Displaying publications 201 - 220 of 616 in total

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  1. Fulltext A novel 3D ray launching technique for radio propagation prediction in indoor environments
    Geok TK, Hossain F, Chiat ATW
    PLoS One, 2018;13(8):e0201905.
    PMID: 30086170 DOI: 10.1371/journal.pone.0201905
    Radio propagation prediction simulation methods based on deterministic technique such as ray launching is extensively used to accomplish radio channel characterization. However, the superiority of the simulation depends on the number of rays launched and received. This paper presented the indoor three-dimensional (3D) Minimum Ray Launching Maximum Accuracy (MRLMA) technique, which is applicable for an efficient indoor radio wave propagation prediction. Utilizing the novel MRLMA technique in the simulation environment for ray lunching and tracing can drastically reduce the number of rays that need to be traced, and improve the efficiency of ray tracing. Implementation and justification of MRLMA presented in the paper. An indoor office 3D layouts are selected and simulations have been performed using the MRLMA and other reference techniques. Results showed that the indoor 3D MRLMA model is appropriate for wireless communications network systems design and optimization process with respect to efficiency, coverage, number of rays launching, number of rays received by the mobile station, and simulation time.
    Matched MeSH terms: Computer Simulation
  2. A hybrid of Cuckoo Search and Minimization of Metabolic Adjustment to optimize metabolites production in genome-scale models
    Arif MA, Mohamad MS, Abd Latif MS, Deris S, Remli MA, Mohd Daud K, et al.
    Comput Biol Med, 2018 11 01;102:112-119.
    PMID: 30267898 DOI: 10.1016/j.compbiomed.2018.09.015
    Metabolic engineering involves the modification and alteration of metabolic pathways to improve the production of desired substance. The modification can be made using in silico gene knockout simulation that is able to predict and analyse the disrupted genes which may enhance the metabolites production. Global optimization algorithms have been widely used for identifying gene knockout strategies. However, their productions were less than theoretical maximum and the algorithms are easily trapped into local optima. These algorithms also require a very large computation time to obtain acceptable results. This is due to the complexity of the metabolic models which are high dimensional and contain thousands of reactions. In this paper, a hybrid algorithm of Cuckoo Search and Minimization of Metabolic Adjustment is proposed to overcome the aforementioned problems. The hybrid algorithm searches for the near-optimal set of gene knockouts that leads to the overproduction of metabolites. Computational experiments on two sets of genome-scale metabolic models demonstrate that the proposed algorithm is better than the previous works in terms of growth rate, Biomass Product Couple Yield, and computation time.
    Matched MeSH terms: Computer Simulation
  3. 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: Computer Simulation
  4. Fulltext Hybrid PSO-FLC for dynamic global peak extraction of the partially shaded photovoltaic system
    Farh HMH, Eltamaly AM, Othman MF
    PLoS One, 2018;13(11):e0206171.
    PMID: 30388119 DOI: 10.1371/journal.pone.0206171
    Particle Swarm Optimization (PSO) is widely used in maximum power point tracking (MPPT) of photovoltaic (PV) energy systems. Nevertheless, this technique suffers from two main problems in the case of partial shading conditions (PSCs). The first problem is that PSO is a time invariant optimization technique that cannot follow the dynamic global peak (GP) under time variant shading patterns (SPs) and sticks to the first GP that occurs at the beginning. This problem can be solved by dispersing the PSO particles using two new techniques introduced in this paper. The two new proposed PSO re-initialization techniques are to disperse the particles upon the SP changes and the other one is upon a predefined time (PDT). The second problem is regarding the high oscillations around steady state, which can be solved by using fuzzy logic controller (FLC) to fine-tune the output power and voltage from the PV system. The new contribution of this paper is the hybrid PSO-FLC with two PSO particles dispersing techniques that is able to solve the two previous mentioned problems effectively and improve the performance of the PV system in both normal and PSCs. A detailed list of comparisons between hybrid PSO-FLC and original PSO using the two proposed methodologies are achieved. The results prove the superior performance of hybrid PSO-FLC compared to PSO in terms of efficiency, accuracy, oscillations reduction around steady state and soft tuning of the GP tracked.
