Displaying publications 41 - 60 of 735 in total

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  1. A modelling study of the event-based retention performance of green roof under the hot-humid tropical climate in Kuching
    Chai CT, Putuhena FJ, Selaman OS
    Water Sci Technol, 2017 Dec;76(11-12):2988-2999.
    PMID: 29210686 DOI: 10.2166/wst.2017.472
    The influences of climate on the retention capability of green roof have been widely discussed in existing literature. However, knowledge on how the retention capability of green roof is affected by the tropical climate is limited. This paper highlights the retention performance of the green roof situated in Kuching under hot-humid tropical climatic conditions. Using the green roof water balance modelling approach, this study simulated the hourly runoff generated from a virtual green roof from November 2012 to October 2013 based on past meteorological data. The result showed that the overall retention performance was satisfactory with a mean retention rate of 72.5% from 380 analysed rainfall events but reduced to 12.0% only for the events that potentially trigger the occurrence of flash flood. By performing the Spearman rank's correlation analysis, it was found that the rainfall depth and mean rainfall intensity, individually, had a strong negative correlation with event retention rate, suggesting that the retention rate increases with decreased rainfall depth. The expected direct relationship between retention rate and antecedent dry weather period was found to be event size dependent.
    Matched MeSH terms: Models, Theoretical*
  2. Fulltext A multi-resolution textural approach to diagnostic neuropathology reporting
    Fauzi MF, Gokozan HN, Elder B, Puduvalli VK, Pierson CR, Otero JJ, et al.
    J Neurooncol, 2015 Sep;124(3):393-402.
    PMID: 26255070 DOI: 10.1007/s11060-015-1872-4
    We present a computer aided diagnostic workflow focusing on two diagnostic branch points in neuropathology (intraoperative consultation and p53 status in tumor biopsy specimens) by means of texture analysis via discrete wavelet frames decomposition. For intraoperative consultation, our methodology is capable of classifying glioblastoma versus metastatic cancer by extracting textural features from the non-nuclei region of cytologic preparations based on the imaging characteristics of glial processes, which appear as anisotropic thin linear structures. For metastasis, these are homogeneous in appearance, thus suitable and extractable texture features distinguish the two tissue types. Experiments on 53 images (29 glioblastomas and 24 metastases) resulted in average accuracy as high as 89.7 % for glioblastoma, 87.5 % for metastasis and 88.7 % overall. For p53 interpretation, we detect and classify p53 status by classifying staining intensity into strong, moderate, weak and negative sub-classes. We achieved this by developing a novel adaptive thresholding for detection, a two-step rule based on weighted color and intensity for the classification of positively and negatively stained nuclei, followed by texture classification to classify the positively stained nuclei into the strong, moderate and weak intensity sub-classes. Our detection method is able to correctly locate and distinguish the four types of cells, at 85 % average precision and 88 % average sensitivity rate. These classification methods on the other hand recorded 81 % accuracy in classifying the positive and negative cells, and 60 % accuracy in further classifying the positive cells into the three intensity groups, which is comparable with neuropathologists' markings.
    Matched MeSH terms: Models, Theoretical
  3. Fulltext A multiscale mathematical model describing the growth and development of bambara groundnut
    Dodd J, Sweby PK, Mayes S, Murchie EH, Karunaratne AS, Massawe F, et al.
    J Theor Biol, 2023 Mar 07;560:111373.
