Displaying publications 101 - 120 of 240 in total

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  1. Fulltext Identifying Significant Metabolic Pathways Using Multi-Block Partial Least-Squares Analysis
    Deng L, Guo F, Cheng KK, Zhu J, Gu H, Raftery D, et al.
    J Proteome Res, 2020 05 01;19(5):1965-1974.
    PMID: 32174118 DOI: 10.1021/acs.jproteome.9b00793
    In metabolomics, identification of metabolic pathways altered by disease, genetics, or environmental perturbations is crucial to uncover the underlying biological mechanisms. A number of pathway analysis methods are currently available, which are generally based on equal-probability, topological-centrality, or model-separability methods. In brief, prior identification of significant metabolites is needed for the first two types of methods, while each pathway is modeled separately in the model-separability-based methods. In these methods, interactions between metabolic pathways are not taken into consideration. The current study aims to develop a novel metabolic pathway identification method based on multi-block partial least squares (MB-PLS) analysis by including all pathways into a global model to facilitate biological interpretation. The detected metabolites are first assigned to pathway blocks based on their roles in metabolism as defined by the KEGG pathway database. The metabolite intensity or concentration data matrix is then reconstructed as data blocks according to the metabolite subsets. Then, a MB-PLS model is built on these data blocks. A new metric, named the pathway importance in projection (PIP), is proposed for evaluation of the significance of each metabolic pathway for group separation. A simulated dataset was generated by imposing artificial perturbation on four pre-defined pathways of the healthy control group of a colorectal cancer study. Performance of the proposed method was evaluated and compared with seven other commonly used methods using both an actual metabolomics dataset and the simulated dataset. For the real metabolomics dataset, most of the significant pathways identified by the proposed method were found to be consistent with the published literature. For the simulated dataset, the significant pathways identified by the proposed method are highly consistent with the pre-defined pathways. The experimental results demonstrate that the proposed method is effective for identification of significant metabolic pathways, which may facilitate biological interpretation of metabolomics data.
    Matched MeSH terms: Probability
  2. Fulltext Introducing a technique in sustaining adult worker bees of Heterotrigona itama (Cockerell, 1918) in laboratory to facilitate future health research on Kelulut honey
    Syazana Jumaan, Jahangir Kamaldin, Rosliza Jajuli, Izfa Riza Hazmi
    Malaysian Journal of Medicine and Health Sciences, 2020;16(102):22-30.
    MyJurnal
    Introduction: The study is introducing a laboratory technique to sustain the longevity of Heterotrigona itama sting- less bees collected from the farm in order to facilitate future health research on Kelulut honey. Methods: The worker bees were held in laboratory at 26 ± 2 oC, 57 ± 8 % relative humidity (RH) and 12:12 hours (light:dark period) in a cup covered with meshed cloth and installed with an inverted-wick system consists of a drinking straw with the bottom end loosely plugged with cotton wool. The artificial diet was pipetted into the straw to wet the cotton wool. The bees were divided into five diet groups, namely a) unfed - control, b) distilled water, c) purified tap water, d) non-carbonated isotonic drink or e) 5% honey solution. Feeding activity and survival of worker bees were observed daily. Results: The worker bees are seen to frequent and lick the cotton wool wetted with artificial diets. Comparison between the artificial diets, Kaplan-Meier statistical analysis showed that the 5% honey solution and non-carbonated isotonic drink have significantly (P < 0.05) extended the longevity of the worker bees with 50% survival probability at least 8 days. When the similar holding and feeding technique used for the bees from commercial farms, the 50% survival probability was extended to 14 days. Conclusion: The inverted-wick system with the use of 5% honey solu- tion or isotonic drink as the artificial diet is capable to hold the H. itama worker bees at least for a week with survival above 50% for laboratory experiments.

    Matched MeSH terms: Probability
  3. Fulltext A rule-based energy management scheme for long-term optimal capacity planning of grid-independent microgrid optimized by multi-objective grasshopper optimization algorithm
    Bukar AL, Tan CW, Yiew LK, Ayop R, Tan WS
    Energy Convers Manag, 2020 Oct 01;221:113161.
