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Implementing artificial intelligence agent within connect 4 using unity3d and machine learning concepts
Nowadays, we come across games that have unbelievably realistic graphics that it usually becomes hard to distinguish between reality and the virtual world when we are exposed to a virtual reality gaming console. Implementing the concepts of Artificial Intelligence (AI) and Machine-Learning (ML) makes the game self-sustainable and way too intelligent on its own, by making use of self-learning methodologies which can give the user a better gaming experience. The use of AI and ML in games can give a better dimension to the gaming experience in general as the virtual world can behave unpredictably, thus improving the overall stigma of the game. In this paper, we have implemented Connect-4, a multiplayer game, using ML concepts in Unity3D. The machine learning toolkit ML-Agents, which depends on Reinforcement Learning (RL) technique, is provided using Unity3D. This toolkit is used for training the game agent which can distinguish its good moves and mistakes while training, so that the agent will not go for same mistakes over and over during actual game with human player. With this paper, authors have increased intelligence of game agent of Connect 4 using Reinforcement Learning, Unity3D and ML-Agents toolkit. BEIESP. -
The impact of slip mechanisms on the flow of hybrid nanofluid past a wedge subjected to thermal and solutal stratification
This investigation aims to inspect the flow and thermal characteristics of hybrid nanoparticles under the effect of thermophoresis and Brownian motion. The hybrid nanofluid is formed by dispersing the silver nanoparticles into the base fluid composed of tungsten oxide and water. The resulting hybrid nanofluid is assumed to flow over a moving wedge. The wedge is a geometry that can be commonly seen in many manufacturing industries, moulding industries, etc., where friction creates more heat and cooling becomes a necessary process. This study currently focuses on such areas of the industries. In this regard, the flow expressions in the form of Partial Differential Equations (PDEs) are obtained by incorporating the modified Buongiorno's model and using boundary layer approximations. The modified Buongiorno model helps us analyze the impact of volume fraction along with the slip mechanisms. Suitable transformations are used to achieve the nondimensional form of governing equations, and further, it transforms the PDE to Ordinary Differential Equation (ODE). The RKF-45 is used to solve the obtained ODE and the boundary conditions. Furthermore, graphic analysis of the solutions for fluid velocity, energy distributions and dimensionless concentration is provided. It was noted that the behavior of the Nusselt and Sherwood numbers was determined by analyzing numerous parameters. The conclusions show that they decrease with greater values of the stratification factors. Additionally, with higher values of the wedge parameter, the magnitude of the velocity field and the thermal boundary layer diminish. 2023 World Scientific Publishing Company. -
Pemetrexed loaded gold nanoparticles as cytotoxic and apoptosis inducers in lung cancer cells through ROS generation and mitochondrial dysfunction pathway
Supramolecular nanoparticles containing peptides and drugs have recently gained recognition as an effective tumor treatment drug delivery system. A multitarget drug termed pemetrexed is effective against various cancers, including nonsmall cell lung cancer. The work aims to establish the capability of pemetrexed gold nanoparticles (PEM-AuNPs) to induce apoptosis and explore molecular changes. X-ray diffraction, Fourier-transform infrared spectroscopy, ultravioletvisible spectroscopy, scanning electron microscope, and transmission electron microscope were used to investigate the synthesized nanoparticles. The MTT assay was utilized to investigate the anticancer properties of PEM-AuNPs at varying concentrations (50, 100, and 200M). PEM-AuNPs demonstrated a decrease in cell viability with 55.87%, 43.04%, and 25.59% for A549 cells and 54.31%, 37.40%, and 25.84% for H1299 cells at the respective concentrations. To assess apoptosis and perform morphological analysis, diverse biochemical staining techniques, including acridine orange-ethidium bromide and 4?,6-diamidino-2-phenylindole nuclear staining assays, were employed. Additionally, 2?,7?-dichlorofluorescein diacetate staining confirmed the induction of reactive oxygen species generation, while JC-1 staining validated the impact on the mitochondrial membrane at the IC50 concentration of PEM-AuNPs. Thus, the study demonstrated that the synthesized PEM-AuNPs exhibited enhanced anticancer activity against both A549 and H1299 cells. 2024 International Union of Biochemistry and Molecular Biology, Inc. -
Training multi-layer perceptron with enhanced brain storm optimization metaheuristics
In the domain of artificial neural networks, the learning process represents one of the most challenging tasks. Since the classification accuracy highly depends on the weights and biases, it is crucial to find its optimal or suboptimal values for the problem at hand. However, to a very large search space, it is very difficult to find the proper values of connection weights and biases. Employing traditional optimization algorithms for this issue leads to slow convergence and it is prone to get stuck in the local optima. Most commonly, back-propagation is used for multi-layer-perceptron training and it can lead to vanishing gradient issue. As an alternative approach, stochastic optimization algorithms, such as nature-inspired metaheuristics are more reliable for complex optimization tax, such as finding the proper values of weights and biases for neural network training. In this work, we propose an enhanced brain storm optimization-based algorithm for training neural networks. In the simulations, ten binary classification benchmark datasets with different difficulty levels are used to evaluate the efficiency of the proposed enhanced brain storm optimization algorithm. The results show that the proposed approach is very promising in this domain and it achieved better results than other state-of-the-art approaches on the majority of datasets in terms of classification accuracy and convergence speed, due to the capability of balancing the intensification and diversification and avoiding the local minima. The proposed approach obtained the best accuracy on eight out of ten observed dataset, outperforming all other algorithms by 1-2% on average. When mean accuracy is observed, the proposed algorithm dominated on nine out of ten datasets. 2022 Tech Science Press. All rights reserved. -
