Displaying publications 1 - 20 of 37 in total

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  1. Fulltext A Markov Chain Monte Carlo Approach to Estimate AIDS after HIV Infection
    Apenteng OO, Ismail NA
    PLoS One, 2015;10(7):e0131950.
    PMID: 26147199 DOI: 10.1371/journal.pone.0131950
    The spread of human immunodeficiency virus (HIV) infection and the resulting acquired immune deficiency syndrome (AIDS) is a major health concern in many parts of the world, and mathematical models are commonly applied to understand the spread of the HIV epidemic. To understand the spread of HIV and AIDS cases and their parameters in a given population, it is necessary to develop a theoretical framework that takes into account realistic factors. The current study used this framework to assess the interaction between individuals who developed AIDS after HIV infection and individuals who did not develop AIDS after HIV infection (pre-AIDS). We first investigated how probabilistic parameters affect the model in terms of the HIV and AIDS population over a period of time. We observed that there is a critical threshold parameter, R0, which determines the behavior of the model. If R0 ≤ 1, there is a unique disease-free equilibrium; if R0 < 1, the disease dies out; and if R0 > 1, the disease-free equilibrium is unstable. We also show how a Markov chain Monte Carlo (MCMC) approach could be used as a supplement to forecast the numbers of reported HIV and AIDS cases. An approach using a Monte Carlo analysis is illustrated to understand the impact of model-based predictions in light of uncertain parameters on the spread of HIV. Finally, to examine this framework and demonstrate how it works, a case study was performed of reported HIV and AIDS cases from an annual data set in Malaysia, and then we compared how these approaches complement each other. We conclude that HIV disease in Malaysia shows epidemic behavior, especially in the context of understanding and predicting emerging cases of HIV and AIDS.
    Matched MeSH terms: Markov Chains*
  2. A New Framework for Analysis of Coevolutionary Systems-Directed Graph Representation and Random Walks
    Chong SY, Tiňo P, He J, Yao X
    Evol Comput, 2019;27(2):195-228.
    PMID: 29155606 DOI: 10.1162/evco_a_00218
    Studying coevolutionary systems in the context of simplified models (i.e., games with pairwise interactions between coevolving solutions modeled as self plays) remains an open challenge since the rich underlying structures associated with pairwise-comparison-based fitness measures are often not taken fully into account. Although cyclic dynamics have been demonstrated in several contexts (such as intransitivity in coevolutionary problems), there is no complete characterization of cycle structures and their effects on coevolutionary search. We develop a new framework to address this issue. At the core of our approach is the directed graph (digraph) representation of coevolutionary problems that fully captures structures in the relations between candidate solutions. Coevolutionary processes are modeled as a specific type of Markov chains-random walks on digraphs. Using this framework, we show that coevolutionary problems admit a qualitative characterization: a coevolutionary problem is either solvable (there is a subset of solutions that dominates the remaining candidate solutions) or not. This has an implication on coevolutionary search. We further develop our framework that provides the means to construct quantitative tools for analysis of coevolutionary processes and demonstrate their applications through case studies. We show that coevolution of solvable problems corresponds to an absorbing Markov chain for which we can compute the expected hitting time of the absorbing class. Otherwise, coevolution will cycle indefinitely and the quantity of interest will be the limiting invariant distribution of the Markov chain. We also provide an index for characterizing complexity in coevolutionary problems and show how they can be generated in a controlled manner.
    Matched MeSH terms: Markov Chains
  3. Fulltext A discrete event simulation model for evaluating the performances of an m/g/c/c state dependent queuing system
    Khalid R, Nawawi MK, Kawsar LA, Ghani NA, Kamil AA, Mustafa A
    PLoS One, 2013;8(4):e58402.
    PMID: 23560037 DOI: 10.1371/journal.pone.0058402