    PMID: 36509139 DOI: 10.1016/j.jtbi.2022.111373
    A principal objective in agriculture is to maximise food production; this is particularly relevant with the added demands of an ever increasing population, coupled with the unpredictability that climate change brings. Further improvements in productivity can only be achieved with an increased understanding of plant and crop processes. In this respect, mathematical modelling of plants and crops plays an important role. In this paper we present a two-scale mathematical model of crop yield that accounts for plant growth and canopy interactions. A system of nonlinear ordinary differential equations (ODEs) is formulated to describe the growth of each individual plant, where equations are coupled via a term that describes plant competition via canopy-canopy interactions. A crop of greenhouse plants is then modelled via an agent based modelling approach in which the growth of each plant is described via our system of ODEs. The model is formulated for the African drought tolerant legume bambara groundnut (Vigna subterranea), which is currently being investigated as a food source in light of climate change and food insecurity challenges. Our model allows us to account for plant diversity and also investigate the effect of individual plant traits (e.g. plant canopy size and planting distance) on the yield of the overall crop. Informed with greenhouse data, model results show that plant positioning relative to other plants has a large impact on individual plant yield. Variation in physiological plant traits from genetic diversity and the environmental effects lead to experimentally observed variations in crop yield. These traits include plant height, plant carrying capacity, leaf accumulation rate and canopy spread. Of these traits plant height and ground cover growth rates are found to have the greatest impact on crop yield. We also consider a range of different planting arrangements (uniform grid, staggered grid, circular rings and random allocation) and find that the staggered grid leads to the greatest crop yield (6% more compared to uniform grid). Whilst formulated specifically for bambara groundnut, the generic formulation of our model means that with changes to certain parameter's, it may be extended to other crop species that form a canopy.
    Matched MeSH terms: Models, Theoretical
  4. Fulltext A new SIR-based sigmoid power control game in cognitive radio networks
    Al-Gumaei YA, Noordin KA, Reza AW, Dimyati K
    PLoS One, 2014;9(10):e109077.
    PMID: 25286044 DOI: 10.1371/journal.pone.0109077
    Interference resulting from Cognitive Radios (CRs) is the most important aspect of cognitive radio networks that leads to degradation in Quality of Service (QoS) in both primary and CR systems. Power control is one of the efficient techniques that can be used to reduce interference and satisfy the Signal-to-Interference Ratio (SIR) constraint among CRs. This paper proposes a new distributed power control algorithm based on game theory approach in cognitive radio networks. The proposal focuses on the channel status of cognitive radio users to improve system performance. A new cost function for SIR-based power control via a sigmoid weighting factor is introduced. The existence of Nash Equilibrium and convergence of the algorithm are also proved. The advantage of the proposed algorithm is the possibility to utilize and implement it in a distributed manner. Simulation results show considerable savings on Nash Equilibrium power compared to relevant algorithms while reduction in achieved SIR is insignificant.
    Matched MeSH terms: Models, Theoretical*
  5. A new meta-heuristic optimization-based MPPT control technique for green energy harvesting from photovoltaic systems under different atmospheric conditions
    Kishore DJK, Mohamed MR, Sudhakar K, Peddakapu K
    Environ Sci Pollut Res Int, 2023 Jul;30(35):84167-84182.
    PMID: 37358770 DOI: 10.1007/s11356-023-28248-8
    At present, a photovoltaic (PV) system takes responsibility to reduce the risk of global warming and generate electricity. However, the PV system faces numerous problems to track global maximum peak power (GMPP) owing to the nonlinear nature of the environment especially due to partial shading conditions (PSC). To solve these difficulties, previous researchers have utilized various conventional methods for investigations. Nevertheless, these methods have oscillations around the GMPP. Hence, a new metaheuristic method such as an opposition-based equilibrium optimizer (OBEO) algorithm is used in this work for mitigating the oscillations around GMPP. To find the effectiveness of the proposed method, it can be evaluated with other methods such as SSA, GWO, and P&O. As per the simulation outcome, the proposed OBEO method provides maximum efficiency against all other methods. The efficiency for the proposed method under dynamic PSC is 95.09% in 0.16 s, similarly, 96.17% for uniform PSC and 86.25% for complex PSC.
    Matched MeSH terms: Models, Theoretical*
  6. Fulltext A new multiconstraint method for determining the optimal cable stresses in cable-stayed bridges
    Asgari B, Osman SA, Adnan A
    ScientificWorldJournal, 2014;2014:503016.