    PMID: 32834297 DOI: 10.1016/j.enconman.2020.113161
    Off-grid electrification of remote communities using sustainable energy systems (SESs) is a requisite for realizing sustainable development goals. Nonetheless, the capacity planning of the SESs is challenging as it needs to fulfil the fluctuating demand from a long-term perspective, in addition to the intermittency and unpredictable nature of renewable energy sources (RESs). Owing to the nonlinear and non-convex nature of the capacity planning problem, an efficient technique must be employed to achieve a cost-effective system. Existing techniques are, subject to some constraints on the derivability and continuity of the objective function, prone to premature convergence, computationally demanding, follows rigorous procedures to fine-tune the algorithm parameters in different applications, and often do not offer a fair balance during the exploitation and exploration phase of the optimization process. Furthermore, the literature review indicates that researchers often do not implement and examine the energy management scheme (EMS) of a microgrid while computing for the capacity planning problem of microgrids. This paper proposes a rule-based EMS (REMS) optimized by a nature-inspired grasshopper optimization algorithm (GOA) for long-term capacity planning of a grid-independent microgrid incorporating a wind turbine, a photovoltaic, a battery (BT) bank and a diesel generator (

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    ). In which, a rule-based algorithm is used to implement an EMS to prioritize the usage of RES and coordinate the power flow of the proposed microgrid components. Subsequently, an attempt is made to explore and confirm the efficiency of the proposed REMS incorporated with GOA. The ultimate goal of the objective function is to minimize the cost of energy (COE) and the deficiency of power supply probability (DPSP). The performance of the REMS is examined via a long-term simulation study to ascertain the REMS resiliency and to ensure the operating limit of the BT storage is not violated. The result of the GOA is compared with particle swarm optimization (PSO) and a cuckoo search algorithm (CSA). The simulation results indicate that the proposed technique's superiority is confirmed in terms of convergence to the optimal solution. The simulation results confirm that the proposed REMS has contributed to better adoption of a cleaner energy production system, as the scheme significantly reduces fuel consumption,


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    emission and COE by 92.4%, 92.3% and 79.8%, respectively as compared to the conventional

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    . The comparative evaluation of the algorithms shows that REMS-GOA yields a better result as it offers the least COE (objective function), at $0.3656/kW h, as compared to the REMS-CSA at $0.3662/kW h and REMS-PSO at $0.3674/kW h, for the desired DPSP of 0%. Finally, sensitivity analysis is performed to highlight the effect of uncertainties on the system inputs that may arise in the future.
    Matched MeSH terms: Probability
  4. Randomized comparison of W.A.R.A. (Wiring Affect with ReAttach) versus distraction: A pilot study assessing the efficacy of an ultrafast transdiagnostic intervention
    Weerkamp-Bartholomeus P, Marazziti D, Chan E, Srivastava A, van Amelsvoort T
    Heliyon, 2020 Aug;6(8):e04660.
    PMID: 32802985 DOI: 10.1016/j.heliyon.2020.e04660
    Background: Generally, neuropsychiatric patients share different symptoms across nosological categories, such as, amongst other, psychological distress, mood alterations, anxiety, and self-regulation disturbances.ReAttach is a novel psychological intervention with its key elements being external affect and arousal regulation, stimulation of multiple sensory processing, conceptualization, affective mentalization, and associative memory processing. ReAttach has been hypothesized to be effective in reducing symptom severity in different psychiatric conditions. Given the limited information currently available, the present study aimed to investigate the effect of main ReAttach elements called "Wiring Affect with ReAttach" (W.A.R.A.) on negative affect (N.A.), and to compare it with "Distraction," another well-established affect-regulating strategy.

    Methods: We used a single-blind, randomized controlled crossover equivalence design to compare the efficacy on N.A. regulation of W.A.R.A. versus Distraction in 101 patients with different neuropsychiatric disorders.

    Results: The results showed a significant difference (p < 0.001) in response to W.A.R.A. vs. Distraction, with W.A.R.A. being significantly more effective in regulating N.A., with a large effect size (dRMpooled = 2.38) and a high probability (95%) of success.

