Displaying publications 441 - 460 of 761 in total

Abstract:
Sort:
  1. Fulltext Research on the mechanism of consumer participation in value co-creation by innovative enterprises: An evolutionary game analysis framework
    Liu Y
    PLoS One, 2024;19(5):e0297475.
    PMID: 38748693 DOI: 10.1371/journal.pone.0297475
    The profound changes brought about by informatization and digitalization have given rise to the user-centered innovation concept, and value co-creation by enterprises has become an inevitable trend. It has become a pressing issue for scholars to analyze the mechanism of consumer participation in the value co-creation of innovative enterprises. In this paper, by establishing an evolutionary game model between consumers and innovative enterprises, we analyze in depth the mechanism of consumer participation in the value co-creation of innovative enterprises. The results show that the initial cooperation probability between consumers and innovative enterprises directly affects their strategic choices; the establishment of reward mechanisms makes consumers more inclined to choose active participation in value co-creation strategies; as the probability of non-cooperation between the two parties being reported increases, the probability of consumers and innovative enterprises choosing cooperation also increases. Studying the mechanism of consumer participation in the value co-creation of innovative enterprises has essential theoretical and practical significance for enterprises to achieve value creation, enhance competitiveness, and promote innovation. This study not only enriches and develops relevant theories but also provides guidance and support for the practice of enterprises, promoting sustainable development and successful co-creation.
    Matched MeSH terms: Models, Theoretical
  2. 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
  3. Fulltext Heat and mass transfer on MHD squeezing flow of Jeffrey nanofluid in horizontal channel through permeable medium
    Mat Noor NA, Shafie S, Admon MA
    PLoS One, 2021;16(5):e0250402.
    PMID: 33956793 DOI: 10.1371/journal.pone.0250402
    The heat and mass transfer on time dependent hydrodynamic squeeze flow of Jeffrey nanofluid across two plates over permeable medium in the slip condition with heat generation/absorption, thermal radiation and chemical reaction are investigated. The impacts of Brownian motion and thermophoresis is examined in the Buongiorno's nanofluid model. Conversion of the governing partial differential equations to the ordinary differential equations is conducted via similarity transformation. The dimensionless equations are solved by imposing numerical method of Keller-box. The outputs are compared with previous reported works in the journals for the validation of the present outputs and found in proper agreement. The behavior of velocity, temperature, and nanoparticles concentration profiles by varying the pertinent parameters are examined. Findings portray that the acceleration of the velocity profile and the wall shear stress is due to the squeezing of plates. Furthermore, the velocity, temperature and concentration profile decline with boost in Hartmann number and ratio of relaxation to retardation times. It is discovered that the rate of heat transfer and temperature profile increase when viscous dissipation, thermophoresis and heat source/sink rises. In contrast, the increment of thermal radiation reduces the temperature and enhances the heat transfer rate. Besides, the mass transfer rate decelerates for increasing Brownian motion in nanofluid, while it elevates when chemical reaction and thermophoresis increases.
    Matched MeSH terms: Models, Theoretical
  4. Mapping pollution dynamics: utilizing GNOME to model oil spill trajectories in tanker terminals
    Farzingohar M, Bagheri M, Gholami I, Ibrahim ZZ, Akhir MF
    Environ Sci Pollut Res Int, 2024 May;31(25):37404-37427.
    PMID: 38777973 DOI: 10.1007/s11356-024-33506-4
    The aim of this study is to uncover the multifaceted environmental threats posed by Oil Spill Water Pollution (OSWP) originating from tanker terminals situated in the Qeshm and Hormozgan regions of Iran. In this region, water pollution arises from diverse sources, mostly from ruptured pipelines, corroded valves, unforeseen accidents, and aging facilities. The Qeshm Canal and Qeshm Tanker Terminal emerged as pivotal sites for investigation within this study. The focus is directed towards pinpointing vulnerable areas at risk of water contamination and delving into the intricate pathways and impacts associated with oil spills. Utilizing the sophisticated modeling capabilities of the National Oceanic and Atmospheric Administration's (NOAA) GNOME model, the research explores various scenarios extrapolated from seasonal atmospheric and oceanic data through 2022. The findings show the OSWP hazard zones located northeast of Qeshm. Notably, the wind and currents greatly affect how OSWPs are destined and dispersed. This underscores the intricate interplay between environmental factors and spill dynamics. In essence, this study not only sheds light on the imminent environmental threats posed by OSWP but also underscores the critical need for proactive measures and comprehensive strategies to mitigate the adverse impacts on marine ecosystems and coastal communities.