    M/G/C/C state dependent queuing networks consider service rates as a function of the number of residing entities (e.g., pedestrians, vehicles, and products). However, modeling such dynamic rates is not supported in modern Discrete Simulation System (DES) software. We designed an approach to cater this limitation and used it to construct the M/G/C/C state-dependent queuing model in Arena software. Using the model, we have evaluated and analyzed the impacts of various arrival rates to the throughput, the blocking probability, the expected service time and the expected number of entities in a complex network topology. Results indicated that there is a range of arrival rates for each network where the simulation results fluctuate drastically across replications and this causes the simulation results and analytical results exhibit discrepancies. Detail results that show how tally the simulation results and the analytical results in both abstract and graphical forms and some scientific justifications for these have been documented and discussed.
    Matched MeSH terms: Markov Chains
  4. Fulltext A new hybrid fuzzy time series model with an application to predict PM10 concentration
    Alyousifi Y, Othman M, Husin A, Rathnayake U
    Ecotoxicol Environ Saf, 2021 Dec 20;227:112875.
    PMID: 34717219 DOI: 10.1016/j.ecoenv.2021.112875
    Fuzzy time series (FTS) forecasting models show a great performance in predicting time series, such as air pollution time series. However, they have caused major issues by utilizing random partitioning of the universe of discourse and ignoring repeated fuzzy sets. In this study, a novel hybrid forecasting model by integrating fuzzy time series to Markov chain and C-Means clustering techniques with an optimal number of clusters is presented. This hybridization contributes to generating effective lengths of intervals and thus, improving the model accuracy. The proposed model was verified and validated with real time series data sets, which are the benchmark data of actual trading of Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) and PM10 concentration data from Melaka, Malaysia. In addition, a comparison was made with some existing fuzzy time series models. Furthermore, the mean absolute percentage error, mean squared error and Theil's U statistic were calculated as evaluation criteria to illustrate the performance of the proposed model. The empirical analysis shows that the proposed model handles the time series data sets more efficiently and provides better overall forecasting results than existing FTS models. The results prove that the proposed model has greatly improved the prediction accuracy, for which it outperforms several fuzzy time series models. Therefore, it can be concluded that the proposed model is a better option for forecasting air pollution parameters and any kind of random parameters.
    Matched MeSH terms: Markov Chains
  5. A study on the S2 -EWMA chart for monitoring the process variance based on the MRL Performance
    Teh Sin Yin, Ong Ker Hsin, Soh Keng Lin, Khoo Michael Boon Chong, Teoh Wei Li
    Sains Malaysiana, 2015;44:1067-1075.
    The existing optimal design of the fixed sampling interval S2-EWMA control chart to monitor the sample variance of a process is based on the average run length (ARL) criterion. Since the shape of the run length distribution changes with the magnitude of the shift in the variance, the median run length (MRL) gives a more meaningful explanation about the in-control and out-of-control performances of a control chart. This paper proposes the optimal design of the S2-EWMA chart, based on the MRL. The Markov chain technique is employed to compute the MRLs. The performances of the S2-EWMA chart, double sampling (DS) S2 chart and S chart are evaluated and compared. The MRL results indicated that the S2-EWMA chart gives better performance for detecting small and moderate variance shifts, while maintaining almost the same sensitivity as the DS S2 and S charts toward large variance shifts, especially when the sample size increases.
    Matched MeSH terms: Markov Chains
  6. Fulltext An Energy-Efficient Spectrum-Aware Reinforcement Learning-Based Clustering Algorithm for Cognitive Radio Sensor Networks
    Mustapha I, Mohd Ali B, Rasid MF, Sali A, Mohamad H
    Sensors (Basel), 2015;15(8):19783-818.
    PMID: 26287191 DOI: 10.3390/s150819783
    It is well-known that clustering partitions network into logical groups of nodes in order to achieve energy efficiency and to enhance dynamic channel access in cognitive radio through cooperative sensing. While the topic of energy efficiency has been well investigated in conventional wireless sensor networks, the latter has not been extensively explored. In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. Each member node selects an optimal cluster that satisfies pairwise constraints, minimizes network energy consumption and enhances channel sensing performance through an exploration technique. We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. Performance comparisons of our algorithm with the Groupwise Spectrum Aware (GWSA)-based algorithm in terms of Sum of Square Error (SSE), complexity, network energy consumption and probability of detection indicate improved performance from the proposed approach. The results further reveal that an energy savings of 9% and a significant Primary User (PU) detection improvement can be achieved with the proposed approach.