    Limitations: The heterogeneity of the study population makes generalization and clear recommendations for specific patient groups difficult. The Numeric Rating Scale might have prevented detection of increased N.A. when the baseline scores were high. More in-depth research is needed to explore the W.A.R.A. technique and the extent of confounding variables such as the placebo effect.

    Conclusions: The findings suggest that W.A.R.A. may be an effective, accessible, and brief intervention reducing negative affect. Although premature, these first results are encouraging.

    Matched MeSH terms: Probability
  5. The utility of the Laplace effect size prior distribution in Bayesian fine-mapping studies
    Walters K, Cox A, Yaacob H
    Genet Epidemiol, 2021 Jun;45(4):386-401.
    PMID: 33410201 DOI: 10.1002/gepi.22375
    The Gaussian distribution is usually the default causal single-nucleotide polymorphism (SNP) effect size prior in Bayesian population-based fine-mapping association studies, but a recent study showed that the heavier-tailed Laplace prior distribution provided a better fit to breast cancer top hits identified in genome-wide association studies. We investigate the utility of the Laplace prior as an effect size prior in univariate fine-mapping studies. We consider ranking SNPs using Bayes factors and other summaries of the effect size posterior distribution, the effect of prior choice on credible set size based on the posterior probability of causality, and on the noteworthiness of SNPs in univariate analyses. Across a wide range of fine-mapping scenarios the Laplace prior generally leads to larger 90% credible sets than the Gaussian prior. These larger credible sets for the Laplace prior are due to relatively high prior mass around zero which can yield many noncausal SNPs with relatively large Bayes factors. If using conventional credible sets, the Gaussian prior generally yields a better trade off between including the causal SNP with high probability and keeping the set size reasonable. Interestingly when using the less well utilised measure of noteworthiness, the Laplace prior performs well, leading to causal SNPs being declared noteworthy with high probability, whilst generally declaring fewer than 5% of noncausal SNPs as being noteworthy. In contrast, the Gaussian prior leads to the causal SNP being declared noteworthy with very low probability.
    Matched MeSH terms: Probability
  6. Fulltext Directionally-Enhanced Binary Multi-Objective Particle Swarm Optimisation for Load Balancing in Software Defined Networks
    Albowarab MH, Zakaria NA, Zainal Abidin Z
    Sensors (Basel), 2021 May 12;21(10).
    PMID: 34065920 DOI: 10.3390/s21103356
    Various aspects of task execution load balancing of Internet of Things (IoTs) networks can be optimised using intelligent algorithms provided by software-defined networking (SDN). These load balancing aspects include makespan, energy consumption, and execution cost. While past studies have evaluated load balancing from one or two aspects, none has explored the possibility of simultaneously optimising all aspects, namely, reliability, energy, cost, and execution time. For the purposes of load balancing, implementing multi-objective optimisation (MOO) based on meta-heuristic searching algorithms requires assurances that the solution space will be thoroughly explored. Optimising load balancing provides not only decision makers with optimised solutions but a rich set of candidate solutions to choose from. Therefore, the purposes of this study were (1) to propose a joint mathematical formulation to solve load balancing challenges in cloud computing and (2) to propose two multi-objective particle swarm optimisation (MP) models; distance angle multi-objective particle swarm optimization (DAMP) and angle multi-objective particle swarm optimization (AMP). Unlike existing models that only use crowding distance as a criterion for solution selection, our MP models probabilistically combine both crowding distance and crowding angle. More specifically, we only selected solutions that had more than a 0.5 probability of higher crowding distance and higher angular distribution. In addition, binary variants of the approaches were generated based on transfer function, and they were denoted by binary DAMP (BDAMP) and binary AMP (BAMP). After using MOO mathematical functions to compare our models, BDAMP and BAMP, with state of the standard models, BMP, BDMP and BPSO, they were tested using the proposed load balancing model. Both tests proved that our DAMP and AMP models were far superior to the state of the art standard models, MP, crowding distance multi-objective particle swarm optimisation (DMP), and PSO. Therefore, this study enables the incorporation of meta-heuristic in the management layer of cloud networks.
