A Cognitive Agent Computing-Based Model For The Primary School Student Migration Problem Using A Descriptive Agent-Based Approach

Students' migration from public to private schools, due to lack of school performance of public schools, is one of the major issues faced by the Government of Punjab to provide compulsory and quality education at low cost. Due to complex adaptive nature of educational system, interdependencies with society, constant feedback loops conventional linear regression methods, for evaluation of effective performance, are ineffective or costly to solve the issue. Linear regression techniques present the static view of the system, which are not enough to understand the complex dynamic nature of educational paradigm. We have presented a Cognitive Agent Computing-Based Model for the School Student Migration Problem Using a Descriptive Agent-Based Modeling approach to understand the causes-effects relationship of student migration. We have presented the primary school students' migration model using descriptive modeling approach along with exploratory modeling. Our research, in the context of Software Engineering of Simulation & Modeling, and exploring the Complex Adaptive nature of school system, is two folds. Firstly, the cause-effect relationship of students' migration is being investigated using Cognitive Descriptive Agent-Based Modeling. Secondly, the formalization extent of Cognitive Agent-Based Computing framework is analyzed by performing its comparative analysis with exploratory modeling protocol 'Overview, Design, and Detail'.Comment: 117 pages, MS thesi

Influence of Natural Zeolite and Paraffin Wax on Adhesion Strength Between Bitumen and Aggregate

Asphalt mixture that is used for the construction of flexible pavements is mainly composed of two constituents i.e. bitumen and aggregate. Sturdy adhesion among bitumen and aggregate is the sign of durability of asphalt pavements. Adhesion is considered as one of the most important factors for sustainable asphalt pavement. This is the motive why its miles utmost important to deeply understand the phenomenon of adhesion considering the effect of alternate in temperature, moisture conditions. In this study softer binder 80/100 was selected that has less adhesion compared to hard pen grades. Limestone aggregates which is commonly used for the construction of asphalt pavements has also been selected. Two types of modifiers (Zeolite and Paraffin Wax) were selected because of the extensive use in asphalt foaming and the polymer modified asphalt mixtures as temperature reducing agent. To investigate the strength of adhesive bond, Bitumen Bond Strength (BBS) was performed at different temperatures, in dry, and wet conditions. To quantify the effect of modifiers on penetration grade and softening point conventional testing is performed. For performance grading, the PG test was performed using Dynamic Shear Rheometer. The comparisons were developed among pull of tensile strength at dry and after 72hrs water conditioning while preserving the temperature at 25 .To check the effect of temperature BBS is performed at 15 . The results illustrate that 2% zeolite shows best results in terms of adhesion and performance grade while Paraffin wax has less adhesion and poor performance grade

Ensemble learning based defect detection of laser sintering

In rapid development, Selective Laser Sintering (SLS) creates prototypes by processing industrial materials, for example, polymers. Such materials are usually in powder form and fused by a laser beam. The manufacturing quality depends on the interaction between a high-energy laser beam and the powdered material. However, in-homogeneous temperature distribution, unstable laser powder, and inconsistent powder densities can cause defects in the final product, for example, Powder Bed Defects. Such factors can lead to irregularities, for example, warping, distortion, and inadequate powder bed fusion. These irregularities may affect the profitable SLS production. Consequently, detecting powder bed defects requires automation. An ensemble learning-based approach is proposed for detecting defects in SLS powder bed images from this perceptive. The proposed approach first pre-processes the images to reduce the computational complexity. Then, the Convolutional Neural Network (CNN) based ensembled models (off-the-shelf CNN, bagged CNN, and boosted CNN) are implemented and compared. The ensemble learning CNN (bagged and boosted CNN) is good for powder bed detection. The evaluation results indicate that the performance of bagged CNN is significant. It also indicates that preprocessing of the images, mainly cropping to the region of interest, improves the performance of the proposed approach. The training and testing accuracy of the bagged CNN is 96.1% and 95.1%, respectively.© 2023The Authors. IET Optoelectronics published by John Wiley& Sons Ltd on behalf of The Institution of Engineering and Technology. This is an open access article under the terms of the Creative Commons Attribution License,which permits use, distribution and reproduction in any medium, provided the original work is properly cited.fi=vertaisarvioitu|en=peerReviewed

Development of an Acid Resistant Concrete: A Review

This review paper addresses the measures taken to prevent or minimize the deterioration of concrete, which confronts an acidic environment. Primarily, the mechanism of reaction between alkaline concrete and acid is clearly demonstrated. The mechanism of reaction clearly sets guidelines as to how the chances of this disastrous reaction should be minimized or eliminated at all. The suggested preventive measures are two-fold i.e. the improvement of the basic microstructure of concrete and the provision of barriers against acids. Concrete can be made acid resistant using classical as well as novel techniques like nanotechnology.   There exists an immense need that these measures are recognized and implemented by the construction industry to put a stop to huge money losses

Quantitative Estimation of Biocapped Surface Chemistry Driven Interparticle Interactions and Growth Kinetics of Gold Nanoparticles