    PMID: 25050400 DOI: 10.1155/2014/503016
    Cable-stayed bridges are one of the most popular types of long-span bridges. The structural behaviour of cable-stayed bridges is sensitive to the load distribution between the girder, pylons, and cables. The determination of pretensioning cable stresses is critical in the cable-stayed bridge design procedure. By finding the optimum stresses in cables, the load and moment distribution of the bridge can be improved. In recent years, different research works have studied iterative and modern methods to find optimum stresses of cables. However, most of the proposed methods have limitations in optimising the structural performance of cable-stayed bridges. This paper presents a multiconstraint optimisation method to specify the optimum cable forces in cable-stayed bridges. The proposed optimisation method produces less bending moments and stresses in the bridge members and requires shorter simulation time than other proposed methods. The results of comparative study show that the proposed method is more successful in restricting the deck and pylon displacements and providing uniform deck moment distribution than unit load method (ULM). The final design of cable-stayed bridges can be optimised considerably through proposed multiconstraint optimisation method.
    Matched MeSH terms: Models, Theoretical*
  7. Fulltext A new trigonometric spline approach to numerical solution of generalized nonlinear Klien-Gordon equation
    Mat Zin S, Abbas M, Majid AA, Ismail AI
    PLoS One, 2014;9(5):e95774.
    PMID: 24796483 DOI: 10.1371/journal.pone.0095774
    The generalized nonlinear Klien-Gordon equation plays an important role in quantum mechanics. In this paper, a new three-time level implicit approach based on cubic trigonometric B-spline is presented for the approximate solution of this equation with Dirichlet boundary conditions. The usual finite difference approach is used to discretize the time derivative while cubic trigonometric B-spline is applied as an interpolating function in the space dimension. Several examples are discussed to exhibit the feasibility and capability of the approach. The absolute errors and L∞ error norms are also computed at different times to assess the performance of the proposed approach and the results were found to be in good agreement with known solutions and with existing schemes in literature.
    Matched MeSH terms: Models, Theoretical*
  8. Fulltext A newton cooperative genetic algorithm method for in silico optimization of metabolic pathway production
    Ismail MA, Deris S, Mohamad MS, Abdullah A
    PLoS One, 2015;10(5):e0126199.
    PMID: 25961295 DOI: 10.1371/journal.pone.0126199
    This paper presents an in silico optimization method of metabolic pathway production. The metabolic pathway can be represented by a mathematical model known as the generalized mass action model, which leads to a complex nonlinear equations system. The optimization process becomes difficult when steady state and the constraints of the components in the metabolic pathway are involved. To deal with this situation, this paper presents an in silico optimization method, namely the Newton Cooperative Genetic Algorithm (NCGA). The NCGA used Newton method in dealing with the metabolic pathway, and then integrated genetic algorithm and cooperative co-evolutionary algorithm. The proposed method was experimentally applied on the benchmark metabolic pathways, and the results showed that the NCGA achieved better results compared to the existing methods.
    Matched MeSH terms: Models, Theoretical
  9. 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: Models, Theoretical
  10. A novel agricultural waste adsorbent for the removal of lead (II) ions from aqueous solutions
    Ibrahim MN, Ngah WS, Norliyana MS, Daud WR, Rafatullah M, Sulaiman O, et al.
    J Hazard Mater, 2010 Oct 15;182(1-3):377-85.
    PMID: 20619537 DOI: 10.1016/j.jhazmat.2010.06.044
    The present study explores the ability of modified soda lignin (MSL) extracted from oil palm empty fruit bunches (EFB) in removing lead (II) ions from aqueous solutions. The effect of contact time, point zero charge (pH(pzc)) and pH of the solution, initial metal ion concentration and adsorbent dosage on the removal process were investigated. Furthermore, the MSL is characterized by SEM, XRF, FT-IR and surface area analysis. Equilibrium adsorption isotherms and kinetics were investigated. The experimental data were analyzed by the Langmuir, Freundlich and Temkin models of adsorption. The kinetic data obtained at different initial concentrations were analyzed using pseudo-first-order and pseudo-second-order models. The results provide strong evidence to support the hypothesis of adsorption mechanism.