    Matched MeSH terms: Computer Simulation
  5. Fulltext A low-loss and compact single-layer butler matrix for a 5G base station antenna
    Idrus II, Abdul Latef T, Aridas NK, Abu Talip MS, Yamada Y, Abd Rahman T, et al.
    PLoS One, 2019;14(12):e0226499.
    PMID: 31841536 DOI: 10.1371/journal.pone.0226499
    Researchers are increasingly showing interest in the application of a Butler matrix for fifth-generation (5G) base station antennas. However, the design of the Butler matrix is challenging at millimeter wave because of the very small wavelength. The literature has reported issues of high insertion losses and incorrect output phases at the output ports of the Butler matrix, which affects the radiation characteristics. To overcome these issues, the circuit elements of the Butler matrix such as the crossover, the quadrature hybrid and the phase shifter must be designed using highly accurate dimensions. This paper presents a low-loss and compact single-layer 8 × 8 Butler matrix operating at 28 GHz. The optimum design of each circuit element is also demonstrated in detail. The designed Butler matrix was fabricated to validate the simulated results. The measured results showed return losses of less than -10 dB at 28 GHz. The proposed Butler matrix achieved a low insertion loss and a low phase error of ± 2 dB and ± 10°, respectively. In sum, this work obtained a good agreement between the simulated and measured results.
    Matched MeSH terms: Computer Simulation
  6. A Comparison Between Bayesian and Maximum Likelihood Estimations in Estimating Finite Mixture Model for Financial Data
    Seuk-Yen Phoong, Mohd Tahir Ismail
    Sains Malaysiana, 2015;44:1033-1039.
    Over the years, maximum likelihood estimation and Bayesian method became popular statistical tools in which applied to fit finite mixture model. These trends begin with the advent of computer technology during the last decades. Moreover, the asymptotic properties for both statistical methods also act as one of the main reasons that boost the popularity of the methods. The difference between these two approaches is that the parameters for maximum likelihood estimation are fixed, but unknown meanwhile the parameters for Bayesian method act as random variables with known prior distributions. In the present paper, both the maximum likelihood estimation and Bayesian method are applied to investigate the relationship between exchange rate and the rubber price for Malaysia, Thailand, Philippines and Indonesia. In order to identify the most plausible method between Bayesian method and maximum likelihood estimation of time series data, Akaike Information Criterion and Bayesian Information Criterion are adopted in this paper. The result depicts that the Bayesian method performs better than maximum likelihood estimation on financial data.
    Matched MeSH terms: Computer Simulation
  7. Dynamic Absorption Enhancement and Equivalent Resonant Circuit Modeling of Tunable Graphene-Metal Hybrid Antenna
    Ullah Z, Nawi I, Witjaksono G, Tansu N, Khattak MI, Junaid M, et al.
    Sensors (Basel), 2020 Jun 04;20(11).
    PMID: 32512718 DOI: 10.3390/s20113187
    Plasmonic antennas are attractive optical components of the optoelectronic devices, operating in the far-infrared regime for sensing and imaging applications. However, low optical absorption hinders its potential applications, and their performance is limited due to fixed resonance frequency. In this article, a novel gate tunable graphene-metal hybrid plasmonic antenna with stacking configuration is proposed and investigated to achieve tunable performance over a broad range of frequencies with enhanced absorption characteristics. The hybrid graphene-metal antenna geometry is built up with a hexagon radiator that is supported by the Al2O3 insulator layer and graphene reflector. This stacked structure is deposited in the high resistive Si wafer substrate, and the hexagon radiator itself is a sandwich structure, which is composed of gold hexagon structure and two multilayer graphene stacks. The proposed antenna characteristics i.e., tunability of frequency, the efficiency corresponding to characteristics modes, and