    Matched MeSH terms: Markov Chains
  7. An expectation-maximization algorithm based Kalman smoother approach for single-trial estimation of event-related potentials
    Ting CM, Samdin SB, Salleh ShH, Omar MH, Kamarulafizam I
    Annu Int Conf IEEE Eng Med Biol Soc, 2012;2012:6534-8.
    PMID: 23367426 DOI: 10.1109/EMBC.2012.6347491
    This paper applies an expectation-maximization (EM) based Kalman smoother (KS) approach for single-trial event-related potential (ERP) estimation. Existing studies assume a Markov diffusion process for the dynamics of ERP parameters which is recursively estimated by optimal filtering approaches such as Kalman filter (KF). However, these studies only consider estimation of ERP state parameters while the model parameters are pre-specified using manual tuning, which is time-consuming for practical usage besides giving suboptimal estimates. We extend the KF approach by adding EM based maximum likelihood estimation of the model parameters to obtain more accurate ERP estimates automatically. We also introduce different model variants by allowing flexibility in the covariance structure of model noises. Optimal model selection is performed based on Akaike Information Criterion (AIC). The method is applied to estimation of chirp-evoked auditory brainstem responses (ABRs) for detection of wave V critical for assessment of hearing loss. Results shows that use of more complex covariances are better estimating inter-trial variability.
    Matched MeSH terms: Markov Chains
  8. Fulltext Application of Markov chain in the PageRank algorithm
    Ravi Kumar, P., Alex Goh, K.L., Ashutosh, K.S.
    Pertanika Journal of Science & Technology, 2013;21(2):541-554.
    MyJurnal
    Link analysis algorithms for Web search engines determine the importance and relevance of Web pages. Among the link analysis algorithms, PageRank is the state of the art ranking mechanism that is used in Google search engine today. The PageRank algorithm is modeled as the behavior of a randomized Web surfer; this model can be seen as Markov chain to predict the behavior of a system that travels from one state to another state considering only the current condition. However, this model has the dangling node or hanging node problem because these nodes cannot be presented in a Markov chain model. This paper focuses on the application of Markov chain on PageRank algorithm and discussed a few methods to handle the dangling node problem. The Experiment is done running on WEBSPAM-UK2007 to show the rank results of the dangling nodes.
    Matched MeSH terms: Markov Chains
  9. Attenuation of excitation decay rate due to collective effect
    Tay BA
    Phys Rev E Stat Nonlin Soft Matter Phys, 2014 Aug;90(2):022142.
    PMID: 25215723
    We study a series of N oscillators, each coupled to its nearest neighbors, and linearly to a phonon field through the oscillator's number operator. We show that the Hamiltonian of a pair of adjacent oscillators, or a dimer, within the series of oscillators can be transformed into a form in which they are collectively coupled to the phonon field as a composite unit. In the weak coupling and rotating-wave approximation, the system behaves effectively as the trilinear boson model in the one excitation subspace of the dimer subsystem. The reduced dynamics of the one excitation subspace of the dimer subsystem coupled weakly to a phonon bath is similar to that of a two-level system, with a metastable state against the vacuum. The decay constant of the subsystem is proportional to the dephasing rate of the individual oscillator in a phonon bath, attenuated by a factor that depends on site asymmetry, intersite coupling, and the resonance frequency between the transformed oscillator modes, or excitons. As a result of the collective effect, the excitation relaxation lifetime is prolonged over the dephasing lifetime of an individual oscillator coupled to the same bath.
    Matched MeSH terms: Markov Chains
  10. Cost-Effectiveness of Second-Line Endocrine Therapies in Postmenopausal Women with Hormone Receptor-positive and Human Epidermal Growth Factor Receptor 2-negative Metastatic Breast Cancer in Japan
    Lertjanyakun V, Chaiyakunapruk N, Kunisawa S, Imanaka Y
    Pharmacoeconomics, 2018 09;36(9):1113-1124.
    PMID: 29707743 DOI: 10.1007/s40273-018-0660-3
    BACKGROUND: Exemestane (EXE), exemestane + everolimus (EXE + EVE), toremifene (TOR), and fulvestrant (FUL) are second-line endocrine therapies for postmenopausal hormone receptor-positive (HR +)/human epidermal growth factor receptor 2-negative (HER2 -) metastatic breast cancer (mBC) in Japan. Although the efficacy of these therapies has been shown in recent studies, cost-effectiveness has not yet been determined in Japan.

