Displaying publications 1 - 20 of 735 in total

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  1. Fulltext A 'combined framework' approach to developing a patient decision aid: the PANDAs model
    Ng CJ, Mathers N, Bradley A, Colwell B
    BMC Health Serv Res, 2014 Oct 24;14:503.
    PMID: 25341370 DOI: 10.1186/s12913-014-0503-7
    BACKGROUND: There is a lack of practical research frameworks to guide the development of patient decision aids [PtDAs]. This paper described how a PtDA was developed using the International Patient Decision Aids (IPDAS) guideline and UK Medical Research Council (UKMRC) frameworks to support patients when making treatment decisions in type 2 diabetes mellitus.

    METHODS: This study used mixed methods to develop a PtDA for use in a UK general practice setting. A 10-member expert panel was convened to guide development and patients and clinicians were also interviewed individually using semi-structured interview guides to identify their decisional needs. Current literature was reviewed systematically to determine the best available evidence. The Ottawa Decision Support Framework was used to guide the presentation of the information and value clarification exercise. An iterative draft-review-revise process by the research team and review panel was conducted until the PtDA reached content and format 'saturation'. The PtDA was then pilot-tested by users in actual consultations to assess its acceptability and feasibility. The IPDAS and UKMRC frameworks were used throughout to inform the development process.

    RESULTS: The PANDAs PtDA was developed systematically and iteratively. Patients and clinicians highlighted the needs for information, decisional, emotional and social support, which were incorporated into the PtDA. The literature review identified gaps in high quality evidence and variations in patient outcome reporting. The PtDA comprised five components: background of the treatment options; pros and cons of each treatment option; value clarification exercise; support needs; and readiness to decide.

    CONCLUSIONS: This study has demonstrated the feasibility of combining the IPDAS and the UKMRC frameworks for the development and evaluation of a PtDA. Future studies should test this model for developing PtDAs across different decisions and healthcare contexts.

    Matched MeSH terms: Models, Theoretical
  2. A Critical Review for Developing Accurate and Dynamic Predictive Models Using Machine Learning Methods in Medicine and Health Care
    Alanazi HO, Abdullah AH, Qureshi KN
    J Med Syst, 2017 Apr;41(4):69.
    PMID: 28285459 DOI: 10.1007/s10916-017-0715-6
    Recently, Artificial Intelligence (AI) has been used widely in medicine and health care sector. In machine learning, the classification or prediction is a major field of AI. Today, the study of existing predictive models based on machine learning methods is extremely active. Doctors need accurate predictions for the outcomes of their patients' diseases. In addition, for accurate predictions, timing is another significant factor that influences treatment decisions. In this paper, existing predictive models in medicine and health care have critically reviewed. Furthermore, the most famous machine learning methods have explained, and the confusion between a statistical approach and machine learning has clarified. A review of related literature reveals that the predictions of existing predictive models differ even when the same dataset is used. Therefore, existing predictive models are essential, and current methods must be improved.
    Matched MeSH terms: Models, Theoretical*
  3. A Filippov model describing the effects of media coverage and quarantine on the spread of human influenza
    Chen C, Chong NS, Smith R
    Math Biosci, 2018 02;296:98-112.
    PMID: 29273381 DOI: 10.1016/j.mbs.2017.12.002
    Mass-media reports on an epidemic or pandemic have the potential to modify human behaviour and affect social attitudes. Here we construct a Filippov model to evaluate the effects of media coverage and quarantine on the transmission dynamics of influenza. We first choose a piecewise smooth incidence rate to represent media reports being triggered once the number of infected individuals exceeds a certain critical level [Formula: see text] . Further, if the number of infected cases increases and exceeds another larger threshold value [Formula: see text] ( [Formula: see text] ), we consider that the incidence rate tends to a saturation level due to the protection measures taken by individuals; meanwhile, we begin to quarantine susceptible individuals when the number of susceptible individuals is larger than a threshold value Sc. Then, for each susceptible threshold value Sc, the global properties of the Filippov model with regard to the existence and stability of all possible equilibria and sliding-mode dynamics are examined, as we vary the infected threshold values [Formula: see text] and [Formula: see text] . We show generically that the Filippov system stabilizes at either the endemic equilibrium of the subsystem or the pseudoequilibrium on the switching surface or the endemic equilibrium [Formula: see text] depending on the choice of the threshold values. The findings suggest that proper combinations of infected and susceptible threshold values can maintain the number of infected individuals either below a certain threshold level or at a previously given level.