the tuning of absorption spectra, are evaluated by full-wave numerical simulations. Besides, the unity absorption peak that was realized through the proposed geometry is sensitive to the incident angle of TM-polarized incidence waves, which can flexibly shift the maxima of the absorption peak from 30 THz to 34 THz. Finally, an equivalent resonant circuit model for the investigated antenna based on the simulations results is designed to validate the antenna performance. Parametric analysis of the proposed antenna is carried out through altering the geometric parameters and graphene parameters in the Computer Simulation Technology (CST) studio. This clearly shows that the proposed antenna has a resonance frequency at 33 THz when the graphene sheet Fermi energy is increased to 0.3 eV by applying electrostatic gate voltage. The good agreement of the simulation and equivalent circuit model results makes the graphene-metal antenna suitable for the realization of far-infrared sensing and imaging device containing graphene antenna with enhanced performance.
    Matched MeSH terms: Computer Simulation
  8. Fulltext In silico gene knockout prediction using a hybrid of Bat algorithm and minimization of metabolic adjustment
    Man MY, Mohamad MS, Choon YW, Ismail MA
    J Integr Bioinform, 2021 Aug 04;18(3).
    PMID: 34348418 DOI: 10.1515/jib-2020-0037
    Microorganisms commonly produce many high-demand industrial products like fuels, food, vitamins, and other chemicals. Microbial strains are the strains of microorganisms, which can be optimized to improve their technological properties through metabolic engineering. Metabolic engineering is the process of overcoming cellular regulation in order to achieve a desired product or to generate a new product that the host cells do not usually need to produce. The prediction of genetic manipulations such as gene knockout is part of metabolic engineering. Gene knockout can be used to optimize the microbial strains, such as to maximize the production rate of chemicals of interest. Metabolic and genetic engineering is important in producing the chemicals of interest as, without them, the product yields of many microorganisms are normally low. As a result, the aim of this paper is to propose a combination of the Bat algorithm and the minimization of metabolic adjustment (BATMOMA) to predict which genes to knock out in order to increase the succinate and lactate production rates in Escherichia coli (E. coli).
    Matched MeSH terms: Computer Simulation
  9. Fulltext Induced electron radiation effect on the performance of inter-satellite optical wireless communication
    Youssouf AS, Hasbullah NF, Saidin N, Habaebi MH, Parthiban R, Bin Mohamed Zin MR, et al.
    PLoS One, 2021;16(12):e0259649.
    PMID: 34972119 DOI: 10.1371/journal.pone.0259649
    This paper provides the details of a study on the effects of electron radiation on the Performance of Inters-satellite Optical Wireless Communication (IsOWC). Academia and industry focus on solutions that can improve performance and reduce the cost of IsWOC systems. Spacecraft, space stations, satellites, and astronauts are exposed to an increased level of radiation when in space, so it is essential to evaluate the risks and performance effects associated with extended radiation exposures in missions and space travel in general. This investigation focuses on LEO, especially in the near-equatorial radiation environment. Radiation experiments supported with simulations have made it possible to obtain and evaluate the electron radiation impact on optoelectronics at the device level and system level performances. The electron radiation has induced a system degradation of 70%. This result demonstrates the importance of such an investigation to predict and take necessary and suitable reliable quality service for future space missions.
    Matched MeSH terms: Computer Simulation
  10. Investigation of two-way fluid-structure interaction of blood flow in a patient-specific left coronary artery
    Athani A, Ghazali NNN, Badruddin IA, Kamangar S, Anqi AE, Algahtani A
    Biomed Mater Eng, 2022;33(1):13-30.
    PMID: 34366314 DOI: 10.3233/BME-201171
    BACKGROUND: The blood flow in the human artery has been a subject of sincere interest due to its prime importance linked with human health. The hemodynamic study has revealed an essential aspect of blood flow that eventually proved to be paramount to make a correct decision to treat patients suffering from cardiac disease.

