Displaying publications 81 - 100 of 735 in total

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  1. Fulltext Adaptive Neuro-Fuzzy Determination of the Effect of Experimental Parameters on Vehicle Agent Speed Relative to Vehicle Intruder
    Shamshirband S, Banjanovic-Mehmedovic L, Bosankic I, Kasapovic S, Abdul Wahab AW
    PLoS One, 2016;11(5):e0155697.
    PMID: 27219539 DOI: 10.1371/journal.pone.0155697
    Intelligent Transportation Systems rely on understanding, predicting and affecting the interactions between vehicles. The goal of this paper is to choose a small subset from the larger set so that the resulting regression model is simple, yet have good predictive ability for Vehicle agent speed relative to Vehicle intruder. The method of ANFIS (adaptive neuro fuzzy inference system) was applied to the data resulting from these measurements. The ANFIS process for variable selection was implemented in order to detect the predominant variables affecting the prediction of agent speed relative to intruder. This process includes several ways to discover a subset of the total set of recorded parameters, showing good predictive capability. The ANFIS network was used to perform a variable search. Then, it was used to determine how 9 parameters (Intruder Front sensors active (boolean), Intruder Rear sensors active (boolean), Agent Front sensors active (boolean), Agent Rear sensors active (boolean), RSSI signal intensity/strength (integer), Elapsed time (in seconds), Distance between Agent and Intruder (m), Angle of Agent relative to Intruder (angle between vehicles °), Altitude difference between Agent and Intruder (m)) influence prediction of agent speed relative to intruder. The results indicated that distance between Vehicle agent and Vehicle intruder (m) and angle of Vehicle agent relative to Vehicle Intruder (angle between vehicles °) is the most influential parameters to Vehicle agent speed relative to Vehicle intruder.
    Matched MeSH terms: Models, Theoretical
  2. Fulltext Adaptive cuckoo search algorithm for unconstrained optimization
    Ong P
    ScientificWorldJournal, 2014;2014:943403.
    PMID: 25298971 DOI: 10.1155/2014/943403
    Modification of the intensification and diversification approaches in the recently developed cuckoo search algorithm (CSA) is performed. The alteration involves the implementation of adaptive step size adjustment strategy, and thus enabling faster convergence to the global optimal solutions. The feasibility of the proposed algorithm is validated against benchmark optimization functions, where the obtained results demonstrate a marked improvement over the standard CSA, in all the cases.
    Matched MeSH terms: Models, Theoretical*
  3. Fulltext Adaptive neuro-fuzzy methodology for noise assessment of wind turbine
    Shamshirband S, Petković D, Hashim R, Motamedi S
    PLoS One, 2014;9(7):e103414.
    PMID: 25075621 DOI: 10.1371/journal.pone.0103414
    Wind turbine noise is one of the major obstacles for the widespread use of wind energy. Noise tone can greatly increase the annoyance factor and the negative impact on human health. Noise annoyance caused by wind turbines has become an emerging problem in recent years, due to the rapid increase in number of wind turbines, triggered by sustainable energy goals set forward at the national and international level. Up to now, not all aspects of the generation, propagation and perception of wind turbine noise are well understood. For a modern large wind turbine, aerodynamic noise from the blades is generally considered to be the dominant noise source, provided that mechanical noise is adequately eliminated. The sources of aerodynamic noise can be divided into tonal noise, inflow turbulence noise, and airfoil self-noise. Many analytical and experimental acoustical studies performed the wind turbines. Since the wind turbine noise level analyzing by numerical methods or computational fluid dynamics (CFD) could be very challenging and time consuming, soft computing techniques are preferred. To estimate noise level of wind turbine, this paper constructed a process which simulates the wind turbine noise levels in regard to wind speed and sound frequency with adaptive neuro-fuzzy inference system (ANFIS). This intelligent estimator is implemented using Matlab/Simulink and the performances are investigated. The simulation results presented in this paper show the effectiveness of the developed method.
    Matched MeSH terms: Models, Theoretical*
  4. Adsorption and desorption of malachite green by using chitosan-deep eutectic solvents beads
    Sadiq AC, Rahim NY, Suah FBM
    Int J Biol Macromol, 2020 Dec 01;164:3965-3973.