Semilinear fractional elliptic equations with combined nonlinearities and measure data
This study focuses on semilinear fractional elliptic problems with concave-convex type nonlinearities and measures as data. Suitable iteration techniques and embedding results are employed to ensure the existence and multiplicity of solutions. 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG. -
Challenges of Treating Bilingual and Multilingual Stuttering
[No abstract available] -
Therapists Issues in Understanding Stuttering
[No abstract available] -
Exploring evolution, development, and contribution of International Journal of Industrial and Systems Engineering (20052022): a bibliometric study
International Journal of Industrial and Systems Engineering (IJISE) reached its 18th year of publishing in 2023. A comprehensive assessment of 1,096 publications using the bibliometric data analysis technique is performed to understand growth of the journal for the past 18 years. Different indicators like co-occurrence of all keywords, co-authorship, citation and co-citation analysis of authors, countries, and institutions is performed through VOS Viewer software. The findings of the study emphasise contribution of IJISE to knowledge domain. Copyright 2024 Inderscience Enterprises Ltd. -
International Journal of Operational Research: a retrospective overview between 2005 and 2020
The study presents a retrospective analysis of the International Journal of Operational Research (IJOR) across its 16 years of publication, 2005 to 2020. IJOR is a journal of international repute that publishes original and peer-reviewed research in the management sciences, decision sciences, and operation research domain. The journal reached its 17th year of publishing in 2021. This study provides a comprehensive overview of 1,023 publications using the bibliometric data analysis technique. The study focuses on the contribution of IJOR to the knowledge domain through publishing trends, authorship patterns, dominant authors, prominent articles, nature of studies, and thematic analysis. Co-occurrence analysis of all keywords, co-authorship, citation and co-citation analysis of authors, countries, and institutions is performed through VOSviewer software. The findings of the study emphasise the relationship of IJOR to different fields. 2024 Inderscience Enterprises Ltd. -
Examining scientific contribution of International Journal of Productivity and Quality Management (20062019) a bibliometric study
International Journal of Productivity and Quality Management (IJPQM) is a journal of global reputation that publishes original and peer-reviewed research in the business management and accounting purview. The journal reached its 17th year of publishing in 2022. This study provides an inclusive synopsis of 720 publications using bibliometric data analysis techniques. The study emphasises the contribution of IJPQM to the academic fraternity through the analysis of publishing developments, authorship analysis, influential contributors, prominent studies published in IJPQM, nature and industry of studies. Analysis of the journal through SCImago indicators is also presented in the study. 2024 Inderscience Enterprises Ltd. -
International Journal of Logistics Systems and Management (20042020): an analytical retrospective
International Journal of Logistics Systems and Management (IJLSM) is a journal of international repute that publishes original and peer-reviewed research in the business, management, accounting, and decision sciences domain. The journal reached its 18th year of publishing in 2021. This study provides a comprehensive overview of 962 publications using the bibliometric data analysis technique. The study focuses on the contribution of IJLSM to the knowledge domain through publishing trends, authorship patterns, dominant authors, prominent articles, nature of studies, and thematic analysis. Cooccurrence of all keywords, co-authorship, citation and co-citation analysis of authors, countries, and institutions is performed through VOS viewer software. The findings of the study emphasise the relationship of IJLSM to different fields. The analysis also provides key insights into the evolution of the domain over time. 2024 Inderscience Enterprises Ltd. -
Retrospective analysis of International Journal of Procurement Management (20072021)
International Journal of Procurement Management (IJPM) is a journal of international repute that publishes original and peer-reviewed research in the business, management, and accounting domain. The journal reached its 15th year of publishing in 2021. This study provides a comprehensive overview of 456 publications using the bibliometric data analysis technique. The study focuses on the contribution of IJPM to the knowledge domain through publishing trends, authorship patterns, dominant authors, prominent articles, nature of studies, and thematic analysis. Co-occurrence of all keywords, co-authorship, citation and co-citation analysis of authors, countries, and institutions is performed through VOS Viewer software. The findings of the study emphasise the relationship of IJPM to different fields. The analysis also provides key insights into the evolution of the domain over time. Copyright 2024 Inderscience Enterprises Ltd. -
An Application of the Caputo Fractional Domain in the Analysis of a COVID-19 Mathematical Model