    OBJECTIVE: This study aimed to examine the cost-effectiveness of second-line endocrine therapies for the treatment of postmenopausal women with HR + and HER2 - mBC.

    METHODS: A Markov model was developed to analyze the cost-effectiveness of the therapies over a 15-year time horizon from a public healthcare payer's perspective. The efficacy and utility parameters were determined via a systematic search of the literature. Direct medical care costs were used. A discount rate of 2% was applied for costs and outcomes. Subgroup analysis was performed for non-visceral metastasis. A series of sensitivity analyses, including probabilistic sensitivity analysis (PSA) and threshold analysis were performed.

    RESULTS: Base-case analyses estimated incremental cost-effectiveness ratios (ICERs) of 3 million and 6 million Japanese yen (JPY)/quality-adjusted life year (QALY) gained for TOR and FUL 500 mg relative to EXE, respectively. FUL 250 mg and EXE + EVE were dominated. The overall survival (OS) highly influenced the ICER. With a willingness-to-pay (WTP) threshold of 5 million JPY/QALY, the probability of TOR being cost-effective was the highest. Subgroup analysis in non-visceral metastasis revealed 0.4 and 10% reduction in ICER from the base-case results of FUL5 500 mg versus EXE and TOR versus EXE, respectively, while threshold analysis indicated EVE and FUL prices should be reduced 73 and 30%, respectively.

    CONCLUSION: As a second-line therapy for postmenopausal women with HR +/HER2 - mBC, TOR may be cost-effective relative to other alternatives and seems to be the most favorable choice, based on a WTP threshold of 5 million JPY/QALY. FUL 250 mg is expected to be as costly and effective as EXE. The cost-effectiveness of EXE + EVE and FUL 500 mg could be improved by a large price reduction. However, the results are highly sensitive to the hazard ratio of OS. Policy makers should carefully interpret and utilize these findings.