    PMID: 32910963 DOI: 10.1016/j.ijbiomac.2020.09.029
    Chitosan-deep eutectic solvent (DES) beads were prepared from chitosan and DESs. The DESs used were choline chloride-urea (DES A) and choline chloride-glycerol (DES B). Both chitosan-DES beads were used to remove malachite green (MG) dye from an aqueous solution. The optimum pH for chitosan-DES A was recorded at pH 8.0 while optimum pH for chitosan-DES B was pH 9.0. The maximum adsorption capacity obtained for chitosan-DES A and chitosan-DES B were 6.54 mg/g and 8.64 mg/g, respectively. The optimum conditions for both chitosan-DES beads to remove MG were 0.08 g of adsorbent and 20 min of agitation time. Five kinetic models were applied to analyse the data and the results showed that the pseudo-second-order and intraparticle diffusion model fitted best with R2 > 0.999. For the adsorption capacity, results show that the Freundlich and Langmuir adsorption isotherms fitted well with chitosan-DES A and chitosan-DES B, respectively. The maximum adsorption capacities (qmax) obtained from chitosan-DES A and chitosan-DES B were 1.43 mg/g and 17.86 mg/g, respectively. Desorption indicated good performance in practical applications.
    Matched MeSH terms: Models, Theoretical
  5. Adsorption characterization of Pb(II) and Cu(II) ions onto chitosan-tripolyphosphate beads: Kinetic, equilibrium and thermodynamic studies
    Ngah WS, Fatinathan S
    J Environ Manage, 2010 Mar-Apr;91(4):958-69.
    PMID: 20044203 DOI: 10.1016/j.jenvman.2009.12.003
    Chitosan-tripolyphosphate (CTPP) beads were synthesized, characterized and were used for the adsorption of Pb(II) and Cu(II) ions from aqueous solution. The effects of initial pH, agitation period, adsorbent dosage, different initial concentrations of heavy metal ions and temperature were studied. The experimental data were correlated with the Langmuir, Freundlich and Dubinin-Radushkevich isotherm models. The maximum adsorption capacities of Pb(II) and Cu(II) ions in a single metal system based on the Langmuir isotherm model were 57.33 and 26.06 mg/g, respectively. However, the beads showed higher selectivity towards Cu(II) over Pb(II) ions in the binary metal system. Various thermodynamic parameters such as enthalpy (DeltaH degrees), Gibbs free energy (DeltaG degrees) and entropy (DeltaS degrees) changes were computed and the results showed that the adsorption of both heavy metal ions onto CTPP beads was spontaneous and endothermic in nature. The kinetic data were evaluated based on the pseudo-first and -second order kinetic and intraparticle diffusion models. Infrared spectra were used to elucidate the mechanism of Pb(II) and Cu(II) ions adsorption onto CTPP beads.
    Matched MeSH terms: Models, Theoretical
  6. Fulltext Advanced drug delivery systems can assist in targeting coronavirus disease (COVID-19): A hypothesis
    Mehta M, Prasher P, Sharma M, Shastri MD, Khurana N, Vyas M, et al.
    Med Hypotheses, 2020 Nov;144:110254.
    PMID: 33254559 DOI: 10.1016/j.mehy.2020.110254
    The highly contagious coronavirus, which had already affected more than 2 million people in 210 countries, triggered a colossal economic crisis consequently resulting from measures adopted by various goverments to limit transmission. This has placed the lives of many people infected worldwide at great risk. Currently there are no established or validated treatments for COVID-19, that is approved worldwide. Nanocarriers may offer a wide range of applications that could be developed into risk-free approaches for successful therapeutic strategies that may lead to immunisation against the severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) which is the primary causative organism that had led to the current COVID-19 pandemic. We address existing as well as emerging therapeutic and prophylactic approaches that may enable us to effectively combat this pandemic, and also may help to identify the key areas where nano-scientists can step in.
    Matched MeSH terms: Models, Theoretical
  7. Fulltext Advances and Future Perspectives in 4D Bioprinting
    Ashammakhi N, Ahadian S, Zengjie F, Suthiwanich K, Lorestani F, Orive G, et al.
    Biotechnol J, 2018 Dec;13(12):e1800148.