    Matched MeSH terms: Models, Theoretical*
  4. Fulltext A Global Analysis of the Relationship between Farmed Seaweed Production and Herbivorous Fish Catch
    Hehre EJ, Meeuwig JJ
    PLoS One, 2016;11(2):e0148250.
    PMID: 26894553 DOI: 10.1371/journal.pone.0148250
    Globally, farmed seaweed production is expanding rapidly in shallow marine habitats. While seaweed farming provides vital income to millions of artisanal farmers, it can negatively impact shallow coral reef and seagrass habitats. However, seaweed farming may also potentially provide food subsidies for herbivorous reef fish such as the Siganidae, a valuable target family, resulting in increased catch. Comparisons of reef fish landings across the central Philippines revealed that the catch of siganids was positively correlated to farmed seaweed production whilst negatively correlated to total reef fish catch over the same period of time. We tested the generality of this pattern by analysing seaweed production, siganid catch, and reef fish catch for six major seaweed-producing countries in the tropics. We hypothesized that increased seaweed production would correspond with increased catch of siganids but not other reef fish species. Analysis of the global data showed a positive correlation between farmed seaweeds and siganids in Southeast Asia (Indonesia, Malaysia, and the Philippines) but not Africa (Tanzania and Zanzibar), or the Western Pacific (Fiji). In Southeast Asia, siganid catch increased disproportionately faster with seaweed production than did reef fish catch. Low continuity, sporadic production and smaller volumes of seaweed farming may explain the differences.
    Matched MeSH terms: Models, Theoretical
  5. A Mathematical Model of the Tuberculosis Epidemic
    Ayinla AY, Othman WAM, Rabiu M
    Acta Biotheor, 2021 Sep;69(3):225-255.
    PMID: 33877474 DOI: 10.1007/s10441-020-09406-8
    Tuberculosis has continued to retain its title as "the captain among these men of death". This is evident as it is the leading cause of death globally from a single infectious agent. TB as it is fondly called has become a major threat to the achievement of the sustainable development goals (SDG) and hence require inputs from different research disciplines. This work presents a mathematical model of tuberculosis. A compartmental model of seven classes was used in the model formulation comprising of the susceptible S, vaccinated V, exposed E, undiagnosed infectious I1, diagnosed infectious I2, treated T and recovered R. The stability analysis of the model was established as well as the condition for the model to undergo backward bifurcation. With the existence of backward bifurcation, keeping the basic reproduction number less than unity [Formula: see text] is no more sufficient to keep TB out of the community. Hence, it is shown by the analysis that vaccination program, diagnosis and treatment helps to control the TB dynamics. In furtherance to that, it is shown that preference should be given to diagnosis over treatment as diagnosis precedes treatment. It is as well shown that at lower vaccination rate (0-20%), TB would still be endemic in the population. As such, high vaccination rate is required to send TB out of the community.
    Matched MeSH terms: Models, Theoretical
  6. Fulltext A Method for Quantifying, Visualising, and Analysing Gastropod Shell Form
    Liew TS, Schilthuizen M
    PLoS One, 2016;11(6):e0157069.