    Matched MeSH terms: Markov Chains
  11. Fulltext Cost-effectiveness analysis of strontium ranelate verse alendronate for management of osteoporosis among post-menopausal women in Malaysia using a Markov modelling approach. [Abstract]
    Wu DB, Hussain S, Mak V, Lee KK
    Value Health, 2014 Nov;17(7):A382.
    PMID: 27200852 DOI: 10.1016/j.jval.2014.08.2625
    OBJECTIVES. Osteoporotic fractures are common in older adults and are often associated with high morbidity and mortality. As the incidence increases with age, it is natural that osteoporotic fractures have become a major health problem worldwide. Increasing number of patients with osteoporotic fracture will have a serious economic impact on the patient themselves and the society. The objective of this study is to study the cost-effectiveness of strontium ranelate compared to alendronate for patients with post-menopausal osteoporotic fractures in Malaysia.
    METHODS. A Markov model was developed to project clinical and economic benefits of strontium in a hypothetical cohort of patients (N=1,000) over a 5-year time horizon. This study was conducted from a payer perspective. Model parameters including transition probabilities and costs of treating fracture at various sites were Malaysia-specific. Drug costs were obtained from a public teaching hospital in Kuala Lumpur. Utilities were derived from previous literatures and efficacy data were derived from two pivotal trials, i. e. SOTI and TROPOS trials. Outcomes were presented as cost per quality-adjusted life year (QALY) gained. A discount rate of 3% was applied. Both 1-way and multivariate probabilistic sensitivity analyses were undertaken to evaluate robustness of results.
    RESULTS. Compared to alendronate, strontium could prevent 328 wrist, 192 hip, 7 vertebra and 115 multiple fractures respectively over 5 years, which was translated into 27.9 QALYs gained. Using strontium can lead to cost reduction of MYR1,416,595 (USD442,685), MYR478,257 (USD149,455), MYR22,784 (USD7,120) and MYR61,883 (USD113,088) due to reduced episodes of fractures at wrist/hip/vertebra/multiple sites respectively. The total reduction of direct medical costs of MYR2,279,519 (USD712,349) was larger than the extra drug cost, hence making strontium a cost-saving therapy.
    CONCLUSIONS. It was shown that strontium appeared to be more cost-effective compared to alendronate and hence should be recommended in the public sector in Malaysia.
    Matched MeSH terms: Markov Chains
  12. Fulltext Cost-effectiveness analysis of ultrasonography screening for nonalcoholic fatty liver disease in metabolic syndrome patients
    Phisalprapa P, Supakankunti S, Charatcharoenwitthaya P, Apisarnthanarak P, Charoensak A, Washirasaksiri C, et al.
    Medicine (Baltimore), 2017 Apr;96(17):e6585.
    PMID: 28445256 DOI: 10.1097/MD.0000000000006585
    BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) can be diagnosed early by noninvasive ultrasonography; however, the cost-effectiveness of ultrasonography screening with intensive weight reduction program in metabolic syndrome patients is not clear. This study aims to estimate economic and clinical outcomes of ultrasonography in Thailand.

    METHODS: Cost-effectiveness analysis used decision tree and Markov models to estimate lifetime costs and health benefits from societal perspective, based on a cohort of 509 metabolic syndrome patients in Thailand. Data were obtained from published literatures and Thai database. Results were reported as incremental cost-effectiveness ratios (ICERs) in 2014 US dollars (USD) per quality-adjusted life year (QALY) gained with discount rate of 3%. Sensitivity analyses were performed to assess the influence of parameter uncertainty on the results.

    RESULTS: The ICER of ultrasonography screening of 50-year-old metabolic syndrome patients with intensive weight reduction program was 958 USD/QALY gained when compared with no screening. The probability of being cost-effective was 67% using willingness-to-pay threshold in Thailand (4848 USD/QALY gained). Screening before 45 years was cost saving while screening at 45 to 64 years was cost-effective.

    CONCLUSIONS: For patients with metabolic syndromes, ultrasonography screening for NAFLD with intensive weight reduction program is a cost-effective program in Thailand. Study can be used as part of evidence-informed decision making.

    TRANSLATIONAL IMPACTS: Findings could contribute to changes of NAFLD diagnosis practice in settings where economic evidence is used as part of decision-making process. Furthermore, study design, model structure, and input parameters could also be used for future research addressing similar questions.