    Matched MeSH terms: Models, Theoretical
  11. A novel antidoping and medical care delivery model at the 2nd Summer Youth Olympic Games (2014), Nanjing China
    Mountjoy M, Akef N, Budgett R, Greinig S, Li G, Manikavasagam J, et al.
    Br J Sports Med, 2015 Jul;49(13):887-92.
    PMID: 25833900 DOI: 10.1136/bjsports-2014-094424
    Antidoping and medical care delivery programmes are required at all large international multisport events.
    Matched MeSH terms: Models, Theoretical
  12. A novel approach to detect respiratory phases from pulmonary acoustic signals using normalised power spectral density and fuzzy inference system
    Palaniappan R, Sundaraj K, Sundaraj S, Huliraj N, Revadi SS
    Clin Respir J, 2016 Jul;10(4):486-94.
    PMID: 25515741 DOI: 10.1111/crj.12250
    BACKGROUND: Monitoring respiration is important in several medical applications. One such application is respiratory rate monitoring in patients with sleep apnoea. The respiratory rate in patients with sleep apnoea disorder is irregular compared with the controls. Respiratory phase detection is required for a proper monitoring of respiration in patients with sleep apnoea.

    AIMS: To develop a model to detect the respiratory phases present in the pulmonary acoustic signals and to evaluate the performance of the model in detecting the respiratory phases.

    METHODS: Normalised averaged power spectral density for each frame and change in normalised averaged power spectral density between the adjacent frames were fuzzified and fuzzy rules were formulated. The fuzzy inference system (FIS) was developed with both Mamdani and Sugeno methods. To evaluate the performance of both Mamdani and Sugeno methods, correlation coefficient and root mean square error (RMSE) were calculated.

    RESULTS: In the correlation coefficient analysis in evaluating the fuzzy model using Mamdani and Sugeno method, the strength of the correlation was found to be r = 0.9892 and r = 0.9964, respectively. The RMSE for Mamdani and Sugeno methods are RMSE = 0.0853 and RMSE = 0.0817, respectively.

    CONCLUSION: The correlation coefficient and the RMSE of the proposed fuzzy models in detecting the respiratory phases reveals that Sugeno method performs better compared with the Mamdani method.

    Matched MeSH terms: Models, Theoretical
  13. Fulltext A novel approach toward fuzzy generalized bi-ideals in ordered semigroups
    Khan FM, Sarmin NH, Khan HU
    ScientificWorldJournal, 2014;2014:275947.
    PMID: 24883375 DOI: 10.1155/2014/275947
    In several advanced fields like control engineering, computer science, fuzzy automata, finite state machine, and error correcting codes, the use of fuzzified algebraic structures especially ordered semigroups plays a central role. In this paper, we introduced a new and advanced generalization of fuzzy generalized bi-ideals of ordered semigroups. These new concepts are supported by suitable examples. These new notions are the generalizations of ordinary fuzzy generalized bi-ideals of ordered semigroups. Several fundamental theorems of ordered semigroups are investigated by the properties of these newly defined fuzzy generalized bi-ideals. Further, using level sets, ordinary fuzzy generalized bi-ideals are linked with these newly defined ideals which is the most significant part of this paper.
    Matched MeSH terms: Models, Theoretical
  14. Fulltext A novel clustering algorithm for mobile ad hoc networks based on determination of virtual links' weight to increase network stability
    Karimi A, Afsharfarnia A, Zarafshan F, Al-Haddad SA
    ScientificWorldJournal, 2014;2014:432952.
    PMID: 25114965 DOI: 10.1155/2014/432952
    The stability of clusters is a serious issue in mobile ad hoc networks. Low stability of clusters may lead to rapid failure of clusters, high energy consumption for reclustering, and decrease in the overall network stability in mobile ad hoc network. In order to improve the stability of clusters, weight-based clustering algorithms are utilized. However, these algorithms only use limited features of the nodes. Thus, they decrease the weight accuracy in determining node's competency and lead to incorrect selection of cluster heads. A new weight-based algorithm presented in this paper not only determines node's weight using its own features, but also considers the direct effect of feature of adjacent nodes. It determines the weight of virtual links between nodes and the effect of the weights on determining node's final weight. By using this strategy, the highest weight is assigned to the best choices for being the cluster heads and the accuracy of nodes selection increases. The performance of new algorithm is analyzed by using computer simulation. The results show that produced clusters have longer lifetime and higher stability. Mathematical simulation shows that this algorithm has high availability in case of failure.
