摘要 :
Nowadays, being in digital era the data generated by various applicationsare increasing drastically both row-wise and column wise; this creates a bottleneckfor analytics and also increases the burden of machine learning algorithms...
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Nowadays, being in digital era the data generated by various applicationsare increasing drastically both row-wise and column wise; this creates a bottleneckfor analytics and also increases the burden of machine learning algorithms that workfor pattern recognition. This cause of dimensionality can be handled throughreduction techniques. The Dimensionality Reduction (DR) can be handled in twoways namely Feature Selection (FS) and Feature Extraction (FE). This paper focuseson a survey of feature selection methods, from this extensive survey we can concludethat most of the FS methods use static data. However, after the emergence of IoT andweb-based applications, the data are generated dynamically and grow in a fast rate,so it is likely to have noisy data, it also hinders the performance of the algorithm.With the increase in the size of the data set, the scalability of the FS methods becomesjeopardized. So the existing DR algorithms do not address the issues with the dynamicdata. Using FS methods not only reduces the burden of the data but also avoidsoverfitting of the model.
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摘要 :
Nowadays, being in digital era the data generated by various applications are increasing drastically both row-wise and column wise; this creates a bottleneck for analytics and also increases the burden of machine learning algorith...
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Nowadays, being in digital era the data generated by various applications are increasing drastically both row-wise and column wise; this creates a bottleneck for analytics and also increases the burden of machine learning algorithms that work for pattern recognition. This cause of dimensionality can be handled through reduction techniques. The Dimensionality Reduction (DR) can be handled in two ways namely Feature Selection (FS) and Feature Extraction (FE). This paper focuses on a survey of feature selection methods, from this extensive survey we can conclude that most of the FS methods use static data. However, after the emergence of IoT and web-based applications, the data are generated dynamically and grow in a fast rate, so it is likely to have noisy data, it also hinders the performance of the algorithm. With the increase in the size of the data set, the scalability of the FS methods becomes jeopardized. So the existing DR algorithms do not address the issues with the dynamic data. Using FS methods not only reduces the burden of the data but also avoids overfitting of the model.
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This study mathematically examines chemical and biomaterial models by employing the finite element method. Unshaped biomaterials’ complex structures have been numerically analyzed using Gaussian quadrature rules. It has been anal...
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This study mathematically examines chemical and biomaterial models by employing the finite element method. Unshaped biomaterials’ complex structures have been numerically analyzed using Gaussian quadrature rules. It has been analyzed for commercial benefits of chemical engineering and biomaterials as well as biorefinery fields. For the computational work, the ellipsoid has been taken as a model, and it has been transformed by subdividing it into six tetrahedral elements with one curved face. Each curved tetrahedral element is considered a quadratic and cubic tetrahedral element and transformed into standard tetrahedral elements with straight faces. Each standard tetrahedral element is further decomposed into four hexahedral elements. Numerical tests are presented that verify the derived transformations and the quadrature rules. Convergence studies are performed for the integration of rational, weakly singular, and trigonometric test functions over an ellipsoid by using Gaussian quadrature rules and compared with the generalized Gaussian quadrature rules. The new transformations are derived to compute numerical integration over curved tetrahedral elements for all tests, and it has been observed that the integral outcomes converge to accurate values with lower computation duration.
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Purpose - A finite element computational methodology on a curved boundary using an efficient subparametric point transformation is presented. The proposed collocation method uses one-side curved and two-side straight triangular el...
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Purpose - A finite element computational methodology on a curved boundary using an efficient subparametric point transformation is presented. The proposed collocation method uses one-side curved and two-side straight triangular elements to derive exact subparametric shape functions. Design/methodology/approach - Our proposed method builds upon the domain discretization into linear, quadratic and cubic-order elements using subparametric spaces and such a discretization greatly reduces the computational complexity. A unique subparametric transformation for each triangle is derived from the unique parabolic arcs via a one-of-a-kind relationship between the nodal points. Findings - The novel transformation derived in this paper is shown to increase the accuracy of the finite element approximation of the boundary value problem (BVP). Our overall strategy is shown to perform well for the BVP considered in this work. The accuracy of the finite element approximate solution increases with higher-order parabolic arcs. Originality/value - The proposed collocation method uses one-side curved and two-side straight triangular elements to derive exact subparametric shape functions.