    Matched MeSH terms: Probability
  7. Discriminatory ability of cervical vertebral maturation stages in predicting attainment of the legal age threshold of 14 years: A pilot study using lateral cephalograms
    Banda TR, Komuravelli AK, Balla SB, Korrai BR, Alluri K, Kondapaneni J, et al.
    Imaging Sci Dent, 2020 Sep;50(3):209-216.
    PMID: 33005578 DOI: 10.5624/isd.2020.50.3.209
    Purpose: In India, the age of 14 years is the legal age threshold for child labour. Therefore, in suspected instances of child labour, age assessment plays a crucial role in determining whether a violation of the law on the employment of children has occurred. The aim of this retrospective cross-sectional study was to assess the discriminatory ability of stages of cervical vertebral maturation (CVM) in predicting the legal age threshold of 14 years.

    Materials and Methods: Routinely taken lateral cephalograms from 408 subjects aged 10 to 18 years were evaluated retrospectively using the CVM stages described by Baccetti et al. Descriptive statistics, accuracy, sensitivity, specificity, positive and negative predictive values, and likelihood ratios were calculated for stages 2, 3, and 4 of CVM.

    Results: Real age increased as the CVM stage gradually increased. The results of 2×2 contingency tables showed that CVM stage 4 produced an accuracy of 71% and 73%, a false positive rate of 7% and 18%, and a post-test probability of 59% and 68% for boys and girls, respectively.

    Conclusion: Based on these findings, it can be concluded that the stages of CVM are of limited use for predicting the attainment of the legal age threshold of 14 years. Future studies should investigate whether combinations of skeletal and dental methods could achieve better accuracy and post-test probability.

    Matched MeSH terms: Probability
  8. Fulltext Detection of Vibrio cholerae in raw cockles (Anadara granosa) by polymerase chain reaction
    International Food Research Journal, 2010;17(3):675-680.
    MyJurnal
    Aimed of this study was to determine the presence of Vibrio cholerae in cockles (Anadara granosa)
    from different coasts in Malaysia and to measure the biosafety of V. cholerae in raw cockles at wet market in Malaysia using the polymerase chain reaction (PCR) in combination with the most probable number (MPN) method. A total of 100 samples from 4 different wet markets in the West and East were examined for the presence of V. cholerae. The prevalence of V. cholerae between the two coasts was not significant different. In fact, the 74% of samples from West coast area was found positive while the 69% for samples collected in the East coast. West coast samples showed a prevalence of 60% for the wet market A=, 64% for B=, 88% for C= and 84% for the market D); East coast samples showed the same percentage with 72% for the wet markets E, F and H, followed by wet market G with 60%.With the MPN-PCR method, using 80 samples of raw cockles obtained from 4 wet markets, the occurrence of V. cholerae detected was of 95%. The frequency of V. cholerae in raw cockles obtained from wet market I and L was higher (100%) compared to other wet market (Wet market B=, 90%; Wet market C=, 95%).The density of V. cholerae detected in all samples ranged from 24000 MPN/g, but most of the samples (24 samples) were in category >24000 MPN/g concentration. V. cholerae was present in raw cockles in higher number. Hence, these results demonstrate the presence of pathogenic V.cholerae in cockles harvested and reveal the potential risk of illness associated with their consumption. This study will be the first biosafety assessment of V. choleare in raw cockles in Malaysia and it will provide significant insights about Malaysian scenario.
    Matched MeSH terms: Probability
  9. Fulltext Health related quality of life using commercially prepared food supplements, multivitamins and minerals - a meta-analysis
    R.(III) P. Dioso
    ASM Science Journal, 2014;8(1):55-66.