    Matched MeSH terms: Models, Theoretical
  15. A novel collocation method based on residual error analysis for solving integro-differential equations using hybrid dickson and taylor polynomials
    Kürkçü ÖK, Aslan E, Sezer M
    Sains Malaysiana, 2017;46:335-347.
    In this study, a novel matrix method based on collocation points is proposed to solve some linear and nonlinear integro-differential equations with variable coefficients under the mixed conditions. The solutions are obtained by means of Dickson and Taylor polynomials. The presented method transforms the equation and its conditions into matrix equations which comply with a system of linear algebraic equations with unknown Dickson coefficients, via collocation points in a finite interval. While solving the matrix equation, the Dickson coefficients and the polynomial approximation are obtained. Besides, the residual error analysis for our method is presented and illustrative examples are given to demonstrate the validity and applicability of the method.
    Matched MeSH terms: Models, Theoretical
  16. Fulltext A novel design, analysis and 3D printing of Ti-6Al-4V alloy bio-inspired porous femoral stem
    Mehboob H, Tarlochan F, Mehboob A, Chang SH, Ramesh S, Harun WSW, et al.
    J Mater Sci Mater Med, 2020 Aug 20;31(9):78.
    PMID: 32816091 DOI: 10.1007/s10856-020-06420-7
    The current study is proposing a design envelope for porous Ti-6Al-4V alloy femoral stems to survive under fatigue loads. Numerical computational analysis of these stems with a body-centered-cube (BCC) structure is conducted in ABAQUS. Femoral stems without shell and with various outer dense shell thicknesses (0.5, 1.0, 1.5, and 2 mm) and inner cores (porosities of 90, 77, 63, 47, 30, and 18%) are analyzed. A design space (envelope) is derived by using stem stiffnesses close to that of the femur bone, maximum fatigue stresses of 0.3σys in the porous part, and endurance limits of the dense part of the stems. The Soderberg approach is successfully employed to compute the factor of safety Nf > 1.1. Fully porous stems without dense shells are concluded to fail under fatigue load. It is thus safe to use the porous stems with a shell thickness of 1.5 and 2 mm for all porosities (18-90%), 1 mm shell with 18 and 30% porosities, and 0.5 mm shell with 18% porosity. The reduction in stress shielding was achieved by 28%. Porous stems incorporated BCC structures with dense shells and beads were successfully printed.
    Matched MeSH terms: Models, Theoretical*
  17. Fulltext A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network
    Salari N, Shohaimi S, Najafi F, Nallappan M, Karishnarajah I
    PLoS One, 2014;9(11):e112987.
    PMID: 25419659 DOI: 10.1371/journal.pone.0112987
    Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. In the present study, the results of the implementation of a novel hybrid feature selection-classification model using the above mentioned methods are presented. The purpose is benefitting from the synergies obtained from combining these technologies for the development of classification models. Such a combination creates an opportunity to invest in the strength of each algorithm, and is an approach to make up for their deficiencies. To develop proposed model, with the aim of obtaining the best array of features, first, feature ranking techniques such as the Fisher's discriminant ratio and class separability criteria were used to prioritize features. Second, the obtained results that included arrays of the top-ranked features were used as the initial population of a genetic algorithm to produce optimum arrays of features. Third, using a modified k-Nearest Neighbor method as well as an improved method of backpropagation neural networks, the classification process was advanced based on optimum arrays of the features selected by genetic algorithms. The performance of the proposed model was compared with thirteen well-known classification models based on seven datasets. Furthermore, the statistical analysis was performed using the Friedman test followed by post-hoc tests. The experimental findings indicated that the novel proposed hybrid model resulted in significantly better classification performance compared with all 13 classification methods. Finally, the performance results of the proposed model was benchmarked against the best ones reported as the state-of-the-art classifiers in terms of classification accuracy for the same data sets. The substantial findings of the comprehensive comparative study revealed that performance of the proposed model in terms of classification accuracy is desirable, promising, and competitive to the existing state-of-the-art classification models.