    OBJECTIVE: The current study aims to elucidate the two-way fluid-structure interaction (FSI) analysis of the blood flow and the effect of stenosis on hemodynamic parameters.

    METHODS: A patient-specific 3D model of the left coronary artery was constructed based on computed tomography (CT) images. The blood is assumed to be incompressible, homogenous, and behaves as Non-Newtonian, while the artery is considered as a nonlinear elastic, anisotropic, and incompressible material. Pulsatile flow conditions were applied at the boundary. Two-way coupled FSI modeling approach was used between fluid and solid domain. The hemodynamic parameters such as the pressure, velocity streamline, and wall shear stress were analyzed in the fluid domain and the solid domain deformation.

    RESULTS: The simulated results reveal that pressure drop exists in the vicinity of stenosis and a recirculation region after the stenosis. It was noted that stenosis leads to high wall stress. The results also demonstrate an overestimation of wall shear stress and velocity in the rigid wall CFD model compared to the FSI model.

    Matched MeSH terms: Computer Simulation
  11. Fulltext Microwave bio-sensor based on symmetrical split ring resonator with spurline filters for therapeutic goods detection
    Alahnomi RA, Zakaria Z, Ruslan E, Ab Rashid SR, Mohd Bahar AA, Shaaban A
    PLoS One, 2017;12(9):e0185122.
    PMID: 28934301 DOI: 10.1371/journal.pone.0185122
    A novel symmetrical split ring resonator (SSRR) based microwave sensor with spurline filters for detecting and characterizing the properties of solid materials has been developed. Due to the weak perturbation in the interaction of material under test (MUT) and planar microwave sensor, spurline filters were embedded to the SSRR microwave sensor which effectively enhanced Q-factor with suppressing the undesired harmonic frequency. The spurline filter structures force the presented sensor to resonate at a fundamental frequency of 2.2 GHz with the capabilities of suppressing rejected harmonic frequency and miniaturization in circuit size. A wide bandwidth rejection is achieved by using double spurlines filters with high Q-factor achievement (up to 652.94) compared to single spurline filter. The new SSRR sensor with spurline filters displayed desired properties such as high sensitivity, accuracy, and performance with a 1.3% typical percentage error in the measurement results. Furthermore, the sensor has been successfully applied for detecting and characterizing solid materials (such as Roger 5880, Roger 4350, and FR4) and evidently demonstrated that it can suppress the harmonic frequency effectively. This novel design with harmonic suppression is useful for various applications such as food industry (meat, fruit, vegetables), biological medicine (derived from proteins and other substances produced by the body), and Therapeutic goods (antiseptics, vitamins, anti-psychotics, and other medicines).
    Matched MeSH terms: Computer Simulation
  12. Fulltext Microwave Imaging Sensor Using Compact Metamaterial UWB Antenna with a High Correlation Factor
    Islam MM, Islam MT, Faruque MRI, Samsuzzaman M, Misran N, Arshad H
    Materials (Basel), 2015 Jul 23;8(8):4631-4651.
    PMID: 28793461 DOI: 10.3390/ma8084631
    The design of a compact metamaterial ultra-wideband (UWB) antenna with a goal towards application in microwave imaging systems for detecting unwanted cells in human tissue, such as in cases of breast cancer, heart failure and brain stroke detection is proposed. This proposed UWB antenna is made of four metamaterial unit cells, where each cell is an integration of a modified split ring resonator (SRR), capacitive loaded strip (CLS) and wire, to attain a design layout that simultaneously exhibits both a negative magnetic permeability and a negative electrical permittivity. This design results in an astonishing negative refractive index that enables amplification of the radiated power of this reported antenna, and therefore, high antenna performance. A low-cost FR4 substrate material is used to design and print this reported antenna, and has the following characteristics: thickness of 1.6 mm, relative permeability of one, relative permittivity of 4.60 and loss tangent of 0.02. The overall antenna size is 19.36 mm × 27.72 mm × 1.6 mm where the electrical dimension is 0.20 λ × 0.28 λ × 0.016 λ at the 3.05 GHz lower frequency band. Voltage Standing Wave Ratio (VSWR) measurements have illustrated that this antenna exhibits an impedance bandwidth from 3.05 GHz to more than 15 GHz for VSWR < 2 with an average gain of 4.38 dBi throughout the operating frequency band. The simulations (both HFSS and computer simulation technology (CST)) and the measurements are in high agreement. A high correlation factor and the capability of detecting tumour simulants confirm that this reported UWB antenna can be used as an imaging sensor.
    Matched MeSH terms: Computer Simulation
  13. A review of mathematical modeling and simulation of controlled-release fertilizers
    Irfan SA, Razali R, KuShaari K, Mansor N, Azeem B, Ford Versypt AN
    J Control Release, 2018 02 10;271:45-54.
    PMID: 29274697 DOI: 10.1016/j.jconrel.2017.12.017