    Matched MeSH terms: Models, Theoretical
  5. Removal of Heavy Metals by Pseudomonas sp. - Model Fitting and Interpretation
    Zhang J, Noor ZZ, Baharuddin NH, Setu SA, Mohd Hamzah MAA, Zakaria ZA
    Curr Microbiol, 2024 Aug 19;81(10):312.
    PMID: 39155344 DOI: 10.1007/s00284-024-03832-4
    Industrial and urban modernization processes generate significant amounts of heavy metal wastewater, which brings great harm to human production and health. The biotechnology developed in recent years has gained increasing attention in the field of wastewater treatment due to its repeatable regeneration and lack of secondary pollutants. Pseudomonas, being among the several bacterial biosorbents, possesses notable benefits in the removal of heavy metals. These advantages encompass its extensive adsorption capacity, broad adaptability, capacity for biotransformation, potential for genetic engineering transformation, cost-effectiveness, and environmentally sustainable nature. The process of bacterial adsorption is a complex phenomenon involving several physical and chemical processes, including adsorption, ion exchange, and surface and contact phenomena. A comprehensive investigation of parameters is necessary in order to develop a mathematical model that effectively measures metal ion recovery and process performance. The aim of this study was to explore the latest advancements in high-tolerance Pseudomonas isolated from natural environments and evaluate its potential as a biological adsorbent. The study investigated the adsorption process of this bacterium, examining key factors such as strain type, contact time, initial metal concentration, and pH that influenced its effectiveness. By utilizing dynamic mathematical models, the research summarized the biosorption process, including adsorption kinetics, equilibrium, and thermodynamics. The findings indicated that Pseudomonas can effectively purify water contaminated with heavy metals and future research will aim to enhance its adsorption performance and expand its application scope for broader environmental purification purposes.
    Matched MeSH terms: Models, Theoretical
  6. Examining optimized machine learning models for accurate multi-month drought forecasting: A representative case study in the USA
    Hameed MM, Mohd Razali SF, Wan Mohtar WHM, Yaseen ZM
    Environ Sci Pollut Res Int, 2024 Aug;31(39):52060-52085.
    PMID: 39134798 DOI: 10.1007/s11356-024-34500-6
    The Colorado River has experienced a significant streamflow reduction in recent decades due to climate change, resulting in pronounced hydrological droughts that pose challenges to the environment and human activities. However, current models struggle to accurately capture complex drought patterns, and their accuracy decreases as the lead time increases. Thus, determining the reliability of drought forecasting for specific months ahead presents a challenging task. This study introduces a robust approach that utilizes the Beluga Whale Optimization (BWO) algorithm to train and optimize the parameters of the Regularized Extreme Learning Machine (RELM) and Random Forest (RF) models. The applied models are validated against a KNN benchmark model for forecasting drought from one- to six-month ahead across four hydrological stations distributed over the Colorado River. The achieved results demonstrate that RELM-BWO outperforms RF-BWO and KNN models, achieving the lowest root-mean square error (0.2795), uncertainty (U95 = 0.1077), mean absolute error (0.2104), and highest correlation coefficient (0.9135). Also, the current study uses Global Multi-Criteria Decision Analysis (GMCDA) as an evaluation metric to assess the reliability of the forecasting. The GMCDA results indicate that RELM-BWO provides reliable forecasts up to four months ahead. Overall, the research methodology is valuable for drought assessment and forecasting, enabling advanced early warning systems and effective drought countermeasures.
    Matched MeSH terms: Models, Theoretical
  7. Fulltext Multi-scenario land use change simulation and spatial-temporal evolution of carbon storage in the Yangtze River Delta region based on the PLUS-InVEST model
    Zhou J, Johnson VC, Shi J, Tan ML, Zhang F
    PLoS One, 2025;20(1):e0316255.
