and average rainfall in the region. The monsoon rains have pounded at a time where health authorities are battling to contain the Coronavirus (COVID-19) pandemic. There is a need to implement centralized dengue control strategies to undertake large scale water drainage, sanitation, and disinfection drives in disaster-stricken areas alongside public health awareness programs to combat the after-effects of this natural calamity.

MeSH terms: Animals; Breeding; Cities; Dengue; Disasters; Disease Outbreaks; Disinfection; Drainage; Humans; Culicidae; Pakistan; Public Health; Rain; Sanitation; Water; Coronavirus; Floods; Pandemics
Fulltext Landmark-based homologous multi-point warping approach to 3D facial recognition using multiple datasets

Agbolade O, Nazri A, Yaakob R, Ghani AAA, Cheah YK

PeerJ Comput Sci, 2020;6:e249.
PMID: 33816901 DOI: 10.7717/peerj-cs.249

Over the years, neuroscientists and psychophysicists have been asking whether data acquisition for facial analysis should be performed holistically or with local feature analysis. This has led to various advanced methods of face recognition being proposed, and especially techniques using facial landmarks. The current facial landmark methods in 3D involve a mathematically complex and time-consuming workflow involving semi-landmark sliding tasks. This paper proposes a homologous multi-point warping for 3D facial landmarking, which is verified experimentally on each of the target objects in a given dataset using 500 landmarks (16 anatomical fixed points and 484 sliding semi-landmarks). This is achieved by building a template mesh as a reference object and applying this template to each of the targets in three datasets using an artificial deformation approach. The semi-landmarks are subjected to sliding along tangents to the curves or surfaces until the bending energy between a template and a target form is minimal. The results indicate that our method can be used to investigate shape variation for multiple datasets when implemented on three databases (Stirling, FRGC and Bosphorus).

MeSH terms: Facial Recognition; Face; Surgical Mesh; Databases, Factual; Workflow
Fulltext Development of a valid and reliable software customization model for SaaS quality through iterative method: perspectives from academia

Ali AQ, Md Sultan AB, Abd Ghani AA, Zulzalil H

PeerJ Comput Sci, 2020;6:e294.
PMID: 33816945 DOI: 10.7717/peerj-cs.294

Despite the benefits of standardization, the customization of Software as a Service (SaaS) application is also essential because of the many unique requirements of customers. This study, therefore, focuses on the development of a valid and reliable software customization model for SaaS quality that consists of (1) generic software customization types and a list of common practices for each customization type in the SaaS multi-tenant context, and (2) key quality attributes of SaaS applications associated with customization. The study was divided into three phases: the conceptualization of the model, analysis of its validity using SaaS academic-derived expertise, and evaluation of its reliability by submitting it to an internal consistency reliability test conducted by software-engineer researchers. The model was initially devised based on six customization approaches, 46 customization practices, and 13 quality attributes in the SaaS multi-tenant context. Subsequently, its content was validated over two rounds of testing after which one approach and 14 practices were removed and 20 practices were reformulated. The internal consistency reliability study was thereafter conducted by 34 software engineer researchers. All constructs of the content-validated model were found to be reliable in this study. The final version of the model consists of 6 constructs and 44 items. These six constructs and their associated items are as follows: (1) Configuration (eight items), (2) Composition (four items), (3) Extension (six items), 4) Integration (eight items), (5) Modification (five items), and (6) SaaS quality (13 items). The results of the study may contribute to enhancing the capability of empirically analyzing the impact of software customization on SaaS quality by benefiting from all resultant constructs and items.