    PMID: 30221837 DOI: 10.1002/biot.201800148
    Three-dimensionally printed constructs are static and do not recapitulate the dynamic nature of tissues. Four-dimensional (4D) bioprinting has emerged to include conformational changes in printed structures in a predetermined fashion using stimuli-responsive biomaterials and/or cells. The ability to make such dynamic constructs would enable an individual to fabricate tissue structures that can undergo morphological changes. Furthermore, other fields (bioactuation, biorobotics, and biosensing) will benefit from developments in 4D bioprinting. Here, the authors discuss stimuli-responsive biomaterials as potential bioinks for 4D bioprinting. Natural cell forces can also be incorporated into 4D bioprinted structures. The authors introduce mathematical modeling to predict the transition and final state of 4D printed constructs. Different potential applications of 4D bioprinting are also described. Finally, the authors highlight future perspectives for this emerging technology in biomedicine.
    Matched MeSH terms: Models, Theoretical
  8. Fulltext Advances on bank erosion studies: a review
    Abdul-Kadir, M.A., Ariffin, J.
    ASM Science Journal, 2012;6(2):128-137.
    MyJurnal
    This paper reviews the advances made on studies related to bank erosion. Bank erosion has been an area of interest by researchers in geological, geotechnical, hydraulic, hydrology and river engineering disciplines. With anticipated global challenges from climate change impacts, bank erosion studies could support challenges faced in ensuring sustainable environmental management. The evolution in the theoretical and laboratory findings have led to the advances in bank erosion and contributed to new knowledge in the said field. This review summarises the findings of previous investigators including measurements approach and prediction of rates of bank erosion through the use of physical models and numerical approach.
    Matched MeSH terms: Models, Theoretical
  9. Fulltext Aedes larval population dynamics and risk for dengue epidemics in Malaysia
    Rohani A, Suzilah I, Malinda M, Anuar I, Mohd Mazlan I, Salmah Maszaitun M, et al.
    Trop Biomed, 2011 Aug;28(2):237-48.
    PMID: 22041742
    Early detection of a dengue outbreak is an important first step towards implementing effective dengue interventions resulting in reduced mortality and morbidity. A dengue mathematical model would be useful for the prediction of an outbreak and evaluation of control measures. However, such a model must be carefully parameterized and validated with epidemiological, ecological and entomological data. A field study was conducted to collect and analyse various parameters to model dengue transmission and outbreak. Dengue prone areas in Kuala Lumpur, Pahang, Kedah and Johor were chosen for this study. Ovitraps were placed outdoor and used to determine the effects of meteorological parameters on vector breeding. Vector population in each area was monitored weekly for 87 weeks. Weather stations, consisting of a temperature and relative humidity data logger and an automated rain gauge, were installed at key locations in each study site. Correlation and Autoregressive Distributed Lag (ADL) model were used to study the relationship among the variables. Previous week rainfall plays a significant role in increasing the mosquito population, followed by maximum humidity and temperature. The secondary data of rainfall, temperature and humidity provided by the meteorological department showed an insignificant relationship with the mosquito population compared to the primary data recorded by the researchers. A well fit model was obtained for each locality to be used as a predictive model to foretell possible outbreak.
    Matched MeSH terms: Models, Theoretical
  10. Age at marriage in Malaysia: a hazard model of marriage timing
    Anderson KH, Hill MA, Butler JS
    J Dev Econ, 1987 Aug;26(2):223-34.
    PMID: 12280709
    "This paper estimates a proportional hazards model for the timing of age at marriage of women in Malaysia. We hypothesize that age at marriage responds significantly to differences in male and female occupations, race, and age. We find considerable empirical support for the relevance of economic variables in determining age at marriage as well as evidence of strong differences in marriage patterns across races."
    Matched MeSH terms: Models, Theoretical*
  11. Allyl triphenyl phosphonium bromide based DES-functionalized carbon nanotubes for the removal of mercury from water
    AlOmar MK, Alsaadi MA, Hayyan M, Akib S, Ibrahim M, Hashim MA
    Chemosphere, 2017 Jan;167:44-52.