    PMID: 39854555 DOI: 10.1371/journal.pone.0316255
    Influenced by urban expansion, population growth, and various socio-economic activities, land use in the Yangtze River Delta (YRD) area has undergone prominent changes. Modifications in land use have resulted in adjustments to ecological structures, leading to subsequent fluctuations in carbon storage. This study focuses on YRD region and analyzes the characteristics of land use changes in the area using land use data from 2000 to 2020, with a 10-year interval. Utilizing InVEST Model's Carbon Storage module in combination with PLUS model (patch-generating land use simulation), we simulated and projected future land use patterns and carbon storage across YRD region under five scenarios including natural development (ND), urban development (UD), ecological protection (EP), cropland protection (CP), and balanced development (BD). Upon comparing carbon storage levels predicted for 2030 under the five scenarios with those in 2020, carbon stocks decrease in the initial four scenarios and then increase in the fifth scenario. In the initial four declining scenarios, CP scenario had the least reduction in carbon storage, followed by EP scenario. The implementation of policies aimed at safeguarding cropland and preserving ecological integrity can efficaciously curtail the expansion of developed land into woodland and cropland, enhance the structure of land use, and mitigate the loss of carbon storage.
    Matched MeSH terms: Models, Theoretical
  8. Fulltext The global convergence of some self-scaling conjugate gradient methods for monotone nonlinear equations with application to 3DOF arm robot model
    Ibrahim SM, Muhammad L, Yunus RB, Waziri MY, Kamaruddin SBA, Sambas A, et al.
    PLoS One, 2025;20(1):e0317318.
    PMID: 39854395 DOI: 10.1371/journal.pone.0317318
    Conjugate Gradient (CG) methods are widely used for solving large-scale nonlinear systems of equations arising in various real-life applications due to their efficiency in employing vector operations. However, the global convergence analysis of CG methods remains a significant challenge. In response, this study proposes scaled versions of CG parameters based on the renowned Barzilai-Borwein approach for solving convex-constrained monotone nonlinear equations. The proposed algorithms enforce a sufficient descent property independent of the accuracy of the line search procedure and ensure global convergence under appropriate assumptions. Numerical experiments demonstrate the efficiency of the proposed methods in solving large-scale nonlinear systems, including their applicability to accurately solving the inverse kinematic problem of a 3DOF robotic manipulator, where the objective is to minimize the error in achieving a desired trajectory configuration.
    Matched MeSH terms: Models, Theoretical
  9. A mathematical model for estimating the intraoperative lowest instrumented vertebra (LIV) tilt angle using preoperative supine left side-bending (LSB) radiographs in adolescent idiopathic scoliosis (AIS) patients with lenke type 1 and 2 non-AR curves
    Kwan MK, Lee SY, Fam SK, Tan YWE, Ngan CH, Chandirasegaran S, et al.
    Eur Spine J, 2025 Feb;34(2):610-624.
    PMID: 39738872 DOI: 10.1007/s00586-024-08602-1
    PURPOSE: To devise a mathematical model for estimating the intraoperative lowest instrumented vertebra (LIV) tilt angle using preoperative supine left side-bending (LSB) radiographs in adolescent idiopathic scoliosis (AIS) patients with Lenke type 1 and 2 (non-AR curves), and to review its clinical and radiological outcomes.

    METHODS: The mathematical model for the adjusted LSB LIV tilt angle (α) measured preoperatively, was expressed as the sum of preoperative LSB LIV tilt angle (x) and LIV displacement angle (y) (α = x + y). This model was validated through inter-rater and intra-rater analysis in Part I of the study. The α angle derived was applied to estimate the intraoperative LIV tilt angle. In part II of the study, clinical and radiological outcomes of 50 Lenke type 1 and 2 (non-AR curves) AIS patients operated using the α angle were reviewed. The difference between the intraoperative LIV tilt angle achieved (β) and the preoperative α angle was determined (∆LIV tilt angle = β-α).

    RESULTS: The α angle had excellent inter-rater and intra-rater intraclass correlation coefficients (0.982; 0.907). 42 patients had positive ∆LIV tilt angles whereas 8 patients had negative ∆LIV tilt angles. The overall incidence of distal adding-on (AO) was 10.0% (n = 5/50). Patients with negative ∆LIV tilt angles had a higher incidence of distal AO (n = 4/8, 50.0%) than patients with positive ∆LIV tilt angles (n = 1/42, 2.4%) (p = 0.001).

    CONCLUSION: Achieving an intraoperative LIV tilt angle (β) greater than or equal to the preoperative α angle derived (β ≥ α) may help avoid the distal AO phenomenon.