MeSH terms: Concept Formation; Humans; Psychometrics; Reference Standards; Research Personnel; Software; Reproducibility of Results; Teaching Rounds
Fulltext Stochastic computing in convolutional neural network implementation: a review

Lee YY, Abdul Halim Z

PeerJ Comput Sci, 2020;6:e309.
PMID: 33816960 DOI: 10.7717/peerj-cs.309

Stochastic computing (SC) is an alternative computing domain for ubiquitous deterministic computing whereby a single logic gate can perform the arithmetic operation by exploiting the nature of probability math. SC was proposed in the 1960s when binary computing was expensive. However, presently, SC started to regain interest after the widespread of deep learning application, specifically the convolutional neural network (CNN) algorithm due to its practicality in hardware implementation. Although not all computing functions can translate to the SC domain, several useful function blocks related to the CNN algorithm had been proposed and tested by researchers. An evolution of CNN, namely, binarised neural network, had also gained attention in the edge computing due to its compactness and computing efficiency. This study reviews various SC CNN hardware implementation methodologies. Firstly, we review the fundamental concepts of SC and the circuit structure and then compare the advantages and disadvantages amongst different SC methods. Finally, we conclude the overview of SC in CNN and make suggestions for widespread implementation.

MeSH terms: Algorithms; Attention; Computing Methodologies; Probability
Fulltext Early survey with bibliometric analysis on machine learning approaches in controlling COVID-19 outbreaks

Chiroma H, Ezugwu AE, Jauro F, Al-Garadi MA, Abdullahi IN, Shuib L

PeerJ Comput Sci, 2020;6:e313.
PMID: 33816964 DOI: 10.7717/peerj-cs.313

Background and Objective: The COVID-19 pandemic has caused severe mortality across the globe, with the USA as the current epicenter of the COVID-19 epidemic even though the initial outbreak was in Wuhan, China. Many studies successfully applied machine learning to fight COVID-19 pandemic from a different perspective. To the best of the authors' knowledge, no comprehensive survey with bibliometric analysis has been conducted yet on the adoption of machine learning to fight COVID-19. Therefore, the main goal of this study is to bridge this gap by carrying out an in-depth survey with bibliometric analysis on the adoption of machine learning-based technologies to fight COVID-19 pandemic from a different perspective, including an extensive systematic literature review and bibliometric analysis.
Methods: We applied a literature survey methodology to retrieved data from academic databases and subsequently employed a bibliometric technique to analyze the accessed records. Besides, the concise summary, sources of COVID-19 datasets, taxonomy, synthesis and analysis are presented in this study. It was found that the Convolutional Neural Network (CNN) is mainly utilized in developing COVID-19 diagnosis and prognosis tools, mostly from chest X-ray and chest CT scan images. Similarly, in this study, we performed a bibliometric analysis of machine learning-based COVID-19 related publications in the Scopus and Web of Science citation indexes. Finally, we propose a new perspective for solving the challenges identified as direction for future research. We believe the survey with bibliometric analysis can help researchers easily detect areas that require further development and identify potential collaborators.
Results: The findings of the analysis presented in this article reveal that machine learning-based COVID-19 diagnose tools received the most considerable attention from researchers. Specifically, the analyses of results show that energy and resources are more dispenses towards COVID-19 automated diagnose tools while COVID-19 drugs and vaccine development remains grossly underexploited. Besides, the machine learning-based algorithm that is predominantly utilized by researchers in developing the diagnostic tool is CNN mainly from X-rays and CT scan images.
Conclusions: The challenges hindering practical work on the application of machine learning-based technologies to fight COVID-19 and new perspective to solve the identified problems are presented in this article. Furthermore, we believed that the presented survey with bibliometric analysis could make it easier for researchers to identify areas that need further development and possibly identify potential collaborators at author, country and institutional level, with the overall aim of furthering research in the focused area of machine learning application to disease control.
Fulltext Improving the performance of opportunistic routing using min-max range and optimum energy level for relay node selection in wireless sensor networks

Yee PL, Mehmood S, Almogren A, Ali I, Anisi MH

PeerJ Comput Sci, 2020;6:e326.
PMID: 33816976 DOI: 10.7717/peerj-cs.326

Opportunistic routing is an emerging routing technology that was proposed to overcome the drawback of unreliable transmission, especially in Wireless Sensor Networks (WSNs). Over the years, many forwarder methods were proposed to improve the performance in opportunistic routing. However, based on existing works, the findings have shown that there is still room for improvement in this domain, especially in the aspects of latency, network lifetime, and packet delivery ratio. In this work, a new relay node selection method was proposed. The proposed method used the minimum or maximum range and optimum energy level to select the best relay node to forward packets to improve the performance in opportunistic routing. OMNeT++ and MiXiM framework were used to simulate and evaluate the proposed method. The simulation settings were adopted based on the benchmark scheme. The evaluation results showed that our proposed method outperforms in the aspect of latency, network lifetime, and packet delivery ratio as compared to the benchmark scheme.