    Nutrients released into soils from uncoated fertilizer granules are lost continuously due to volatilization, leaching, denitrification, and surface run-off. These issues have caused economic loss due to low nutrient absorption efficiency and environmental pollution due to hazardous emissions and water eutrophication. Controlled-release fertilizers (CRFs) can change the release kinetics of the fertilizer nutrients through an abatement strategy to offset these issues by providing the fertilizer content in synchrony with the metabolic needs of the plants. Parametric analysis of release characteristics of CRFs is of paramount importance for the design and development of new CRFs. However, the experimental approaches are not only time consuming, but they are also cumbersome and expensive. Scientists have introduced mathematical modeling techniques to predict the release of nutrients from the CRFs to elucidate fundamental understanding of the dynamics of the release processes and to design new CRFs in a shorter time and with relatively lower cost. This paper reviews and critically analyzes the latest developments in the mathematical modeling and simulation techniques that have been reported for the characteristics and mechanisms of nutrient release from CRFs. The scope of this review includes the modeling and simulations techniques used for coated, controlled-release fertilizers.
    Matched MeSH terms: Computer Simulation
  14. Fulltext Robust artificial bee colony in the Hopfield network for 2-satisfiability problem
    Mohd. Shareduwan Mohd. Kasihmuddin, Mohd. Asyraf Mansor, Saratha Sathasivam
    Pertanika Journal of Science & Technology, 2017;25(2):453-468.
    MyJurnal
    Swarm intelligence is a research area that models the population of swarm that is able to self-organise effectively. Honey bees that gather around their hive with a distinctive behaviour is another example of swarm intelligence. In fact, the artificial bee colony (ABC) algorithm is a swarm-based meta-heuristic algorithm introduced by Karaboga in order to optimise numerical problems. 2SAT can be treated as a constrained optimisation problem which represents any problem by using clauses containing 2 literals each. Most of the current researchers represent their problem by using 2SAT. Meanwhile, the Hopfield neural network incorporated with the ABC has been utilised to perform randomised 2SAT. Hence, the aim of this study is to investigate the performance of the solutions produced by HNN2SAT-ABC and compared it with the traditional HNN2SAT-ES. The comparison of both algorithms has been examined by using Microsoft Visual Studio 2013 C++ Express Software. The detailed comparison on the performance of the ABC and ES in performing 2SAT is discussed based on global minima ratio, hamming distance, CPU time and fitness landscape. The results obtained from the computer simulation depict the beneficial features of ABC compared to ES. Moreover, the findings have led to a significant implication on the choice of determining an alternative method to perform 2SAT.
    Matched MeSH terms: Computer Simulation
  15. Observation and explanation of two-dimensional interconversion of oximes with multiple heart-cutting using comprehensive multidimensional gas chromatography
    Kulsing C, Nolvachai Y, Wong YF, Glouzman MI, Marriott PJ
    J Chromatogr A, 2018 Apr 20;1546:97-105.
    PMID: 29548566 DOI: 10.1016/j.chroma.2018.02.035
    Real-time interconversion processes produce unconventional peak broadening in gas chromatography (GC), and can be used to generate kinetic and thermodynamic data. In this study, an unusual separation situation in comprehensive two dimensional GC where two dimensional interconversion (i.e. a raised plateau in both first and second dimension, 1D and 2D) was observed in analysis of oxime isomers. This resulted in a characteristic and unusual rectangular peak shape in the two dimensional result. A related theoretical approach was introduced to explain the peak shape supported by simulation results which can be varied depending on concentration profiles and kinetics of the process. The simulated results were supported by experimental results obtained by a comprehensive heart-cut multidimensional GC (H/C MDGC) approach which was developed to clearly investigate isomerisation of E/Z oxime molecules in both 1D and 2D separations under different isothermal conditions. The carrier gas flow and oven temperature were selected according to initial results for 1D interconversion on a poly(ethyleneglycol) stationary phase, which was further used in both 1D and 2D separations to result in broad zones of oxime interconversion in both dimensions. The method involved repetitive injections of oxime sample, then sampling contiguous fractions of sample into a long 2D column which is intended to promote considerable interconversion. Comprehensiveness arises from the fact that the whole sample is sampled from the 1D to the 2D column, with the long 2D column replacing the short 2D column used in classical comprehensive two-dimensional gas chromatography, where the latter will not promote sufficient interconversion. Data processing and presentation permits a 'rectangular' distribution corresponding to the separated compounds, characteristic of this experiment.
    Matched MeSH terms: Computer Simulation
  16. Visualization of multiphase pulsatile blood over single phase blood flow in a patient specific stenosed left coronary artery using image processing technique
    Athani A, Ghazali NNN, Anjum Badruddin I, Kamangar S, Salman Ahmed NJ, Honnutagi A
    Biomed Mater Eng, 2023;34(1):13-35.
    PMID: 36278331 DOI: 10.3233/BME-211333
    BACKGROUND: Coronary arteries disease has been reported as one of the principal roots of deaths worldwide.