    Matched MeSH terms: Models, Theoretical
  10. Fulltext Suitability of Parkinson's patients for surgery in the north East coast of peninsular malaysia: a prospective analysis
    Abdullah J, Abdullah MR
    Malays J Med Sci, 2003 Jan;10(1):74-7.
    PMID: 23365504 MyJurnal
    There is no report in the English literature on the criteria for neuroablation or neuroaugmentation for the treatment of Parkinson's disease in a developing country like Malaysia. A prospective study of patients with Parkinson's disease from the north-eastern peninsular Malaysia was done to assess their suitability of surgery. Age, race, duration of illness and dementia were considered important factors towards the success of such surgical procedures. A mathematical model is suggested for future cases deemed to be suitable for neuroaugmentative or ablative surgery.
    Matched MeSH terms: Models, Theoretical
  11. Effective sample size estimation for a mechanical ventilation trial through Monte-Carlo simulation: Length of mechanical ventilation and Ventilator Free Days
    Morton SE, Chiew YS, Pretty C, Moltchanova E, Scarrott C, Redmond D, et al.
    Math Biosci, 2017 02;284:21-31.
    PMID: 27301378 DOI: 10.1016/j.mbs.2016.06.001
    Randomised control trials have sought to seek to improve mechanical ventilation treatment. However, few trials to date have shown clinical significance. It is hypothesised that aside from effective treatment, the outcome metrics and sample sizes of the trial also affect the significance, and thus impact trial design. In this study, a Monte-Carlo simulation method was developed and used to investigate several outcome metrics of ventilation treatment, including 1) length of mechanical ventilation (LoMV); 2) Ventilator Free Days (VFD); and 3) LoMV-28, a combination of the other metrics. As these metrics have highly skewed distributions, it also investigated the impact of imposing clinically relevant exclusion criteria on study power to enable better design for significance. Data from invasively ventilated patients from a single intensive care unit were used in this analysis to demonstrate the method. Use of LoMV as an outcome metric required 160 patients/arm to reach 80% power with a clinically expected intervention difference of 25% LoMV if clinically relevant exclusion criteria were applied to the cohort, but 400 patients/arm if they were not. However, only 130 patients/arm would be required for the same statistical significance at the same intervention difference if VFD was used. A Monte-Carlo simulation approach using local cohort data combined with objective patient selection criteria can yield better design of ventilation studies to desired power and significance, with fewer patients per arm than traditional trial design methods, which in turn reduces patient risk. Outcome metrics, such as VFD, should be used when a difference in mortality is also expected between the two cohorts. Finally, the non-parametric approach taken is readily generalisable to a range of trial types where outcome data is similarly skewed.
    Matched MeSH terms: Models, Theoretical*
  12. 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*
  13. Fulltext Development and validation of a risk model for predicting adverse drug reactions in older people during hospital stay: Brighton Adverse Drug Reactions Risk (BADRI) model
    Tangiisuran B, Scutt G, Stevenson J, Wright J, Onder G, Petrovic M, et al.
    PLoS One, 2014;9(10):e111254.
    PMID: 25356898 DOI: 10.1371/journal.pone.0111254
    Older patients are at an increased risk of developing adverse drug reactions (ADR). Of particular concern are the oldest old, which constitute an increasingly growing population. Having a validated clinical tool to identify those older patients at risk of developing an ADR during hospital stay would enable healthcare staff to put measures in place to reduce the risk of such an event developing. The current study aimed to (1) develop and (2) validate an ADR risk prediction model.
    Matched MeSH terms: Models, Theoretical*
  14. Fulltext Stochastic optimized relevance feedback particle swarm optimization for content based image retrieval
    Imran M, Hashim R, Noor Elaiza AK, Irtaza A
    ScientificWorldJournal, 2014;2014:752090.