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Double-pipe counter-flow heat exchangers are considered more suitable for heat recovery in the heat transfer industry. Numerous studies have been conducted to develop static tools for optimizing operating parameters of heat exchan...
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Double-pipe counter-flow heat exchangers are considered more suitable for heat recovery in the heat transfer industry. Numerous studies have been conducted to develop static tools for optimizing operating parameters of heat exchangers. Using this study, an improved heat exchanger system will be developed. This is frequently used to solve optimization problems and find optimal solutions. The Taguchi method determines the critical factor affecting a specific performance parameter of the heat exchanger by identifying the significant level of the factor affecting that parameter. Gray relational analysis was adopted to determine the gray relational grade to represent the multi-factor optimization model, and the heat exchanger gray relation coefficient target values that were predicted have been achieved using ANN with a back propagation model with the Levenberg-Marquardt drive algorithm. The genetic algorithm improved the accuracy of the gray relational grade by assigning gray relational coefficient values as input to the developed effective parameter. This study also demonstrated significant differences between experimental and estimated values. According to the results, selecting the parameters yielded optimal heat exchanger performance. Using a genetic algorithm to solve a double-pipe heat exchanger with counterflow can produce the most efficient heat exchanger.
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This paper describes the development and implementation of a wind turbine emulator (WTE), based on a d.c. motor, using LabVIEW. The emulator imitates both static and dynamic characteristics of a typical wind turbine (WT) of a wind...
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This paper describes the development and implementation of a wind turbine emulator (WTE), based on a d.c. motor, using LabVIEW. The emulator imitates both static and dynamic characteristics of a typical wind turbine (WT) of a wind energy conversion system (WECS). The setup can be used for development and testing of real-time control algorithms. The laboratory setup consists of a d.c. motor coupled to a three-phase self-excited induction generator (SEIG). The mathematical model of WT, designed in LabVIEW, is interfaced with the d.c. motor control circuit by the compact real-time I/O module (cRIO). The armature current is regulated by armature voltage control with appropriate switching signals for a power MOSFET-based control circuit. The simulation and experimental results under different scenarios prove the effectiveness of this LabVIEW-based WTE. This WTE can be effectively used as a laboratory-based teaching tool for electrical engineering students. The learning objective of this simple yet efficient laboratory setup is to study the WT characteristics in the absence of a real WT. A manual and a list of questions have been prepared related to the experiment and have been used at the Indian Institute of Technology Kharagpur (India). The learning performances of the students have been evaluated based on a questionnaire.
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In this work, medicinal plant alfalfa leaf extract was used as an antihemorrhagic, antimicrobial,
and antifungal agent and applied to cotton fabrics. The medicinal herb alfalfa leaf was
extracted using the ethanol and methanol s...