    Matched MeSH terms: Models, Theoretical*
  18. A novel mechanism measurement of predator interference in predator-prey models
    Alebraheem J, Abu-Hassan Y
    J Math Biol, 2023 Apr 27;86(5):84.
    PMID: 37103566 DOI: 10.1007/s00285-023-01914-8
    A characteristic of ecosystems is the existence of manifold of independencies which are highly complex. Various mathematical models have made considerable contributions in gaining a better understanding of the predator-prey interactions. The main components of any predator-prey models are, firstly, how the different population classes grow and secondly, how the prey and predator interacts. In this paper, the two populations' growth rates obey the logistic law and the carrying capacity of the predator depends on the available number of prey are considered. Our aim is to clarify the relationship between models and Holling types functional and numerical responses in order to gain insights into predator interferences and to answer an important question how competition is carried out. We consider a predator-prey model and a two-predator one-prey model to explain the idea. The novel approach is explained for the mechanism measurement of predator interference through depending on numerical response. Our approach gives good correspondence between an important real data and computer simulations.
    Matched MeSH terms: Models, Theoretical
  19. Fulltext A novel method for multifactorial bio-chemical experiments design based on combinational design theory
    Wang X, Sun B, Liu B, Fu Y, Zheng P
    PLoS One, 2017;12(11):e0186853.
    PMID: 29095845 DOI: 10.1371/journal.pone.0186853
    Experimental design focuses on describing or explaining the multifactorial interactions that are hypothesized to reflect the variation. The design introduces conditions that may directly affect the variation, where particular conditions are purposely selected for observation. Combinatorial design theory deals with the existence, construction and properties of systems of finite sets whose arrangements satisfy generalized concepts of balance and/or symmetry. In this work, borrowing the concept of "balance" in combinatorial design theory, a novel method for multifactorial bio-chemical experiments design is proposed, where balanced templates in combinational design are used to select the conditions for observation. Balanced experimental data that covers all the influencing factors of experiments can be obtianed for further processing, such as training set for machine learning models. Finally, a software based on the proposed method is developed for designing experiments with covering influencing factors a certain number of times.
    Matched MeSH terms: Models, Theoretical*
  20. Fulltext A novel vehicle stationary detection utilizing map matching and IMU sensors
    Amin MS, Reaz MB, Nasir SS, Bhuiyan MA, Ali MA
    ScientificWorldJournal, 2014;2014:597180.
    PMID: 25276855 DOI: 10.1155/2014/597180
    Precise navigation is a vital need for many modern vehicular applications. The global positioning system (GPS) cannot provide continuous navigation information in urban areas. The widely used inertial navigation system (INS) can provide full vehicle state at high rates. However, the accuracy diverges quickly in low cost microelectromechanical systems (MEMS) based INS due to bias, drift, noise, and other errors. These errors can be corrected in a stationary state. But detecting stationary state is a challenging task. A novel stationary state detection technique from the variation of acceleration, heading, and pitch and roll of an attitude heading reference system (AHRS) built from the inertial measurement unit (IMU) sensors is proposed. Besides, the map matching (MM) algorithm detects the intersections where the vehicle is likely to stop. Combining these two results, the stationary state is detected with a smaller timing window of 3 s. A longer timing window of 5 s is used when the stationary state is detected only from the AHRS. The experimental results show that the stationary state is correctly identified and the position error is reduced to 90% and outperforms previously reported work. The proposed algorithm would help to reduce INS errors and enhance the performance of the navigation system.
    Matched MeSH terms: Models, Theoretical
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