    MyJurnal
    Through the six domains of the health-related quality of life (HRQOL) - physical, psychological, level of independence, social relationship, environment and spirituality or religion - ten out of one hundred randomly selected studies were analysed and evaluated as a theoretical outcome of self care using health products such as food supplements, multivitamins and minerals. A reconstructed HRQOL tool was used in the qualitative and the quantitative analysis and evaluation of the ten selected studies. A Critical Appraisal Skills Programme tool was also used in making sense of the evidences of the study trials. The Population, Intervention, Comparison and Outcome guide focused the protocol for the selection of the studies used in this meta-analysis. A probability sampling generated a uniform distribution of the populations. The manner of consuming or the route of administration, the volume and the preparation of commercially prepared health products were neither analysed nor evaluated as the exclusion criteria. Of the ten studies, nine gave a high significance to the six domains of the (O.R. = 90% / p =
    Matched MeSH terms: Probability
  10. Fulltext Bayesian network classification of gastrointestinal bleeding
    Nazziwa Aisha, Mohd Bakri Adam, Shamarina Shohaimi, Aida Mustapha
    Pertanika Journal of Science & Technology, 2014;22(2):567-575.
    MyJurnal
    The source of gastrointestinal bleeding (GIB) remains uncertain in patients presenting without hematemesis. This paper aims at studying the accuracy, specificity and sensitivity of the Naive Bayesian Classifier (NBC) in identifying the source of GIB in the absence of hematemesis. Data of 325 patients admitted via the emergency department (ED) for GIB without hematemesis and who underwent confirmatory testing were analysed. Six attributes related to demography and their presenting signs were chosen. NBC was used to calculate the conditional probability of an individual being assigned to Upper Gastrointestinal bleeding (UGIB) or Lower Gastrointestinal bleeding (LGIB). High classification accuracy (87.3 %), specificity (0.85) and sensitivity (0.88) were achieved. NBC is a useful tool to support the identification of the source of gastrointestinal bleeding in patients without hematemesis.
    Matched MeSH terms: Probability
  11. Automated detection of atrial fibrillation using long short-term memory network with RR interval signals
    Faust O, Shenfield A, Kareem M, San TR, Fujita H, Acharya UR
    Comput Biol Med, 2018 11 01;102:327-335.
    PMID: 30031535 DOI: 10.1016/j.compbiomed.2018.07.001
    Atrial Fibrillation (AF), either permanent or intermittent (paroxysnal AF), increases the risk of cardioembolic stroke. Accurate diagnosis of AF is obligatory for initiation of effective treatment to prevent stroke. Long term cardiac monitoring improves the likelihood of diagnosing paroxysmal AF. We used a deep learning system to detect AF beats in Heart Rate (HR) signals. The data was partitioned with a sliding window of 100 beats. The resulting signal blocks were directly fed into a deep Recurrent Neural Network (RNN) with Long Short-Term Memory (LSTM). The system was validated and tested with data from the MIT-BIH Atrial Fibrillation Database. It achieved 98.51% accuracy with 10-fold cross-validation (20 subjects) and 99.77% with blindfold validation (3 subjects). The proposed system structure is straight forward, because there is no need for information reduction through feature extraction. All the complexity resides in the deep learning system, which gets the entire information from a signal block. This setup leads to the robust performance for unknown data, as measured with the blind fold validation. The proposed Computer-Aided Diagnosis (CAD) system can be used for long-term monitoring of the human heart. To the best of our knowledge, the proposed system is the first to incorporate deep learning for AF beat detection.
    Matched MeSH terms: Probability
  12. Fulltext Stream flow projection for Muar river in Malaysia using précis – HEC-HMS model
    Malek, M. A., Heyrani, M., Juneng, Liew
    ASM Science Journal, 2015;9(1):8-19.