    PMID: 27710842 DOI: 10.1016/j.chemosphere.2016.09.133
    Recently, deep eutectic solvents (DESs) have shown their new and interesting ability for chemistry through their involvement in variety of applications. This study introduces carbon nanotubes (CNTs) functionalized with DES as a novel adsorbent for Hg(2+) from water. Allyl triphenyl phosphonium bromide (ATPB) was combined with glycerol as the hydrogen bond donor (HBD) to form DES, which can act as a novel CNTs functionalization agent. The novel adsorbent was characterized using Raman, FTIR, XRD, FESEM, EDX, BET surface area, TGA, TEM and Zeta potential. Response surface methodology was used to optimize the removal conditions for Hg(2+). The optimum removal conditions were found to be pH 5.5, contact time 28 min, and an adsorbent dosage of 5 mg. Freundlich isotherm model described the adsorption isotherm of the novel adsorbent, and the maximum adsorption capacity obtained from the experimental data was 186.97 mg g(-1). Pseudo-second order kinetics describes the adsorption rate order.
    Matched MeSH terms: Models, Theoretical
  12. Fulltext An Automated System for Skeletal Maturity Assessment by Extreme Learning Machines
    Mansourvar M, Shamshirband S, Raj RG, Gunalan R, Mazinani I
    PLoS One, 2015;10(9):e0138493.
    PMID: 26402795 DOI: 10.1371/journal.pone.0138493
    Assessing skeletal age is a subjective and tedious examination process. Hence, automated assessment methods have been developed to replace manual evaluation in medical applications. In this study, a new fully automated method based on content-based image retrieval and using extreme learning machines (ELM) is designed and adapted to assess skeletal maturity. The main novelty of this approach is it overcomes the segmentation problem as suffered by existing systems. The estimation results of ELM models are compared with those of genetic programming (GP) and artificial neural networks (ANNs) models. The experimental results signify improvement in assessment accuracy over GP and ANN, while generalization capability is possible with the ELM approach. Moreover, the results are indicated that the ELM model developed can be used confidently in further work on formulating novel models of skeletal age assessment strategies. According to the experimental results, the new presented method has the capacity to learn many hundreds of times faster than traditional learning methods and it has sufficient overall performance in many aspects. It has conclusively been found that applying ELM is particularly promising as an alternative method for evaluating skeletal age.
    Matched MeSH terms: Models, Theoretical*
  13. Fulltext An Eddy Current Testing Platform System for Pipe Defect Inspection Based on an Optimized Eddy Current Technique Probe Design
    Rifai D, Abdalla AN, Razali R, Ali K, Faraj MA
    Sensors (Basel), 2017 Mar 13;17(3).
    PMID: 28335399 DOI: 10.3390/s17030579
    The use of the eddy current technique (ECT) for the non-destructive testing of conducting materials has become increasingly important in the past few years. The use of the non-destructive ECT plays a key role in the ensuring the safety and integrity of the large industrial structures such as oil and gas pipelines. This paper introduce a novel ECT probe design integrated with the distributed ECT inspection system (DSECT) use for crack inspection on inner ferromagnetic pipes. The system consists of an array of giant magneto-resistive (GMR) sensors, a pneumatic system, a rotating magnetic field excitation source and a host PC acting as the data analysis center. Probe design parameters, namely probe diameter, an excitation coil and the number of GMR sensors in the array sensor is optimized using numerical optimization based on the desirability approach. The main benefits of DSECT can be seen in terms of its modularity and flexibility for the use of different types of magnetic transducers/sensors, and signals of a different nature with either digital or analog outputs, making it suited for the ECT probe design using an array of GMR magnetic sensors. A real-time application of the DSECT distributed system for ECT inspection can be exploited for the inspection of 70 mm carbon steel pipe. In order to predict the axial and circumference defect detection, a mathematical model is developed based on the technique known as response surface methodology (RSM). The inspection results of a carbon steel pipe sample with artificial defects indicate that the system design is highly efficient.
    Matched MeSH terms: Models, Theoretical
  14. Fulltext An Efficient Soft Set-Based Approach for Conflict Analysis
    Sutoyo E, Mungad M, Hamid S, Herawan T
    PLoS One, 2016;11(2):e0148837.