    PMID: 27280463 DOI: 10.1371/journal.pone.0157069
    Quantitative analysis of organismal form is an important component for almost every branch of biology. Although generally considered an easily-measurable structure, the quantification of gastropod shell form is still a challenge because many shells lack homologous structures and have a spiral form that is difficult to capture with linear measurements. In view of this, we adopt the idea of theoretical modelling of shell form, in which the shell form is the product of aperture ontogeny profiles in terms of aperture growth trajectory that is quantified as curvature and torsion, and of aperture form that is represented by size and shape. We develop a workflow for the analysis of shell forms based on the aperture ontogeny profile, starting from the procedure of data preparation (retopologising the shell model), via data acquisition (calculation of aperture growth trajectory, aperture form and ontogeny axis), and data presentation (qualitative comparison between shell forms) and ending with data analysis (quantitative comparison between shell forms). We evaluate our methods on representative shells of the genera Opisthostoma and Plectostoma, which exhibit great variability in shell form. The outcome suggests that our method is a robust, reproducible, and versatile approach for the analysis of shell form. Finally, we propose several potential applications of our methods in functional morphology, theoretical modelling, taxonomy, and evolutionary biology.
    Matched MeSH terms: Models, Theoretical*
  7. Fulltext A Negative Index Metamaterial-Inspired UWB Antenna with an Integration of Complementary SRR and CLS Unit Cells for Microwave Imaging Sensor Applications
    Islam MT, Islam MM, Samsuzzaman M, Faruque MR, Misran N
    Sensors (Basel), 2015 May 20;15(5):11601-27.
    PMID: 26007721 DOI: 10.3390/s150511601
    This paper presents a negative index metamaterial incorporated UWB antenna with an integration of complementary SRR (split-ring resonator) and CLS (capacitive loaded strip) unit cells for microwave imaging sensor applications. This metamaterial UWB antenna sensor consists of four unit cells along one axis, where each unit cell incorporates a complementary SRR and CLS pair. This integration enables a design layout that allows both a negative value of permittivity and a negative value of permeability simultaneous, resulting in a durable negative index to enhance the antenna sensor performance for microwave imaging sensor applications. The proposed MTM antenna sensor was designed and fabricated on an FR4 substrate having a thickness of 1.6 mm and a dielectric constant of 4.6. The electrical dimensions of this antenna sensor are 0.20 λ × 0.29 λ at a lower frequency of 3.1 GHz. This antenna sensor achieves a 131.5% bandwidth (VSWR < 2) covering the frequency bands from 3.1 GHz to more than 15 GHz with a maximum gain of 6.57 dBi. High fidelity factor and gain, smooth surface-current distribution and nearly omni-directional radiation patterns with low cross-polarization confirm that the proposed negative index UWB antenna is a promising entrant in the field of microwave imaging sensors.
    Matched MeSH terms: Models, Theoretical
  8. Fulltext A New Model of Alcoholic Fermentation under a Byproduct Inhibitory Effect
    Zentou H, Zainal Abidin Z, Yunus R, Awang Biak DR, Abdullah Issa M, Yahaya Pudza M
    ACS Omega, 2021 Feb 16;6(6):4137-4146.
    PMID: 33644536 DOI: 10.1021/acsomega.0c04025
    Despite the advantages of continuous fermentation whereby ethanol is selectively removed from the fermenting broth to reduce the end-product inhibition, this process can concentrate minor secondary products to the point where they become toxic to the yeast. This study aims to develop a new mathematical model do describe the inhibitory effect of byproducts on alcoholic fermentation including glycerol, lactic acid, acetic acid, and succinic acid, which were reported as major byproducts during batch alcoholic fermentation. The accumulation of these byproducts during the different stages of batch fermentation has been quantified. The yields of total byproducts, glycerol, acetic acid, and succinic acid per gram of glucose were 0.0442, 0.023, 0.0155, and 0.0054, respectively. It was found that the concentration of these byproducts linearly increases with the increase in glucose concentration in the range of 25-250 g/L. The results have also showed that byproduct concentration has a significant inhibitory effect on specific growth coefficient (μ) whereas no effect was observed on the half-velocity constant (Ks). A new mathematical model of alcoholic fermentation was developed considering the byproduct inhibitory effect, which showed a good performance and more accuracy compared to the classical Monod model.