    MyJurnal
    In this study, the implementation of the Regional Climate Model into the hydrodynamic model has been applied for streamflow projection on a river located at the south of Peninsular Malaysia within the years 2070 till 2099. The data has been obtained from a Regional Climate Model (RCM), named Précis, on a daily basis. It begins by comparing historical rainfall data generated from Précis versus the actual gauged recorded rainfall data from Department of Irrigation and Drainage Malaysia (DID). The bias of the generated rainfall data has been reduced by statistical techniques. The same has been applied to the future generated rainfall data from 2070 to 2099. Using the generated precipitation data as input to the hydrological model, results in the daily output of river discharge identified as the main contributor of flood occurrences. Based on the results of the hydrological model utilised, e.g. HEC-HMS, comparison was made between the future and historical generated discharge data using Précis between the years 1960 till 1998. Dividing a year into three segments, e.g. January-April, May-August, SeptemberDecember, the results show that there would be a significant drop of peak discharge in the third segment and an increase in discharge during the second segment. The first part remains almost with no changes. As an addition, the drop of the peak shows reduction in the probability of flood occurrences. It also indicates the reduction in water storage capacity which coherently affects the water supply scheme
    Matched MeSH terms: Probability
  13. Use of a Diagnostic Score to Prioritize Computed Tomographic (CT) Imaging for Patients Suspected of Ischemic Stroke Who May Benefit from Thrombolytic Therapy
    Hwong WY, Bots ML, Selvarajah S, Kappelle LJ, Abdul Aziz Z, Sidek NN, et al.
    PLoS One, 2016;11(10):e0165330.
    PMID: 27768752 DOI: 10.1371/journal.pone.0165330
    A shortage of computed tomographic (CT) machines in low and middle income countries often results in delayed CT imaging for patients suspected of a stroke. Yet, time constraint is one of the most important aspects for patients with an ischemic stroke to benefit from thrombolytic therapy. We set out to assess whether application of the Siriraj Stroke Score is able to assist physicians in prioritizing patients with a high probability of having an ischemic stroke for urgent CT imaging.
    Matched MeSH terms: Probability
  14. Fulltext Critical Data-Based Incremental Cooperative Communication for Wireless Body Area Network
    Al-Mishmish H, Akhayyat A, Rahim HA, Hammood DA, Ahmad RB, Abbasi QH
    Sensors (Basel), 2018 Oct 28;18(11).
    PMID: 30373314 DOI: 10.3390/s18113661
    Wireless Body Area Networks (WBANs) are single-hop network systems, where sensors gather the body's vital signs and send them directly to master nodes (MNs). The sensors are distributed in or on the body. Therefore, body posture, clothing, muscle movement, body temperature, and climatic conditions generally influence the quality of the wireless link between sensors and the destination. Hence, in some cases, single hop transmission ('direct transmission') is not sufficient to deliver the signals to the destination. Therefore, we propose an emergency-based cooperative communication protocol for WBAN, named Critical Data-based Incremental Cooperative Communication (CD-ICC), based on the IEEE 802.15.6 CSMA standard but assuming a lognormal shadowing channel model. In this paper, a complete study of a system model is inspected in the terms of the channel path loss, the successful transmission probability, and the outage probability. Then a mathematical model is derived for the proposed protocol, end-to-end delay, duty cycle, and average power consumption. A new back-off time is proposed within CD-ICC, which ensures the best relays cooperate in a distributed manner. The design objective of the CD-ICC is to reduce the end-to-end delay, the duty cycle, and the average power transmission. The simulation and numerical results presented here show that, under general conditions, CD-ICC can enhance network performance compared to direct transmission mode (DTM) IEEE 802.15.6 CSMA and benchmarking. To this end, we have shown that the power saving when using CD-ICC is 37.5% with respect to DTM IEEE 802.15.6 CSMA and 10% with respect to MI-ICC.
    Matched MeSH terms: Probability
  15. Fulltext Culinary arts entrepreneurship: alternative student Diploma in Culinary Arts at Kolej Yayasan Pelajaran Johor in facing open market
    Abdul Wafi Abdul Rahman, Yusmady Md Junus, Melor Md Yunus
    Malaysian Journal of Social Sciences and Humanities, 2017;2(3):27-34.