    OBJECTIVE: The aim of this study is to analyze the multiphase pulsatile blood flow in the left coronary artery tree with stenosis.

    METHODS: The 3D left coronary artery model was reconstructed using 2D computerized tomography (CT) scan images. The Red Blood Cell (RBC) and varying hemodynamic parameters for single and multiphase blood flow conditions were analyzed.

    RESULTS: Results asserted that the multiphase blood flow modeling has a maximum velocity of 1.017 m/s and1.339 m/s at the stenosed region during the systolic and diastolic phases respectively. The increase in Wall Shear Stress (WSS) observed at the stenosed region during the diastole phase as compared during the systolic phase. It was also observed that the highest Oscillatory Shear Index (OSI) regions are found in the downstream area of stenosis and across the bifurcations. The increase in RBCs velocity from 0.45 m/s to 0.6 m/s across the stenosis was also noticed.

    CONCLUSION: The computational multiphase blood flow analysis improves the understanding and accuracy of the complex flow conditions of blood elements (RBC and Plasma) and provides the progression of the disease development in the coronary arteries. This study helps to enhance the diagnosis of the blocked (stenosed) arteries more precisely compared to the single-phase blood flow modeling.

    Matched MeSH terms: Computer Simulation
  17. Bayesian multivariant fine mapping using the Laplace prior
    Walters K, Yaacob H
    Genet Epidemiol, 2023 Apr;47(3):249-260.
    PMID: 36739616 DOI: 10.1002/gepi.22517
    Currently, the only effect size prior that is routinely implemented in a Bayesian fine-mapping multi-single-nucleotide polymorphism (SNP) analysis is the Gaussian prior. Here, we show how the Laplace prior can be deployed in Bayesian multi-SNP fine mapping studies. We compare the ranking performance of the posterior inclusion probability (PIP) using a Laplace prior with the ranking performance of the corresponding Gaussian prior and FINEMAP. Our results indicate that, for the simulation scenarios we consider here, the Laplace prior can lead to higher PIPs than either the Gaussian prior or FINEMAP, particularly for moderately sized fine-mapping studies. The Laplace prior also appears to have better worst-case scenario properties. We reanalyse the iCOGS case-control data from the CASP8 region on Chromosome 2. Even though this study has a total sample size of nearly 90,000 individuals, there are still some differences in the top few ranked SNPs if the Laplace prior is used rather than the Gaussian prior. R code to implement the Laplace (and Gaussian) prior is available at https://github.com/Kevin-walters/lapmapr.
    Matched MeSH terms: Computer Simulation
  18. Fulltext Vaccines alone are no silver bullets: a modeling study on the impact of efficient contact tracing on COVID-19 infection and transmission in Malaysia
    Baha Raja D, Abdul Taib NA, Teo AKJ, Jayaraj VJ, Ting CY
    Int Health, 2023 Jan 03;15(1):37-46.
    PMID: 35265998 DOI: 10.1093/inthealth/ihac005
    BACKGROUND: The computer simulation presented in this study aimed to investigate the effect of contact tracing on coronavirus disease 2019 (COVID-19) transmission and infection in the context of rising vaccination rates.

    METHODS: This study proposed a deterministic, compartmental model with contact tracing and vaccination components. We defined contact tracing effectiveness as the proportion of contacts of a positive case that was successfully traced and the vaccination rate as the proportion of daily doses administered per population in Malaysia. Sensitivity analyses on the untraced and infectious populations were conducted.

    RESULTS: At a vaccination rate of 1.4%, contact tracing with an effectiveness of 70% could delay the peak of untraced asymptomatic cases by 17 d and reduce it by 70% compared with 30% contact tracing effectiveness. A similar trend was observed for symptomatic cases when a similar experiment setting was used. We also performed sensitivity analyses by using different combinations of contact tracing effectiveness and vaccination rates. In all scenarios, the effect of contact tracing on COVID-19 incidence persisted for both asymptomatic and symptomatic cases.