    Matched MeSH terms: Models, Theoretical
  9. Fulltext A Novel RSSI Prediction Using Imperialist Competition Algorithm (ICA), Radial Basis Function (RBF) and Firefly Algorithm (FFA) in Wireless Networks
    Goudarzi S, Haslina Hassan W, Abdalla Hashim AH, Soleymani SA, Anisi MH, Zakaria OM
    PLoS One, 2016;11(7):e0151355.
    PMID: 27438600 DOI: 10.1371/journal.pone.0151355
    This study aims to design a vertical handover prediction method to minimize unnecessary handovers for a mobile node (MN) during the vertical handover process. This relies on a novel method for the prediction of a received signal strength indicator (RSSI) referred to as IRBF-FFA, which is designed by utilizing the imperialist competition algorithm (ICA) to train the radial basis function (RBF), and by hybridizing with the firefly algorithm (FFA) to predict the optimal solution. The prediction accuracy of the proposed IRBF-FFA model was validated by comparing it to support vector machines (SVMs) and multilayer perceptron (MLP) models. In order to assess the model's performance, we measured the coefficient of determination (R2), correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE). The achieved results indicate that the IRBF-FFA model provides more precise predictions compared to different ANNs, namely, support vector machines (SVMs) and multilayer perceptron (MLP). The performance of the proposed model is analyzed through simulated and real-time RSSI measurements. The results also suggest that the IRBF-FFA model can be applied as an efficient technique for the accurate prediction of vertical handover.
    Matched MeSH terms: Models, Theoretical
  10. Fulltext A Promising Polymer Blend Electrolytes Based on Chitosan: Methyl Cellulose for EDLC Application with High Specific Capacitance and Energy Density
    Aziz SB, Hamsan MH, Abdullah RM, Kadir MFZ
    Molecules, 2019 Jul 09;24(13).
    PMID: 31323966 DOI: 10.3390/molecules24132503
    In the present work, promising proton conducting solid polymer blend electrolytes (SPBEs) composed of chitosan (CS) and methylcellulose (MC) were prepared for electrochemical double-layer capacitor (EDLC) application with a high specific capacitance and energy density. The change in intensity and the broad nature of the XRD pattern of doped samples compared to pure CS:MC system evidencedthe amorphous character of the electrolyte samples. The morphology of the samples in FESEM images supported the amorphous behavior of the solid electrolyte films. The results of impedance and Bode plotindicate that the bulk resistance decreasedwith increasing salt concentration. The highest DC conductivity was found to be 2.81 × 10-3 S/cm. The electrical equivalent circuit (EEC) model was conducted for selected samples to explain the complete picture of the electrical properties.The performance of EDLC cells was examined at room temperature by electrochemical techniques, such as impedance spectroscopy, cyclic voltammetry (CV) and constant current charge-discharge techniques. It was found that the studied samples exhibit a very good performance as electrolyte for EDLC applications. Ions were found to be the dominant charge carriers in the polymer electrolyte. The ion transference number (tion) was found to be 0.84 while 0.16 for electron transference number (tel). Through investigation of linear sweep voltammetry (LSV), the CS:MC:NH4SCN system was found to be electrochemically stable up to 1.8 V. The CV plot revealed no redox peak, indicating the occurrence of charge double-layer at the surface of activated carbon electrodes. Specific capacitance (Cspe) for the fabricated EDLC was calculated using CV plot and charge-discharge analyses. It was found to be 66.3 F g-1 and 69.9 F g-1 (at thefirst cycle), respectively. Equivalent series resistance (Resr) of the EDLC was also identified, ranging from 50.0 to 150.0 Ω. Finally, energy density (Ed) was stabilized to anaverage of 8.63 Wh kg-1 from the 10th cycle to the 100th cycle. The first cycle obtained power density (Pd) of 1666.6 W kg-1 and then itdropped to 747.0 W kg-1 at the 50th cycle and continued to drop to 555.5 W kg-1 as the EDLC completed 100 cycles.