    MyJurnal
    The Open Market scenario provides high levels of unreliability to culinary arts graduates where they
    are no longer promised a place in the hospitality and tourism sectors but rather to compete with
    graduates from other fields for employment. Hence, the field of entrepreneurship is seen as an
    alternative in building a career that can help in reducing the dumping of graduates in the job market in
    line with the government's call encouraging more entrepreneurs in Malaysia. Therefore, this study is
    aimed at identifying the tendency to entrepreneurship among students of the final year semester of the Diploma in Culinary Arts, Hospitality School and Tourism Kolej Yayasan Pelajaran Johor
    (SHPKYPJ). Measurements for this study were based on surveys using questionnaire and data
    collected by Statistical Packages for Social Science (SPSS) Version 21.0. The results of the study
    found that overall respondents have a high inclination towards entrepreneurship. If they are more
    focused, encouragement and exposure are given to them, the probability that they become
    entrepreneurs after graduation will be higher.
    Matched MeSH terms: Probability
  16. Modeling flood susceptibility using data-driven approaches of naïve Bayes tree, alternating decision tree, and random forest methods
    Chen W, Li Y, Xue W, Shahabi H, Li S, Hong H, et al.
    Sci Total Environ, 2020 Jan 20;701:134979.
    PMID: 31733400 DOI: 10.1016/j.scitotenv.2019.134979
    Floods are one of the most devastating types of disasters that cause loss of lives and property worldwide each year. This study aimed to evaluate and compare the prediction capability of the naïve Bayes tree (NBTree), alternating decision tree (ADTree), and random forest (RF) methods for the spatial prediction of flood occurrence in the Quannan area, China. A flood inventory map with 363 flood locations was produced and partitioned into training and validation datasets through random selection with a ratio of 70/30. The spatial flood database was constructed using thirteen flood explanatory factors. The probability certainty factor (PCF) method was used to analyze the correlation between the factors and flood occurrences. Consequently, three flood susceptibility maps were produced using the NBTree, ADTree, and RF methods. Finally, the area under the curve (AUC) and statistical measures were used to validate the flood susceptibility models. The results indicated that the RF method is an efficient and reliable model in flood susceptibility assessment, with the highest AUC values, positive predictive rate, negative predictive rate, sensitivity, specificity, and accuracy for the training (0.951, 0.892, 0.941, 0.945, 0.886, and 0.915, respectively) and validation (0.925, 0.851, 0.938, 0.945, 0.835, and 0.890, respectively) datasets.
    Matched MeSH terms: Probability
  17. Maternal education and tetanus immunisation in Indonesia
    Mohamed WN
    Sains Malaysiana, 1996;25(4):19-29.
    This paper examines the influence of maternal education on the acceptance of tetanus toxoid vaccine, using data from two villages in rural Yogyakarta, Indonesia. Maternal education results in increased tetanus toxoid uptake. Irrespective of the level of formal education, correct knowledge of the function of tetanus toxoid is positively associated with the probability of using the vaccine. It is therefore recommended that health education campaign be run to provide correct information on the importance of tetanus toxoid. This study can be used as a model for health programmes in other population with low levels of women education.
    Key words: Neonatal tetanus, maternal education, tetanus toxoid, binomial logistic regression, multinomial logistic regression.
    Kertas ini mengkaji pengaruh pendidikan ibu ke atas penerimaan vaksin tetanus toxoid, dengan menggunakan data daripada dua buah kampung di pendalaman Yogyakarta, Indonesia. Kajian ini mendapati pendidikan ibu dapat meningkatkan kadar pengambilan tetanus toxiod. Pengetahuan yang tepat tentang kepentingan vaksin tersebut didapati mempunyai hubungan yang positif dengan pengambilannya, tanpa mengira tahap pendidikan wanita. Dengan itu dicadangkan agar kempen pendidikan kesihatan dijalankan untuk menyebarkan maklumat yang jelas ten tang kepentingan tetanus toxoid. Kajian ini boleh dijadikan model bagi program kesihatan untuk populasi lain yang mempunyai tahap pendidikan wanita yang rendah.
    Kata kunci: Tetanus neonatal, pendidikan ibu, tetanus toxoid, regresi logistik binomial, regresi logistik multinomial.
    Matched MeSH terms: Probability
  18. Performance comparison between bootstrap and multiscale bootstrap for assessing phylogenetic tree for RNA polymerase
    Safinah Sharuddin, Nora Muda
    Sains Malaysiana, 2015;44:1643-1651.