    PMID: 25121136 DOI: 10.1155/2014/752090
    One of the major challenges for the CBIR is to bridge the gap between low level features and high level semantics according to the need of the user. To overcome this gap, relevance feedback (RF) coupled with support vector machine (SVM) has been applied successfully. However, when the feedback sample is small, the performance of the SVM based RF is often poor. To improve the performance of RF, this paper has proposed a new technique, namely, PSO-SVM-RF, which combines SVM based RF with particle swarm optimization (PSO). The aims of this proposed technique are to enhance the performance of SVM based RF and also to minimize the user interaction with the system by minimizing the RF number. The PSO-SVM-RF was tested on the coral photo gallery containing 10908 images. The results obtained from the experiments showed that the proposed PSO-SVM-RF achieved 100% accuracy in 8 feedback iterations for top 10 retrievals and 80% accuracy in 6 iterations for 100 top retrievals. This implies that with PSO-SVM-RF technique high accuracy rate is achieved at a small number of iterations.
    Matched MeSH terms: Models, Theoretical*
  15. Fulltext Analysis of glass-reinforced epoxy material for radio frequency resonator
    Zaman MR, Islam MT, Misran N, Yatim B
    ScientificWorldJournal, 2014;2014:831435.
    PMID: 24977230 DOI: 10.1155/2014/831435
    A radio frequency (RF) resonator using glass-reinforced epoxy material for C and X band is proposed in this paper. Microstrip line technology for RF over glass-reinforced epoxy material is analyzed. Coupling mechanism over RF material and parasitic coupling performance is explained utilizing even and odd mode impedance with relevant equivalent circuit. Babinet's principle is deployed to explicate the circular slot ground plane of the proposed resonator. The resonator is designed over four materials from different backgrounds which are glass-reinforced epoxy, polyester, gallium arsenide (GaAs), and rogers RO 4350B. Parametric studies and optimization algorithm are applied over the geometry of the microstrip resonator to achieve dual band response for C and X band. Resonator behaviors for different materials are concluded and compared for the same structure. The final design is fabricated over glass-reinforced epoxy material. The fabricated resonator shows a maximum directivity of 5.65 dBi and 6.62 dBi at 5.84 GHz and 8.16 GHz, respectively. The lowest resonance response is less than -20 dB for C band and -34 dB for X band. The resonator is prototyped using LPKF (S63) drilling machine to study the material behavior.
    Matched MeSH terms: Models, Theoretical*
  16. Fulltext Comparative study of popular objective functions for damping power system oscillations in multimachine system
    Islam NN, Hannan MA, Shareef H, Mohamed A, Salam MA
    ScientificWorldJournal, 2014;2014:549094.
    PMID: 24977210 DOI: 10.1155/2014/549094
    Power oscillation damping controller is designed in linearized model with heuristic optimization techniques. Selection of the objective function is very crucial for damping controller design by optimization algorithms. In this research, comparative analysis has been carried out to evaluate the effectiveness of popular objective functions used in power system oscillation damping. Two-stage lead-lag damping controller by means of power system stabilizers is optimized using differential search algorithm for different objective functions. Linearized model simulations are performed to compare the dominant mode's performance and then the nonlinear model is continued to evaluate the damping performance over power system oscillations. All the simulations are conducted in two-area four-machine power system to bring a detailed analysis. Investigated results proved that multiobjective D-shaped function is an effective objective function in terms of moving unstable and lightly damped electromechanical modes into stable region. Thus, D-shape function ultimately improves overall system damping and concurrently enhances power system reliability.
    Matched MeSH terms: Models, Theoretical*
  17. Fulltext Single-event-upset sensitivity analysis on low-swing drivers
    Mahyuddin NM, Russell G
    ScientificWorldJournal, 2014;2014:876435.
    PMID: 24782671 DOI: 10.1155/2014/876435
    Technology scaling relies on reduced nodal capacitances and lower voltages in order to improve performance and power consumption, resulting in significant increase in layout density, thus making these submicron technologies more susceptible to soft errors. Previous analysis indicates a significant improvement in SEU tolerance of the driver when the bias current is injected into the circuit but results in increase of power dissipation. Subsequently, other alternatives are considered. The impact of transistor sizes and temperature on SEU tolerance is tested. Results indicate no significant changes in Q(crit) when the effective transistor length is increased by 10%, but there is an improvement when high temperature and high bias currents are applied. However, this is due to other process parameters that are temperature dependent, which contribute to the sharp increase in Q(crit). It is found that, with temperature, there is no clear factor that can justify the direct impact of temperature on the SEU tolerance. Thus, in order to improve the SEU tolerance, high bias currents are still considered to be the most effective method in improving the SEU sensitivity. However, good trade-off is required for the low-swing driver in order to meet the reliability target with minimal power overhead.