    Matched MeSH terms: Models, Theoretical
  11. Fulltext A ROM-less direct digital frequency synthesizer based on hybrid polynomial approximation
    Omran QK, Islam MT, Misran N, Faruque MR
    ScientificWorldJournal, 2014;2014:812576.
    PMID: 24892092 DOI: 10.1155/2014/812576
    In this paper, a novel design approach for a phase to sinusoid amplitude converter (PSAC) has been investigated. Two segments have been used to approximate the first sine quadrant. A first linear segment is used to fit the region near the zero point, while a second fourth-order parabolic segment is used to approximate the rest of the sine curve. The phase sample, where the polynomial changed, was chosen in such a way as to achieve the maximum spurious free dynamic range (SFDR). The invented direct digital frequency synthesizer (DDFS) has been encoded in VHDL and post simulation was carried out. The synthesized architecture exhibits a promising result of 90 dBc SFDR. The targeted structure is expected to show advantages for perceptible reduction of hardware resources and power consumption as well as high clock speeds.
    Matched MeSH terms: Models, Theoretical*
  12. Fulltext A Robust Speaker Identification System Using the Responses from a Model of the Auditory Periphery
    Islam MA, Jassim WA, Cheok NS, Zilany MS
    PLoS One, 2016;11(7):e0158520.
    PMID: 27392046 DOI: 10.1371/journal.pone.0158520
    Speaker identification under noisy conditions is one of the challenging topics in the field of speech processing applications. Motivated by the fact that the neural responses are robust against noise, this paper proposes a new speaker identification system using 2-D neurograms constructed from the responses of a physiologically-based computational model of the auditory periphery. The responses of auditory-nerve fibers for a wide range of characteristic frequency were simulated to speech signals to construct neurograms. The neurogram coefficients were trained using the well-known Gaussian mixture model-universal background model classification technique to generate an identity model for each speaker. In this study, three text-independent and one text-dependent speaker databases were employed to test the identification performance of the proposed method. Also, the robustness of the proposed method was investigated using speech signals distorted by three types of noise such as the white Gaussian, pink, and street noises with different signal-to-noise ratios. The identification results of the proposed neural-response-based method were compared to the performances of the traditional speaker identification methods using features such as the Mel-frequency cepstral coefficients, Gamma-tone frequency cepstral coefficients and frequency domain linear prediction. Although the classification accuracy achieved by the proposed method was comparable to the performance of those traditional techniques in quiet, the new feature was found to provide lower error rates of classification under noisy environments.
    Matched MeSH terms: Models, Theoretical*
  13. Fulltext A Theoretical Study of Surface Mode Propagation with a Guiding Layer of GaN/Sapphire Hetero-Structure in Liquid Medium
    Mohd Razip Wee MF, Jaafar MM, Faiz MS, Dee CF, Yeop Majlis B
    Biosensors (Basel), 2018 Dec 05;8(4).
    PMID: 30563159 DOI: 10.3390/bios8040124
    Gallium Nitride (GaN) is considered as the second most popular semiconductor material in industry after silicon. This is due to its wide applications encompassing Light Emitting Diode (LED) and power electronics. In addition, its piezoelectric properties are fascinating to be explored as electromechanical material for the development of diverse microelectromechanical systems (MEMS) application. In this article, we conducted a theoretical study concerning surface mode propagation, especially Rayleigh and Sezawa mode in the layered GaN/sapphire structure with the presence of various guiding layers. It is demonstrated that the increase in thickness of guiding layer will decrease the phase velocities of surface mode depending on the material properties of the layer. In addition, the Q-factor value indicating the resonance properties of surface mode appeared to be affected with the presence of fluid domain, particularly in the Rayleigh mode. Meanwhile, the peak for Sezawa mode shows the highest Q factor and is not altered by the presence of fluid. Based on these theoretical results using the finite element method, it could contribute to the development of a GaN-based device to generate surface acoustic wave, especially in Sezawa mode which could be useful in acoustophoresis, lab on-chip and microfluidics applications.