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In this work, medicinal plant alfalfa leaf extract was used as an antihemorrhagic, antimicrobial,
and antifungal agent and applied to cotton fabrics. The medicinal herb alfalfa leaf was
extracted using the ethanol and methanol solvents in the Soxhlet apparatus. The 50-μL,
100-μL, and 150-μL concentrations of extracted solution were tested against the positive and
negative bacteria, namely Staphylococcus, Escherichia coli, Pseudomonas aeruginosa, Bacillus
subtilis, and the yeast fungi. The zone of inhibition was measured in each concentration. The
150-μL extract concentration in methanol extract showed good antibacterial activity against
Staphylococcus and P. aeruginosa bacteria compared with the ethanol extract. The treated cotton
fabrics were assessed for their antimicrobial property, and the zone of inhibition was found to
be in the range of 13–15 mm. Then the antihemorrhagic property was assessed in both ethanol
extract and methanol extract solution alone. The ethanol extracts showed a minimum time for
clotting the blood, i.e., 2.2min. The treated fabrics were assessed for the time taken to clot blood,
and it was found that it took 1.2–1.4 min, which was improved when compared with the normal
blood clotting time of 2–2.3 min. Biocompatibility Chorioallantoic membrane (CAM) preparation
helps us to know the endpoints like hemorrhage, vascularlysis, coagulation, and irritation score of
treated and untreated cotton fabric. The test is similar to the effects of the rabbit skin testing
treatment, which shows the result of zero value for endpoints. The Medicago sativa herb exhibited
good antimicrobial and antihemorrhagic properties for medicinal applications.
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摘要 :
In this work, medicinal plant alfalfa leaf extract was used as an antihemorrhagic, antimicrobial,
and antifungal agent and applied to cotton fabrics. The medicinal herb alfalfa leaf was
extracted using the ethanol and methanol s...
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In this work, medicinal plant alfalfa leaf extract was used as an antihemorrhagic, antimicrobial,
and antifungal agent and applied to cotton fabrics. The medicinal herb alfalfa leaf was
extracted using the ethanol and methanol solvents in the Soxhlet apparatus. The 50-μL,
100-μL, and 150-μL concentrations of extracted solution were tested against the positive and
negative bacteria, namely Staphylococcus, Escherichia coli, Pseudomonas aeruginosa, Bacillus
subtilis, and the yeast fungi. The zone of inhibition was measured in each concentration. The
150-μL extract concentration in methanol extract showed good antibacterial activity against
Staphylococcus and P. aeruginosa bacteria compared with the ethanol extract. The treated cotton
fabrics were assessed for their antimicrobial property, and the zone of inhibition was found to
be in the range of 13–15 mm. Then the antihemorrhagic property was assessed in both ethanol
extract and methanol extract solution alone. The ethanol extracts showed a minimum time for
clotting the blood, i.e., 2.2min. The treated fabrics were assessed for the time taken to clot blood,
and it was found that it took 1.2–1.4 min, which was improved when compared with the normal
blood clotting time of 2–2.3 min. Biocompatibility Chorioallantoic membrane (CAM) preparation
helps us to know the endpoints like hemorrhage, vascularlysis, coagulation, and irritation score of
treated and untreated cotton fabric. The test is similar to the effects of the rabbit skin testing
treatment, which shows the result of zero value for endpoints. The Medicago sativa herb exhibited
good antimicrobial and antihemorrhagic properties for medicinal applications.
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摘要 :
In this study, the performance and emissions of Al_(2)O_(3)alkaline cottonseed biodiesel-powered compression ignition engines were predicted. An experiment was conducted using different biodiesel blends made from cottonseed oil un...
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In this study, the performance and emissions of Al_(2)O_(3)alkaline cottonseed biodiesel-powered compression ignition engines were predicted. An experiment was conducted using different biodiesel blends made from cottonseed oil under various loading conditions. Biodiesel was produced using ethanol and Cao-mg/Al_(2)O_(3)as catalysts through the transesterification process and blended with diesel to produce CBDN10, CBDN20, CBDN30, and CBDN40. The CBDN20 blends showed an evident reduction in fuel consumption by 8% and a 12% improvement in thermal efficiency at high static thrust. The use of these blends resulted in minimal CO, CO_(2), and NO_(x)emissions from engines. These emissions were monitored by an IoT system and analysed with gas analysers, which revealed CBDN20's ability to reduce nitrogen oxide and hydrocarbon emissions compared to diesel. Additionally, CBDN20 demonstrated improved thermal efficiency and reduced brake-specific fuel consumption compared to the other blends.
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