    Matched MeSH terms: Markov Chains
  13. Fulltext Cost-effectiveness of aspirin adjuvant therapy in early stage colorectal cancer in older patients
    Soon SS, Chia WK, Chan ML, Ho GF, Jian X, Deng YH, et al.
    PLoS One, 2014;9(9):e107866.
    PMID: 25250815 DOI: 10.1371/journal.pone.0107866
    Recent observational studies showed that post-operative aspirin use reduces cancer relapse and death in the earliest stages of colorectal cancer. We sought to evaluate the cost-effectiveness of aspirin as an adjuvant therapy in Stage I and II colorectal cancer patients aged 65 years and older.
    Matched MeSH terms: Markov Chains*
  14. Cost-effectiveness of dipeptidyl peptidase-4 inhibitor monotherapy versus sulfonylurea monotherapy for people with type 2 diabetes and chronic kidney disease in Thailand
    Permsuwan U, Dilokthornsakul P, Thavorn K, Saokaew S, Chaiyakunapruk N
    J Med Econ, 2017 Feb;20(2):171-181.
    PMID: 27645706 DOI: 10.1080/13696998.2016.1238386
    OBJECTIVE: With a high prevalence of chronic kidney disease (CKD) in type 2 diabetes (T2DM) in Thailand, the appropriate treatment for the patients has become a major concern. This study aimed to evaluate long-term cost-effective of dipeptidyl peptidase-4 (DPP-4) inhibitor monothearpy vs sulfonylurea (SFU) monotherapy in people with T2DM and CKD.

    METHODS: A validated IMS CORE Diabetes Model was used to estimate the long-term costs and outcomes. The efficacy parameters were identified and synthesized using a systematic review and meta-analysis. Baseline characteristics and cost parameters were obtained from published studies and hospital databases in Thailand. Costs were expressed in 2014 US Dollars. Outcomes were presented as an incremental cost-effectiveness ratio (ICER). One-way and probabilistic sensitivity analyses were performed to estimate parameter uncertainty.

    RESULTS: From a societal perspective, treatment with DPP-4 inhibitors yielded more quality-adjusted life years (QALYs) (0.024) at a higher cost (>66,000 Thai baht (THB) or >1,829.27 USD) per person than SFU, resulting in the ICER of >2.7 million THB/QALY (>74,833.70 USD/QALY). The cost-effectiveness results were mainly driven by differences in HbA1c reduction, hypoglycemic events, and drug acquisition cost of DPP-4 inhibitors. At the ceiling ratio of 160,000 THB/QALY (4,434.59 USD/QALY), the probability that DPP-4 inhibitors are cost-effective compared to SFU was less than 10%.

    CONCLUSIONS: Compared to SFU, DPP-4 inhibitor monotherapy is not a cost-effective treatment for people with T2DM and CKD in Thailand.