    Matched MeSH terms: Models, Theoretical
  14. Fulltext A Variable Sampling Interval Synthetic Xbar Chart for the Process Mean
    Lee LY, Khoo MB, Teh SY, Lee MH
    PLoS One, 2015;10(5):e0126331.
    PMID: 25951141 DOI: 10.1371/journal.pone.0126331
    The usual practice of using a control chart to monitor a process is to take samples from the process with fixed sampling interval (FSI). In this paper, a synthetic X control chart with the variable sampling interval (VSI) feature is proposed for monitoring changes in the process mean. The VSI synthetic X chart integrates the VSI X chart and the VSI conforming run length (CRL) chart. The proposed VSI synthetic X chart is evaluated using the average time to signal (ATS) criterion. The optimal charting parameters of the proposed chart are obtained by minimizing the out-of-control ATS for a desired shift. Comparisons between the VSI synthetic X chart and the existing X, synthetic X, VSI X and EWMA X charts, in terms of ATS, are made. The ATS results show that the VSI synthetic X chart outperforms the other X type charts for detecting moderate and large shifts. An illustrative example is also presented to explain the application of the VSI synthetic X chart.
    Matched MeSH terms: Models, Theoretical*
  15. Fulltext A behavior of reinforced vibrocompacted stone column in peat
    Prasad, Arun, Kazemian, Sina, Kalantari, Behzad, Bujang B.K. Huat
    Pertanika Journal of Science & Technology, 2012;20(2):221-241.
    MyJurnal
    In the literature, several methods of ground improvement have been presented including compacted stone columns. The bearing capacity of the granular column is governed mainly by the lateral confining pressure mobilized in the soft soil to restrain or prevent bulging of the granular column. Therefore, the technique becomes unfeasible in peat that does not provide sufficient lateral confinement. This condition can be overcome by encasing the stone column with geogrid. This paper investigates the performance of the geogrid encased vibrocompacted stone column in peat. This study was carried out using PLAXIS software equipped with unit cell concept. The peat was modelled using soft soil model and the stone column using Mohr-Coulomb soil model, respectively. The geogrid was modelled using the geogrid option and could take only tensile force. The results indicate that the geogrid encased stone column can take much higher load in comparison to ordinary stone columns as the stiffness of the column increases. Meanwhile, the length of encasement also varied and it was observed that it was very effective up to about two times the diameter of the column. It also increased the column stiffness, and therefore led to a significant strain reduction. It was also observed that the columns at a spacing of three times the diameter are very effective. The results presented here can be used by the geotechnical engineers to design the geogrid reinforced stone column based on the strength of the soil, diameter of the column, spacing of the columns and stiffness of the geogrid.
    Matched MeSH terms: Models, Theoretical
  16. A bicycle safety index for evaluating urban street facilities
    Asadi-Shekari Z, Moeinaddini M, Zaly Shah M
    Traffic Inj Prev, 2015;16:283-8.
    PMID: 24983474 DOI: 10.1080/15389588.2014.936010
    The objectives of this research are to conceptualize the Bicycle Safety Index (BSI) that considers all parts of the street and to propose a universal guideline with microscale details.
    Matched MeSH terms: Models, Theoretical
  17. A causal eco-industrial park hierarchical transition model with qualitative information: Policy and regulatory framework leads to collaboration among firms
    Tseng ML, Negash YT, Nagypál NC, Iranmanesh M, Tan RR
    J Environ Manage, 2021 Aug 15;292:112735.