MeSH terms: Computer Communication Networks; Technology; Benchmarking; Wireless Technology
Fulltext Latent based temporal optimization approach for improving the performance of collaborative filtering

Al-Hadi IAA, Sharef NM, Sulaiman MN, Mustapha N, Nilashi M

PeerJ Comput Sci, 2020;6:e331.
PMID: 33816980 DOI: 10.7717/peerj-cs.331

Recommendation systems suggest peculiar products to customers based on their past ratings, preferences, and interests. These systems typically utilize collaborative filtering (CF) to analyze customers' ratings for products within the rating matrix. CF suffers from the sparsity problem because a large number of rating grades are not accurately determined. Various prediction approaches have been used to solve this problem by learning its latent and temporal factors. A few other challenges such as latent feedback learning, customers' drifting interests, overfitting, and the popularity decay of products over time have also been addressed. Existing works have typically deployed either short or long temporal representation for addressing the recommendation system issues. Although each effort improves on the accuracy of its respective benchmark, an integrative solution that could address all the problems without trading off its accuracy is needed. Thus, this paper presents a Latent-based Temporal Optimization (LTO) approach to improve the prediction accuracy of CF by learning the past attitudes of users and their interests over time. Experimental results show that the LTO approach efficiently improves the prediction accuracy of CF compared to the benchmark schemes.

MeSH terms: Algorithms; Attitude; Data Collection; Feedback; Learning; Social Behavior; Benchmarking
Fulltext State-of-the-art IoV trust management a meta-synthesis systematic literature review (SLR)

Rehman A, Hassan MF, Yew KH, Paputungan I, Tran DC

PeerJ Comput Sci, 2020;6:e334.
PMID: 33816982 DOI: 10.7717/peerj-cs.334

In the near future, the Internet of Vehicles (IoV) is foreseen to become an inviolable part of smart cities. The integration of vehicular ad hoc networks (VANETs) into the IoV is being driven by the advent of the Internet of Things (IoT) and high-speed communication. However, both the technological and non-technical elements of IoV need to be standardized prior to deployment on the road. This study focuses on trust management (TM) in the IoV/VANETs/ITS (intelligent transport system). Trust has always been important in vehicular networks to ensure safety. A variety of techniques for TM and evaluation have been proposed over the years, yet few comprehensive studies that lay the foundation for the development of a "standard" for TM in IoV have been reported. The motivation behind this study is to examine all the TM models available for vehicular networks to bring together all the techniques from previous studies in this review. The study was carried out using a systematic method in which 31 papers out of 256 research publications were screened. An in-depth analysis of all the TM models was conducted and the strengths and weaknesses of each are highlighted. Considering that solutions based on AI are necessary to meet the requirements of a smart city, our second objective is to analyze the implications of incorporating an AI method based on "context awareness" in a vehicular network. It is evident from mobile ad hoc networks (MANETs) that there is potential for context awareness in ad hoc networks. The findings are expected to contribute significantly to the future formulation of IoVITS standards. In addition, gray areas and open questions for new research dimensions are highlighted.

MeSH terms: Artificial Intelligence; Cities; Communication; Health Services; Motivation; Reference Standards; Internet; Trust
Fulltext Geographic distribution of Tick-borne encephalitis virus complex

Im JH, Baek JH, Durey A, Kwon HY, Chung MH, Lee JS

J Vector Borne Dis, 2020 1 1;57(1):14-22.
PMID: 33818450 DOI: 10.4103/0972-9062.308794