    Matched MeSH terms: Markov Chains
  15. Fulltext Cross-border sexual transmission of the newly emerging HIV-1 clade CRF51_01B
    Cheong HT, Ng KT, Ong LY, Chook JB, Chan KG, Takebe Y, et al.
    PLoS One, 2014;9(10):e111236.
    PMID: 25340817 DOI: 10.1371/journal.pone.0111236
    A novel HIV-1 recombinant clade (CRF51_01B) was recently identified among men who have sex with men (MSM) in Singapore. As cases of sexually transmitted HIV-1 infection increase concurrently in two socioeconomically intimate countries such as Malaysia and Singapore, cross transmission of HIV-1 between said countries is highly probable. In order to investigate the timeline for the emergence of HIV-1 CRF51_01B in Singapore and its possible introduction into Malaysia, 595 HIV-positive subjects recruited in Kuala Lumpur from 2008 to 2012 were screened. Phylogenetic relationship of 485 amplified polymerase gene sequences was determined through neighbour-joining method. Next, near-full length sequences were amplified for genomic sequences inferred to be CRF51_01B and subjected to further analysis implemented through Bayesian Markov chain Monte Carlo (MCMC) sampling and maximum likelihood methods. Based on the near full length genomes, two isolates formed a phylogenetic cluster with CRF51_01B sequences of Singapore origin, sharing identical recombination structure. Spatial and temporal information from Bayesian MCMC coalescent and maximum likelihood analysis of the protease, gp120 and gp41 genes suggest that Singapore is probably the country of origin of CRF51_01B (as early as in the mid-1990s) and featured a Malaysian who acquired the infection through heterosexual contact as host for its ancestral lineages. CRF51_01B then spread rapidly among the MSM in Singapore and Malaysia. Although the importation of CRF51_01B from Singapore to Malaysia is supported by coalescence analysis, the narrow timeframe of the transmission event indicates a closely linked epidemic. Discrepancies in the estimated divergence times suggest that CRF51_01B may have arisen through multiple recombination events from more than one parental lineage. We report the cross transmission of a novel CRF51_01B lineage between countries that involved different sexual risk groups. Understanding the cross-border transmission of HIV-1 involving sexual networks is crucial for effective intervention strategies in the region.
    Matched MeSH terms: Markov Chains
  16. Developmental Approach for Behavior Learning Using Primitive Motion Skills
    Dawood F, Loo CK
    Int J Neural Syst, 2018 May;28(4):1750038.
    PMID: 29022403 DOI: 10.1142/S0129065717500381
    Imitation learning through self-exploration is essential in developing sensorimotor skills. Most developmental theories emphasize that social interactions, especially understanding of observed actions, could be first achieved through imitation, yet the discussion on the origin of primitive imitative abilities is often neglected, referring instead to the possibility of its innateness. This paper presents a developmental model of imitation learning based on the hypothesis that humanoid robot acquires imitative abilities as induced by sensorimotor associative learning through self-exploration. In designing such learning system, several key issues will be addressed: automatic segmentation of the observed actions into motion primitives using raw images acquired from the camera without requiring any kinematic model; incremental learning of spatio-temporal motion sequences to dynamically generates a topological structure in a self-stabilizing manner; organization of the learned data for easy and efficient retrieval using a dynamic associative memory; and utilizing segmented motion primitives to generate complex behavior by the combining these motion primitives. In our experiment, the self-posture is acquired through observing the image of its own body posture while performing the action in front of a mirror through body babbling. The complete architecture was evaluated by simulation and real robot experiments performed on DARwIn-OP humanoid robot.
    Matched MeSH terms: Markov Chains
  17. Economic and efficiency based optimisation of water quality monitoring network for land use impact assessment
    Camara M, Jamil NR, Abdullah AFB, Hashim RB, Aliyu AG
    Sci Total Environ, 2020 May 30;737:139800.
    PMID: 32526579 DOI: 10.1016/j.scitotenv.2020.139800
    The evaluation of the importance of having accurate and representative stations in a network for river water quality monitoring is always a matter of concern. The minimal budget and time demands of water quality monitoring programme may appear very attractive, especially when dealing with large-scale river watersheds. This article proposes an improved methodology for optimising water quality monitoring network for present and forthcoming monitoring of water quality under a case study of the Selangor River watershed in Malaysia, where different monitoring networks are being used by water management authorities. Knowing that the lack of financial resources in developing countries like Malaysia is one of the reasons for inadequate monitoring network density, to identify an optimised network for cost-efficiency benefits in this study, a geo-statistical technique coupled Kendall's W was first applied to analyse the performance of each monitoring station in the existing networks under the monitored water quality parameters. Second, the present and future changes in non-point pollution sources were simulated using the integrated Cellular Automata and Markov chain model (CA-Markov). Third, Station Potential Pollution Score (SPPS) determined based on Analytic Hierarchy Process (AHP) was used to weight each station under the changes of non-point pollution sources for 2015, 2024, and 2033 prior to prioritisation. Finally, according to the Kendall's W test on kriging results, the weights of non-point sources from the AHP evaluation and fuzzy membership functions, six most efficient sampling stations were identified to build a robust network for the present and future monitoring of water quality status in the Selangor River watershed. This study proposes a useful approach to the pertinent agencies and management authority concerned to establish appropriate methods for developing an efficient water quality monitoring network for tropical rivers.