    Matched MeSH terms: Models, Theoretical*
  18. Solid waste bin detection and classification using Dynamic Time Warping and MLP classifier
    Islam MS, Hannan MA, Basri H, Hussain A, Arebey M
    Waste Manag, 2014 Feb;34(2):281-90.
    PMID: 24238802 DOI: 10.1016/j.wasman.2013.10.030
    The increasing requirement for Solid Waste Management (SWM) has become a significant challenge for municipal authorities. A number of integrated systems and methods have introduced to overcome this challenge. Many researchers have aimed to develop an ideal SWM system, including approaches involving software-based routing, Geographic Information Systems (GIS), Radio-frequency Identification (RFID), or sensor intelligent bins. Image processing solutions for the Solid Waste (SW) collection have also been developed; however, during capturing the bin image, it is challenging to position the camera for getting a bin area centralized image. As yet, there is no ideal system which can correctly estimate the amount of SW. This paper briefly discusses an efficient image processing solution to overcome these problems. Dynamic Time Warping (DTW) was used for detecting and cropping the bin area and Gabor wavelet (GW) was introduced for feature extraction of the waste bin image. Image features were used to train the classifier. A Multi-Layer Perceptron (MLP) classifier was used to classify the waste bin level and estimate the amount of waste inside the bin. The area under the Receiver Operating Characteristic (ROC) curves was used to statistically evaluate classifier performance. The results of this developed system are comparable to previous image processing based system. The system demonstration using DTW with GW for feature extraction and an MLP classifier led to promising results with respect to the accuracy of waste level estimation (98.50%). The application can be used to optimize the routing of waste collection based on the estimated bin level.
    Matched MeSH terms: Models, Theoretical*
  19. A mathematical framework for minimally invasive tumor ablation therapies
    Hall SK, Ooi EH, Payne SJ
    Crit Rev Biomed Eng, 2014;42(5):383-417.
    PMID: 25745803
    Minimally invasive tumor ablations (MITAs) are an increasingly important tool in the treatment of solid tumors across multiple organs. The problems experienced in modeling different types of MITAs are very similar, but the development of mathematical models is mostly performed in isolation according to modality. Fundamental research into the modeling of specific types of MITAs is indeed required, but to choose the optimal treatment for an individual the primary clinical requirement is to have reliable predictions for a range of MITAs. In this review of the mathematical modeling of MITAs 4 modalities are considered: radiofrequency ablation, microwave ablation, cryoablation, and irreversible electroporation. The similarities in the mathematical modeling of these treatments are highlighted, and the analysis of the models within a general framework is discussed. This will aid in developing a deeper understanding of the sensitivity of MITA models to physiological parameters and the impact of uncertainty on predictions of the ablation zone. Through robust validation and analysis of the models it will be possible to choose the best model for a given application. This is important because many different models exist with no objective comparison of their performance. The collection of relevant in vivo experimental data is also critical to parameterize such models accurately. This approach will be necessary to translate the field into clinical practice.
    Matched MeSH terms: Models, Theoretical*
  20. Spatial effect of new municipal solid waste landfill siting using different guidelines
    Ahmad SZ, Ahamad MS, Yusoff MS
    Waste Manag Res, 2014 Jan;32(1):24-33.
    PMID: 24241167 DOI: 10.1177/0734242X13507313
    Proper implementation of landfill siting with the right regulations and constraints can prevent undesirable long-term effects. Different countries have respective guidelines on criteria for new landfill sites. In this article, we perform a comparative study of municipal solid waste landfill siting criteria stated in the policies and guidelines of eight different constitutional bodies from Malaysia, Australia, India, U.S.A., Europe, China and the Middle East, and the World Bank. Subsequently, a geographic information system (GIS) multi-criteria evaluation model was applied to determine new suitable landfill sites using different criterion parameters using a constraint mapping technique and weighted linear combination. Application of Macro Modeler provided in the GIS-IDRISI Andes software helps in building and executing multi-step models. In addition, the analytic hierarchy process technique was included to determine the criterion weight of the decision maker's preferences as part of the weighted linear combination procedure. The differences in spatial results of suitable sites obtained signifies that dissimilarity in guideline specifications and requirements will have an effect on the decision-making process.
    Matched MeSH terms: Models, Theoretical*
Related Terms
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links