A comprehensive understanding of the geographic distribution of the tick-borne encephalitis virus (TBEV) complex is necessary due to increasing transboundary movement and cross-reactivity of serological tests. This review was conducted to identify the geographic distribution of the TBEV complex, including TBE virus, Alkhurma haemorrhagic fever virus, Kyasanur forest disease virus, louping-ill virus, Omsk haemorrhagic fever virus, and Powassan virus. Published reports were identified using PubMed, EMBASE, and the Cochrane library. In addition to TBEV complex case-related studies, seroprevalence studies were also retrieved to assess the risk of TBEV complex infection. Among 1406 search results, 314 articles met the inclusion criteria. The following countries, which are known to TBEV epidemic region, had conducted national surveillance studies: Austria, China, Czech, Denmark, Estonia, Finland, Germany, Hungary, Italy, Latvia, Norway, Poland, Romania, Russia, Switzerland, Sweden, Slovenia, and Slovakia. There were also studies/reports on human TBEV infection from Belarus, Bulgaria, Croatia, France, Japan, Kyrgyzstan, Netherland, and Turkey. Seroprevalence studies were found in some areas far from the TBEV belt, specifically Malaysia, Comoros, Djibouti, and Kenya. Kyasanur forest disease virus was reported in southwestern India and Yunnan of China, the Powassan virus in the United States, Canada, and east Siberia, Alkhurma haemorrhagic fever virus in Saudi Arabia and east Egypt, and Louping-ill virus in the United Kingdom, Ireland, and east Siberia. In some areas, the distribution of the TBEV complex overlaps with that of other viruses, and caution is recommended during serologic diagnosis. The geographic distribution of the TBEV complex appears to be wide and overlap of the TBE virus complex with other viruses was observed in some areas. Knowledge of the geographical distribution of the TBEV complex could help avoid cross-reactivity during the serologic diagnosis of these viruses. Surveillance studies can implement effective control measures according to the distribution pattern of these viruses.

MeSH terms: Animals; Cross Reactions; Encephalitis Viruses, Tick-Borne/classification; Encephalitis Viruses, Tick-Borne/immunology*; Encephalitis Viruses, Tick-Borne/isolation & purification; Encephalitis Viruses, Tick-Borne/pathogenicity; Encephalitis, Tick-Borne/immunology; Encephalitis, Tick-Borne/epidemiology*; Geography; Humans; Serologic Tests/standards; Seroepidemiologic Studies; Endemic Diseases/prevention & control*
Fulltext Effects on parameter estimates and goodness of fit measures: comparing item-level and item-parcel models in structural equation modeling

Ainur Amira Kamaruddin, Yap, Bee Wah, Sayang Mohd Deni

Pertanika Journal of Science & Technology, 2020;28(2):627-647.
MyJurnal

The assessment of model fit is important in Structural Equation Modeling (SEM). Several goodness-of-fit (GoF) measures are affected by sample size and the number of parameters to be estimated. A large sample size is needed to test a complex model involving a large number of parameters to be estimated. One of the solutions to reduce the number of parameters to be estimated in a given model is by considering item parceling. The effects of item parceling on parameter estimates and GoF measures in a structural equation model was investigated via a simulation study. The simulation results indicate that the parameter estimates are closer to the true parameter values for the IL model whenever the distribution of data is normal but biased when the data is highly skewed. The parameter estimates for the IP model were found to be underestimated for both normal and non-normal data. The GoF measures were higher for the IP model. Additionally, the RMSEA was lower for the IP model when data were skewed. This shows that item parceling may improve GoF measures but the effect of exogenous on endogenous variable is underestimated. Application to a real data set confirmed the results of the simulation study.
Fulltext Comparison of sparse and robust regression techniques in efficient model selection for moisture ratio removal of seaweed using solar drier