    Matched MeSH terms: Markov Chains
  18. Fulltext Enhanced handover mechanism using mobility prediction in wireless networks
    Yap KL, Chong YW, Liu W
    PLoS One, 2020;15(1):e0227982.
    PMID: 31978101 DOI: 10.1371/journal.pone.0227982
    The rapid increase in the usage of the mobile internet has led to a great expansion of cellular data networks in order to provide better quality of service. However, the cost to expand the cellular network is high. One of the solutions to provide affordable wireless connectivity is the deployment of a WiFi access point to offload users' data usage. Nevertheless, the frequent and inefficient handover process between the WiFi AP and cellular network, especially when the mobile device is on the go, may degrade the network performance. Mobile devices do not have the intelligence to select the optimal network to enhance the quality of service (QoS). This paper presents an enhanced handover mechanism using mobility prediction (eHMP) to assist mobile devices in the handover process so that users can experience seamless connectivity. eHMP is tested in two wireless architectures, homogeneous and heterogeneous networks. The network performance significantly improved when eHMP is used in a homogeneous network, where the network throughput increases by 106% and the rate of retransmission decreases by 85%. When eHMP is used in a heterogeneous network, the network throughput increases by 55% and the retransmission rate decreases by 75%. The findings presented in this paper reveal that mobility prediction coupled with the multipath protocol can improve the QoS for mobile devices. These results will contribute to a better understanding of how the network service provider can offload traffic to the WiFi network without experiencing performance degradation.
    Matched MeSH terms: Markov Chains
  19. Gender classification in children based on speech characteristics: using fundamental and formant frequencies of Malay vowels
    Zourmand A, Ting HN, Mirhassani SM
    J Voice, 2013 Mar;27(2):201-9.
    PMID: 23473455 DOI: 10.1016/j.jvoice.2012.12.006
    Speech is one of the prevalent communication mediums for humans. Identifying the gender of a child speaker based on his/her speech is crucial in telecommunication and speech therapy. This article investigates the use of fundamental and formant frequencies from sustained vowel phonation to distinguish the gender of Malay children aged between 7 and 12 years. The Euclidean minimum distance and multilayer perceptron were used to classify the gender of 360 Malay children based on different combinations of fundamental and formant frequencies (F0, F1, F2, and F3). The Euclidean minimum distance with normalized frequency data achieved a classification accuracy of 79.44%, which was higher than that of the nonnormalized frequency data. Age-dependent modeling was used to improve the accuracy of gender classification. The Euclidean distance method obtained 84.17% based on the optimal classification accuracy for all age groups. The accuracy was further increased to 99.81% using multilayer perceptron based on mel-frequency cepstral coefficients.
    Matched MeSH terms: Markov Chains
  20. HMM based automated wheelchair navigation using EOG traces in EEG
    Aziz F, Arof H, Mokhtar N, Mubin M
    J Neural Eng, 2014 Oct;11(5):056018.
    PMID: 25188730 DOI: 10.1088/1741-2560/11/5/056018
    This paper presents a wheelchair navigation system based on a hidden Markov model (HMM), which we developed to assist those with restricted mobility. The semi-autonomous system is equipped with obstacle/collision avoidance sensors and it takes the electrooculography (EOG) signal traces from the user as commands to maneuver the wheelchair. The EOG traces originate from eyeball and eyelid movements and they are embedded in EEG signals collected from the scalp of the user at three different locations. Features extracted from the EOG traces are used to determine whether the eyes are open or closed, and whether the eyes are gazing to the right, center, or left. These features are utilized as inputs to a few support vector machine (SVM) classifiers, whose outputs are regarded as observations to an HMM. The HMM determines the state of the system and generates commands for navigating the wheelchair accordingly. The use of simple features and the implementation of a sliding window that captures important signatures in the EOG traces result in a fast execution time and high classification rates. The wheelchair is equipped with a proximity sensor and it can move forward and backward in three directions. The asynchronous system achieved an average classification rate of 98% when tested with online data while its average execution time was less than 1 s. It was also tested in a navigation experiment where all of the participants managed to complete the tasks successfully without collisions.
    Matched MeSH terms: Markov Chains*
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