    CONCLUSIONS: While vaccines are progressively rolled out, efficient contact tracing must be rapidly implemented concurrently to reach, find, test, isolate and support the affected populations to bring COVID-19 under control.

    Matched MeSH terms: Computer Simulation
  19. Fulltext A hybrid multi objective cellular spotted hyena optimizer for wellbore trajectory optimization
    Biswas K, Nazir A, Rahman MT, Khandaker MU, Idris AM, Islam J, et al.
    PLoS One, 2022;17(1):e0261427.
    PMID: 35085239 DOI: 10.1371/journal.pone.0261427
    Cost and safety are critical factors in the oil and gas industry for optimizing wellbore trajectory, which is a constrained and nonlinear optimization problem. In this work, the wellbore trajectory is optimized using the true measured depth, well profile energy, and torque. Numerous metaheuristic algorithms were employed to optimize these objectives by tuning 17 constrained variables, with notable drawbacks including decreased exploitation/exploration capability, local optima trapping, non-uniform distribution of non-dominated solutions, and inability to track isolated minima. The purpose of this work is to propose a modified multi-objective cellular spotted hyena algorithm (MOCSHOPSO) for optimizing true measured depth, well profile energy, and torque. To overcome the aforementioned difficulties, the modification incorporates cellular automata (CA) and particle swarm optimization (PSO). By adding CA, the SHO's exploration phase is enhanced, and the SHO's hunting mechanisms are modified with PSO's velocity update property. Several geophysical and operational constraints have been utilized during trajectory optimization and data has been collected from the Gulf of Suez oil field. The proposed algorithm was compared with the standard methods (MOCPSO, MOSHO, MOCGWO) and observed significant improvements in terms of better distribution of non-dominated solutions, better-searching capability, a minimum number of isolated minima, and better Pareto optimal front. These significant improvements were validated by analysing the algorithms in terms of some statistical analysis, such as IGD, MS, SP, and ER. The proposed algorithm has obtained the lowest values in IGD, SP and ER, on the other side highest values in MS. Finally, an adaptive neighbourhood mechanism has been proposed which showed better performance than the fixed neighbourhood topology such as L5, L9, C9, C13, C21, and C25. Hopefully, this newly proposed modified algorithm will pave the way for better wellbore trajectory optimization.
    Matched MeSH terms: Computer Simulation
  20. Fulltext Effect of nanoshell geometries, sizes, and quantum emitter parameters on the sensitivity of plasmon-exciton hybrid nanoshells for sensing application
    Firoozi A, Amphawan A, Khordad R, Mohammadi A, Jalali T, Edet CO, et al.
    Sci Rep, 2023 Jul 13;13(1):11325.
    PMID: 37443203 DOI: 10.1038/s41598-023-38475-1
    A proposed nanosensor based on hybrid nanoshells consisting of a core of metal nanoparticles and a coating of molecules is simulated by plasmon-exciton coupling in semi classical approach. We study the interaction of electromagnetic radiation with multilevel atoms in a way that takes into account both the spatial and the temporal dependence of the local fields. Our approach has a wide range of applications, from the description of pulse propagation in two-level media to the elaborate simulation of optoelectronic devices, including sensors. We have numerically solved the corresponding system of coupled Maxwell-Liouville equations using finite difference time domain (FDTD) method for different geometries. Plasmon-exciton hybrid nanoshells with different geometries are designed and simulated, which shows more sensitive to environment refractive index (RI) than nanosensor based on localized surface plasmon. The effects of nanoshell geometries, sizes, and quantum emitter parameters on the sensitivity of nanosensors to changes in the RI of the environment were investigated. It was found that the cone-like nanoshell with a silver core and quantum emitter shell had the highest sensitivity. The tapered shape of the cone like nanoshell leads to a higher density of plasmonic excitations at the tapered end of the nanoshell. Under specific conditions, two sharp, deep LSPR peaks were evident in the scattering data. These distinguishing features are valuable as signatures in nanosensors requiring fast, noninvasive response.
    Matched MeSH terms: Computer Simulation
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