In phytosynthesis of gold nanoparticles (AuNPs), biomolecules play a vital role in biocapping the surface of particles and generating the electrostatic repulsive forces to inhibit their growth kinetics. However, estimation of bioactive compounds influencing their surface characteristics through formation of electric repulsive forces (Velec\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$V_{elec}$$\end{document}), Van der Waals attraction forces (Vvdw\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$V_{vdw}$$\end{document}) and ultimately hindering their growth is still in the phase of obscurity. Current study, based on surface chemistry approach has been performed for identification of bioactive compounds in Elaeis guineensis leaves (EGL/OPL), acting as biocapping agents and directing the growth of AuNPs over a period of time. The quantitative estimation of interparticle interactions and modification in Ostwald ripening (MOR) model were also done to correlate the growth kinetic of AuNPs. The X-ray photoelectron spectroscopy (XPS) showed the major contribution of oxygen, carbon and nitrogen elements, corresponding to polyphenolic, carboxylic and amides, in biocapping the surface of AuNPs and directing their interparticle interactions associated with growth kinetics. The Velec\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$V_{elec}$$\end{document} forces were reduced with an enhancement in the Vvdw\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$V_{vdw}$$\end{document} forces, depicting their major role in impeding growth of AuNPs. The MOR model exhibited an excellent agreement of predicted growth with experimental size enlargements of AuNPs, having 4.8% average absolute relative percentage error

Controllable phytosynthesis of gold nanoparticles and investigation of their size and morphology-dependent photocatalytic activity under visible light

© 2020 Elsevier B.V. Plants mediated synthesis of gold nanoparticles (AuNPs) containing desired characteristics for their suitable potential applications has been a challenging task, which is causing a major hindrance towards its commercialization. Therefore, herein phytosynthesis of AuNPs with required size and morphology has been achieved through manipulating the reaction conditions including reaction temperature and volume of Elaeis guineensis leaves (EGL) extract. Furthermore, photocatalytic potential of EGL mediated AuNPs having different size and shape has also been explored for the removal of methylene blue (MB) under visible light irradiation. The reaction temperature and volume of EGL strongly influenced the size and morphology of AuNPs, which are directly associated with the photocatalytic activities. The experimental results revealed that predominantly spherical and ultra-smaller size AuNPs with particle size of 16.26 ± 5.84 nm, formed at 70 °C showed the highest removal efficiency up to 92.55 % in 60 min. This highest photocatalytic activity of AuNPs could be attributed to the availability of higher number of low-coordinated gold (Au) atoms in the MB aqueous solution, which might have boosted the adsorption of the MB on the surface of particles and accelerated the degradation phenomenon. The proposed photocatalytic degradation mechanism of AuNPs for MB was also explained. The highly photoactive EGL mediated AuNPs with controllable morphology and size could be an advance step in future in chemical and biomedical applications

Effect of gold and iron nanoparticles on photocatalytic behaviour of titanium dioxide towards 1-butyl-3-methylimidazolium chloride ionic liquid

© 2019 Elsevier B.V. The high water solubility, chemical stability and low volatility of ionic liquids (ILs) have made them potentially persistent than conventional pollutants and toxic to the aquatic organisms. Therefore, extensive research efforts are being directed with an aim to develop cheap and efficient protocols to reduce the uncontrolled release of ILs in the environment. In the same line of action, titanium dioxide (TiO2) loaded with gold and iron nanoparticles were trialled for the photocatalytic degradation of highly concentrated 1-butyl-3-methylimidazolium chloride [BmimCl] ionic liquid. Furthermore, results pertaining to the degradation of the [BmimCl] using TiO2 loaded with gold nanoparticles (AuNPs) were compared with results obtained by using TiO2 loaded with Fe (NO3)3.9H2O and pristine TiO2 under same set of conditions. It was found that TiO2 decorated AuNPs demonstrated 7 times higher photocatalytic degradation for highly concentrated [BmimCl] in 60 min of reaction time in comparison to the pristine TiO2. Congruently, investigations also revealed that TiO2 loaded AuNPs expressed 3.3 times higher photocatalytic degradation of [BmimCl] in comparison to conventional photocatalyst TiO2@Fe under same reaction conditions. The higher photocatalytic performance associated with TiO2 loaded AuNPs was due to the enhanced Schottky barrier, which could have minimized the photocharge carrier resistance separation and migration. The mechanism for photocatalytic degradation of [BmimCl] using TiO2 loaded AuNPs has been also been described

Mechanical and Comfort Properties of Hydroentangled Nonwovens from Comber Noil

Cotton fibre is one of the most important commodity fibre and is widely employed in apparels. At present, the share of natural fibres in production of nonwoven fabrics is low and employed in opt applications. The cotton fibre is conventionally converted into woven and knitted fabrics by short staple spinning methods. The comber noil is short fibre waste during production of combed cotton yarns. The aims of the current study were to employ comber noil for preparation of hydroentangled cotton nonwovens at varying water jet pressures and conveyor speeds. The effect of these parameters is studied with respect to mechanical and comfort properties of prepared fabrics. The results showed that these variables can help to manufacture fibrous assemblies with engineered properties according to required application area