    PMID: 26928627 DOI: 10.1371/journal.pone.0148837
    Conflict analysis has been used as an important tool in economic, business, governmental and political dispute, games, management negotiations, military operations and etc. There are many mathematical formal models have been proposed to handle conflict situations and one of the most popular is rough set theory. With the ability to handle vagueness from the conflict data set, rough set theory has been successfully used. However, computational time is still an issue when determining the certainty, coverage, and strength of conflict situations. In this paper, we present an alternative approach to handle conflict situations, based on some ideas using soft set theory. The novelty of the proposed approach is that, unlike in rough set theory that uses decision rules, it is based on the concept of co-occurrence of parameters in soft set theory. We illustrate the proposed approach by means of a tutorial example of voting analysis in conflict situations. Furthermore, we elaborate the proposed approach on real world dataset of political conflict in Indonesian Parliament. We show that, the proposed approach achieves lower computational time as compared to rough set theory of up to 3.9%.
    Matched MeSH terms: Models, Theoretical
  15. An External Independent Validation of APACHE IV in a Malaysian Intensive Care Unit
    Wong RS, Ismail NA, Tan CC
    Ann Acad Med Singap, 2015 Apr;44(4):127-32.
    PMID: 26041636
    INTRODUCTION: Intensive care unit (ICU) prognostic models are predominantly used in more developed nations such as the United States, Europe and Australia. These are not that popular in Southeast Asian countries due to costs and technology considerations. The purpose of this study is to evaluate the suitability of the acute physiology and chronic health evaluation (APACHE) IV model in a single centre Malaysian ICU.

    MATERIALS AND METHODS: A prospective study was conducted at the single centre ICU in Hospital Sultanah Aminah (HSA) Malaysia. External validation of APACHE IV involved a cohort of 916 patients who were admitted in 2009. Model performance was assessed through its calibration and discrimination abilities. A first-level customisation using logistic regression approach was also applied to improve model calibration.

    RESULTS: APACHE IV exhibited good discrimination, with an area under receiver operating characteristic (ROC) curve of 0.78. However, the model's overall fit was observed to be poor, as indicated by the Hosmer-Lemeshow goodness-of-fit test (Ĉ = 113, P <0.001). Predicted in-ICU mortality rate (28.1%) was significantly higher than the actual in-ICU mortality rate (18.8%). Model calibration was improved after applying first-level customisation (Ĉ = 6.39, P = 0.78) although discrimination was not affected.

    CONCLUSION: APACHE IV is not suitable for application in HSA ICU, without further customisation. The model's lack of fit in the Malaysian study is attributed to differences in the baseline characteristics between HSA ICU and APACHE IV datasets. Other possible factors could be due to differences in clinical practice, quality and services of health care systems between Malaysia and the United States.

    Matched MeSH terms: Models, Theoretical*
  16. Fulltext An M/M/c/K State-Dependent Model for Pedestrian Flow Control and Design of Facilities
    Rahman K, Abdul Ghani N, Kamil AA, Mustafa A, Chowdhury MA
    PLoS One, 2015;10(7):e0133229.
    PMID: 26196124 DOI: 10.1371/journal.pone.0133229
    Pedestrian overflow causes queuing delay and in turn, is controlled by the capacity of a facility. Flow control or blocking control takes action to avoid queues from building up to extreme values. Thus, in this paper, the problem of pedestrian flow control in open outdoor walking facilities in equilibrium condition is investigated using M/M/c/K queuing models. State dependent service rate based on speed and density relationship is utilized. The effective rate of the Poisson arrival process to the facility is determined so as there is no overflow of pedestrians. In addition, the use of the state dependent queuing models to the design of the facilities and the effect of pedestrian personal capacity on the design and the traffic congestion are discussed. The study does not validate the sustainability of adaptation of Western design codes for the pedestrian facilities in the countries like Bangladesh.
    Matched MeSH terms: Models, Theoretical
  17. Fulltext An Overview of In Vitro, In Vivo, and Computational Techniques for Cancer-Associated Angiogenesis Studies
    Rahman HS, Tan BL, Othman HH, Chartrand MS, Pathak Y, Mohan S, et al.
    Biomed Res Int, 2020;2020:8857428.