    PMID: 33992872 DOI: 10.1016/j.jenvman.2021.112735
    Eco-industrial parks promise to reduce environmental and social impacts and improve the economic performance of industrial parks. However, the transition from industrial parks to eco-industrial parks is still not well understood. This study contributes to developing valid hierarchical eco-industrial park transition attribute sets with qualitative information, as prior studies lack an exploration of the attributes in the transition of eco-industrial parks in Hungary. In nature, eco-industrial park transition attributes have causal and hierarchical interrelationships and are described with qualitative information. The assessment involves an analysis of the industrial symbiosis principles by using linguistic preferences. However, multiple attributes are involved in the assessment; therefore, this study proposes the Delphi method to develop a valid attribute set and applies fuzzy set theory to translate qualitative information into crisp values. The fuzzy decision-making trial evaluation laboratory method is used to visualize the attributes' causal interrelationships under uncertainties. The results indicate that the policy and regulatory framework leads to collaboration among firms in the eco-industrial park transition model. In practice, price reforms, management commitment, strategic planning, cognitive barriers and the integration of external information are the practical criteria for improvement. Theoretical and practical implications are also discussed.
    Matched MeSH terms: Models, Theoretical
  18. A clonal selection algorithm model for daily rainfall data prediction
    Noor Rodi NS, Malek MA, Ismail AR, Ting SC, Tang CW
    Water Sci Technol, 2014;70(10):1641-7.
    PMID: 25429452 DOI: 10.2166/wst.2014.420
    This study applies the clonal selection algorithm (CSA) in an artificial immune system (AIS) as an alternative method to predicting future rainfall data. The stochastic and the artificial neural network techniques are commonly used in hydrology. However, in this study a novel technique for forecasting rainfall was established. Results from this study have proven that the theory of biological immune systems could be technically applied to time series data. Biological immune systems are nonlinear and chaotic in nature similar to the daily rainfall data. This study discovered that the proposed CSA was able to predict the daily rainfall data with an accuracy of 90% during the model training stage. In the testing stage, the results showed that an accuracy between the actual and the generated data was within the range of 75 to 92%. Thus, the CSA approach shows a new method in rainfall data prediction.
    Matched MeSH terms: Models, Theoretical*
  19. Fulltext A compact 5.5 GHz band-rejected UWB antenna using complementary split ring resonators
    Islam MM, Faruque MR, Islam MT
    ScientificWorldJournal, 2014;2014:528489.
    PMID: 24971379 DOI: 10.1155/2014/528489
    A band-removal property employing microwave frequencies using complementary split ring resonators (CSRRs) is applied to design a compact UWB antenna wishing for the rejection of some frequency band, which is meanwhile exercised by the existing wireless applications. The reported antenna comprises optimization of a circular radiating patch, in which slotted complementary SRRs are implanted. It is printed on low dielectric FR4 substrate material fed by a partial ground plane and a microstrip line. Validated results exhibit that the reported antenna shows a wide bandwidth covering from 3.45 to more than 12 GHz, with a compact dimension of 22 × 26 mm(2), and VSWR < 2, observing band elimination of 5.5 GHz WLAN band.
    Matched MeSH terms: Models, Theoretical*
  20. A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant
    Chun TS, Malek MA, Ismail AR
    Water Sci Technol, 2015;71(4):524-8.
    PMID: 25746643 DOI: 10.2166/wst.2014.451
    The development of effluent removal prediction is crucial in providing a planning tool necessary for the future development and the construction of a septic sludge treatment plant (SSTP), especially in the developing countries. In order to investigate the expected functionality of the required standard, the prediction of the effluent quality, namely biological oxygen demand, chemical oxygen demand and total suspended solid of an SSTP was modelled using an artificial intelligence approach. In this paper, we adopt the clonal selection algorithm (CSA) to set up a prediction model, with a well-established method - namely the least-square support vector machine (LS-SVM) as a baseline model. The test results of the case study showed that the prediction of the CSA-based SSTP model worked well and provided model performance as satisfactory as the LS-SVM model. The CSA approach shows that fewer control and training parameters are required for model simulation as compared with the LS-SVM approach. The ability of a CSA approach in resolving limited data samples, non-linear sample function and multidimensional pattern recognition makes it a powerful tool in modelling the prediction of effluent removals in an SSTP.
    Matched MeSH terms: Models, Theoretical*
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