Javaid, Anam, Mohd. Tahir Ismail, Ali, Majid Khan Majahar

Pertanika Journal of Science & Technology, 2020;28(2):609-625.
MyJurnal

Solar drier is considered to be an important product used in the internet of things (IoT). It is used to dry different kinds of products used in agriculture or aquaculture. There are many factors that have different effects on the drying of items in the solar drier. The current study focused on the removal of the moisture ratio in the drying process for seaweed using solar drier. For this purpose, a dataset containing 1924 observations was used to study the effect of six different independent variables on the dependent variable. Moisture ratio removal (%) was considered to be dependent variable with ambient temperature, chamber temperature, collector temperature, chamber relative humidity, ambient relative humidity and solar radiation as independent variables. All possible models were used in the analysis till fifth order interaction terms. Hybrid model of LASSO with bisquare M was proposed for efficient selection of the model. The procedure based on four phases was used for efficient model selection and a comparison was made with other existing sparse and robust regression techniques. The result indicates that the proposed technique is better than other existing techniques in terms of mean squared error (MSE) and mean absolute percentage error (MAPE).
Fulltext Instantaneous speed ratio of traffic flowing through a merging area at kilometer 31.6 on the highway from Shah Alam to Kuala Lumpur

Nur Syahirah Husin Basri, Nurul Akmal Mohamed, Muhammad Akram Adnan, Nurul Farihan Mohamed, Nurul Hila Zainuddin

Pertanika Journal of Science & Technology, 2020;28(2):565-578.
MyJurnal

This study aims to evaluate a continuous flow model that involves a ramp area at kilometer 31.6 on the highway from Shah Alam to Kuala Lumpur, to analyze the findings of numerical results of instantaneous speed ratios and to observe the convergence patterns for each section. The continuous flow model assumes traffic flow to be similar to the heat equation in regard to the concept of the one-dimensional viscous flow of a compressible fluid. For the methodology, for solving an initial value-boundary value problem, an initial condition together with a set of boundary conditions are required to solve the partial differential equation. The boundary conditions are chosen to assess the suitableness of the design of the entrance ramp in Malaysia, which is for right hand drive traffic. Highway traffic data were collected on the tapered acceleration lane and obtained by the videotaping method. The Maple programming language was used to write a numerical code in order to evaluate the instantaneous speed ratio in terms of a Fourier series. Our results show that the realistic results of instantaneous speed ratios on the ramp at kilometer 31.6 from Shah Alam to Kuala Lumpur are acceptable when compared to the theoretical results. Therefore, a very minimal collision rate is expected due to the well-designed ramp at kilometer 31.6 from Shah Alam to Kuala Lumpur. It is beneficial to study the mathematical model and theories of traffic flows on the merging area to enhance the efficiency of the traffic flowing on highways.
Fulltext A case of Prader-Willi syndrome with behavioural disturbances: a successful multidisciplinary management approach

Nor Jannah Nasution Raduan, Mohd Razali Salleh, Norharlina Bahar, Mohd Faiz Md Tahir, Najwa Hanim Md Rosli3

Journal of Clinical and Health Sciences, 2020;5(1):83-86.
MyJurnal

Prader-Willi Syndrome (PWS) is a genetically determined neurodevelopmental disorder
occurring in 1 in 15,000 births. PWS is a rare case in Malaysia and a successful approach to its
management has not been well reported here. We present a case of a 13-year-old boy with
Prader-Willi Syndrome with prominent behavioural disturbances characterised by temper
tantrums, compulsive food intake, stubbornness, stealing and impulsivity further complicated by
underlying morbid obesity, poorly controlled type 2 diabetes mellitus, hypertension,
dyslipidaemia, obstructive sleep apnoea syndrome and intellectual disability. Multidisciplinary
approach involving child and adolescent psychiatrist, occupational therapist, counsellor, family
therapist, endocrinologist and dietician has shown to improve the patient’s weight, glucose and
blood pressure control and most importantly the behavioural disturbances
Fulltext Suspected hand, foot and mouth disease (HFMD) in an adult: an uncommon but important infectious disease

Khasnur Abd Malek, Ilham Ameera Ismail

Journal of Clinical and Health Sciences, 2020;5(1):79-82.
MyJurnal

Hand, foot and mouth disease (HFMD) is an uncommon infection to be diagnosed in adults.
We present a case of a 32-year-old immunocompetent man with HFMD. This case report
highlights the importance of identifying a common childhood disease that could occur in an
adult. Recognition is important for possible role in notification, especially for outbreak
prevention and to consider potential differential diagnoses. The management and disease
prevention measures in a working adult in Malaysia and the shortfalls identified in management
guidelines are discussed.

External Links