    PMID: 33381591 DOI: 10.1155/2020/8857428
    Angiogenesis is a crucial area in scientific research because it involves many important physiological and pathological processes. Indeed, angiogenesis is critical for normal physiological processes, including wound healing and embryonic development, as well as being a component of many disorders, such as rheumatoid arthritis, obesity, and diabetic retinopathies. Investigations of angiogenic mechanisms require assays that can activate the critical steps of angiogenesis as well as provide a tool for assessing the efficacy of therapeutic agents. Thus, angiogenesis assays are key tools for studying the mechanisms of angiogenesis and identifying the potential therapeutic strategies to modulate neovascularization. However, the regulation of angiogenesis is highly complex and not fully understood. Difficulties in assessing the regulators of angiogenic response have necessitated the development of an alternative approach. In this paper, we review the standard models for the study of tumor angiogenesis on the macroscopic scale that include in vitro, in vivo, and computational models. We also highlight the differences in several modeling approaches and describe key advances in understanding the computational models that contributed to the knowledge base of the field.
    Matched MeSH terms: Models, Theoretical
  18. Fulltext An algorithmic framework for multiobjective optimization
    Ganesan T, Elamvazuthi I, Shaari KZ, Vasant P
    ScientificWorldJournal, 2013;2013:859701.
    PMID: 24470795 DOI: 10.1155/2013/859701
    Multiobjective (MO) optimization is an emerging field which is increasingly being encountered in many fields globally. Various metaheuristic techniques such as differential evolution (DE), genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) have been used in conjunction with scalarization techniques such as weighted sum approach and the normal-boundary intersection (NBI) method to solve MO problems. Nevertheless, many challenges still arise especially when dealing with problems with multiple objectives (especially in cases more than two). In addition, problems with extensive computational overhead emerge when dealing with hybrid algorithms. This paper discusses these issues by proposing an alternative framework that utilizes algorithmic concepts related to the problem structure for generating efficient and effective algorithms. This paper proposes a framework to generate new high-performance algorithms with minimal computational overhead for MO optimization.
    Matched MeSH terms: Models, Theoretical*
  19. Fulltext An alternate method to springback compensation for sheet metal forming
    Siswanto WA, Anggono AD, Omar B, Jusoff K
    ScientificWorldJournal, 2014;2014:301271.
    PMID: 25165738 DOI: 10.1155/2014/301271
    The aim of this work is to improve the accuracy of cold stamping product by accommodating springback. This is a numerical approach to improve the accuracy of springback analysis and die compensation process combining the displacement adjustment (DA) method and the spring forward (SF) algorithm. This alternate hybrid method (HM) is conducted by firstly employing DA method followed by the SF method instead of either DA or SF method individually. The springback shape and the target part are used to optimize the die surfaces compensating springback. The hybrid method (HM) algorithm has been coded in Fortran and tested in two- and three-dimensional models. By implementing the HM, the springback error can be decreased and the dimensional deviation falls in the predefined tolerance range.
    Matched MeSH terms: Models, Theoretical*
  20. Fulltext An analytical model to minimize the latency in healthcare internet-of-things in fog computing environment
    Shukla S, Hassan MF, Khan MK, Jung LT, Awang A
    PLoS One, 2019;14(11):e0224934.
    PMID: 31721807 DOI: 10.1371/journal.pone.0224934
    Fog computing (FC) is an evolving computing technology that operates in a distributed environment. FC aims to bring cloud computing features close to edge devices. The approach is expected to fulfill the minimum latency requirement for healthcare Internet-of-Things (IoT) devices. Healthcare IoT devices generate various volumes of healthcare data. This large volume of data results in high data traffic that causes network congestion and high latency. An increase in round-trip time delay owing to large data transmission and large hop counts between IoTs and cloud servers render healthcare data meaningless and inadequate for end-users. Time-sensitive healthcare applications require real-time data. Traditional cloud servers cannot fulfill the minimum latency demands of healthcare IoT devices and end-users. Therefore, communication latency, computation latency, and network latency must be reduced for IoT data transmission. FC affords the storage, processing, and analysis of data from cloud computing to a network edge to reduce high latency. A novel solution for the abovementioned problem is proposed herein. It includes an analytical model and a hybrid fuzzy-based reinforcement learning algorithm in an FC environment. The aim is to reduce high latency among healthcare IoTs, end-users, and cloud servers. The proposed intelligent FC analytical model and algorithm use a fuzzy inference system combined with reinforcement learning and neural network evolution strategies for data packet allocation and selection in an IoT-FC environment. The approach is tested on simulators iFogSim (Net-Beans) and Spyder (Python). The obtained results indicated the better performance of the proposed approach compared with existing methods.
    Matched MeSH terms: Models, Theoretical*
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