    Phylogenetic inference refers to the reconstruction of evolutionary relationships among various species that is usually
    presented in the form of a tree. This study constructs the phylogenetic tree by using a novel distance-based method known
    as Modified one step M-estimator (MOM) method. The branches of the phylogenetic tree constructed were then evaluated
    to see their reliability. The performance of the reliability was then compared between the p-value of multiscale bootstrap
    (AU value) and bootstrap p-value (BP value). The aim of this study was to compare the performance between the AU value
    and BP value for assessing phylogenetic tree of RNA polymerase. The results have shown that multiscale bootstrap analysis
    can detect high sampling errors but not in bootstrap analysis. To overcome this problem, the multiscale bootstrap analysis
    has reduced the sampling error by increasing the number of replications. The clusters were indicated as significant if AU
    values or BP values were 95% or higher. From the analysis, the results showed that the BP and AU values differ at 11th
    and 15th branch of the phylogenetic tree. The BP values at both branches were 72 and 85%, respectively, thereby making
    the cluster not significant but by looking at the AU values, the two branches were more than 95% and the clusters were
    significant. This was due to the biasness in calculation of the probability of bootstrap analysis, therefore, the multiscale
    bootstrap analysis has improved the calculation of the probability value compared to the bootstrap analysis.
    Matched MeSH terms: Probability
  19. Projected changes of future climate extremes in Malaysia
    Meng Sei Kwan, Fredolin T. Tangang, Liew Juneng
    Sains Malaysiana, 2013;42:1051-1059.
    Mitigating and adapting to the impacts of climate change at regional level require downscaled projection of future climate states. This paper examined the possible changes of future climate extremes over Malaysia based on the IPCC SRES A1B emission scenario. The projected changes at 17 stations were produced by bias correcting the UKMO PRECIS downscaling simulation output. The simulation expected higher probability of rainfall extreme occurrences over the west coast of Peninsular Malaysia during the autumn transitional monsoon period. In addition, possible early monsoon rainfall was projected for certain stations located over East Malaysia. The simulation also projected larger increase of warm temperature extremes but smaller decrease of cold extremes, suggesting asymmetric expansion of the temperature distribution. The impact of the elevated green house gases (GHG) is higher in the night time temperature extremes as compared to the day time temperature extremes. The larger increment of warm night frequencies as compared to the warm day suggests smaller diurnal temperature ranges under the influence of higher greenhouse gases. Stations located in East Malaysia were projected to experience the largest increase of warm night occurrence.
    Matched MeSH terms: Probability
  20. Coral reef and associated habitat mapping using ALOS satellite imagery
    Mustapha M, Lihan T, Khalid L
    Sains Malaysiana, 2014;43:1363-1371.
    Coral reefs are rich in biodiversity and ecosystem services. However increase in degradation are still occurring at an alarming rate. In management of this ecosystem, determination of its spatial distribution is of importance. Satellite imageries can be used to map distribution extent using spectral characteristics which is a fundamental parameter in mapping. The aims of this study were to determine the spectral characteristics of corals and associated habitats and to map its spatial distribution using 2009 ALOS advanced visible and near infrared radiometer type 2 (AVNIR-2) satellite imagery. Results indicated that coral and habitats surrounding the area display variation in the spectral characteristics magnitude but displays similar spectral curve. Spectral characteristics from the corals and surrounding habitats were determined by presence of benthic microalgae and calcium carbonate. Maximum likelihood classification on the image produced five main classes. Spatial distribution of coral and associated habitats indicated five main zones which are sandy shore zone, sandy intertidal zone, seagrass zone, coral/submerged sandy zone and rocky zone. Distribution of live corals indicated coverage of 0.54 km2, sea grass (0.94 km2), sandy bottom (1.31 km2) and rocky shores (0.19 km2). The results of this study indicated that ALOS satellite data was able to determine variation in spectral characteristics of coral reefs and other habitats thus is capable of mapping the ecosystems spatial distribution.
    Matched MeSH terms: Probability
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