Vaccination programs aimed at preventing the spread of the coronavirus appear to have a significant global impact. In this research, we have investigated a mathematical model projecting COVID-19 disease spread by considering five groups of individuals viz. vulnerable, exposed, infected, unreported, recovered, and vaccinated. Looking at the current abnormal pattern of the virus spread in the projected model, we have implemented the fractional derivative in the Mittag-Leffler context. Using the existing theory of the fractional derivative, we have examined the theoretical aspects such as the existence and uniqueness of the solutions, the existence and stability of the disease-free and endemic equilibrium points, and the global stability of the disease-free equilibrium point. In computing the basic reproduction number, we have analyzed that the existence and stability of points of equilibrium are dependent on this number. The sensitivity of the basic reproduction number is also examined. The importance of the vaccination drive is highlighted by relating it to the basic reproduction number. Finally, we have presented the simulation of the numerical results by capturing the profile of each group under the influence of the fractional derivative and investigated the impact of vaccination rate and contact rate in controlling the disease by applying the Adams-Bashforth-Moultan (ABM) method. The present research study demonstrates the importance of the vaccination campaign and the curb on individual contact by featuring a novel fractional operator in the projected model and capturing the corresponding consequence. 2024 P. Veeresha, et al. -
Dynamical analysis of fractional yellow fever virus model with efficient numerical approach
In this paper, we have projected the theoretical and numerical investigation of the mathematical model representing the yellow fever virus transmission from infected mosquitoes to humans or vise-versa through mosquito bites in the framework of the Caputo derivative. Theoretical aspects of the dynamics of susceptible individuals, exposed individuals, infected individuals, toxic infected individuals, recovered and immune individuals, and susceptible mosquitoes and infected mosquitoes have been analyzed by using the theory of fractional calculus such as boundedness, uniqueness and existence of the solutions. Sufficient conditions for the global stability of the virus-free point of equilibrium are inspected. T validate the theoretical results numerical analysis is performed using the generalized Adams-Bashforth-Moultan method. 2023, Eudoxus Press, LLC. All rights reserved. -
Dynamics of a fractional epidemiological model with disease infection in both the populations
In order to depict a situation of possible spread of infection from prey to predator, a fractional-order model is developed and its dynamics is surveyed in terms of boundedness, uniqueness, and existence of the solutions. We introduce several threshold parameters to analyze various points of equilibrium of the projected model, and in terms of these threshold parameters, we have derived some conditions for the stability of these equilibrium points. Global stability of axial, predator-extinct, and disease-free equilibrium points are investigated. Novelty of this model is that fractional derivative is incorporated in a system where susceptible predators get the infection from preys while predating as well as from infected predators and both infected preys and predators do not reproduce. The occurrences of transcritical bifurcation for the proposed model are investigated. By finding the basic reproduction number, we have investigated whether the disease will become prevalent in the environment. We have shown that the predation of more number of diseased preys allows us to eliminate the disease from the environment, otherwise the disease would have remained endemic within the prey population. We notice that the fractional-order derivative has a balancing impact and it assists in administering the co-existence among susceptible prey, infected prey, susceptible predator, and infected predator populations. Numerical computations are conducted to strengthen the theoretical findings. 2021 Author(s). -
Fractional Approach for Belousov-Zhabotinsky Reactions Model with Unified Technique
The Belousov-Zhabotinsky reaction model represents chemical oscillators that exhibit periodic vibrations as a result of complex physic-chemical phenomena. The non-linear behaviour exhibited by Belousov-Zhabotinsky model is the cause of Turing patterns, birth of spiral waves, rise of limit cycle attractors, and deterministic chaos in many chemical reaction processes. Due to these noteworthy characteristics, in this paper, we have analyzed mathematical Belousov-Zhabotinsky model by a novel numerical approach q-Homotopy analysis transformation method. To interpret new observations, we have incorporated Caputo fractional derivative in the model. The numerical result are presented graphically and concerning the absolute error of solutions. With the help of the homotopy parameter curve, we have projected the convergence region with reference to diverse values of fractional derivative. This work establishes that the projected numerical algorithm is a well-organized tool to analyze the multifaceted coupled partial differential equation representing Belousov-Zhabotinsky type reactions. 2024 NSP Natural Sciences Publishing Cor. -
Laguerre polynomial-based operational matrix of integration for solving fractional differential equations with non-singular kernel
The Atangana-Baleanu derivative and the Laguerre polynomial are used in this analysis to define a new computational technique for solving fractional differential equations. To serve this purpose, we have derived the operational matrices of fractional integration and fractional integro-differentiation via Laguerre polynomials. Using the derived operational matrices and collocation points, we reduce the fractional differential equations to a system of linear or nonlinear algebraic equations. For the error of the operational matrix of the fractional integration, an error bound is derived. To illustrate the accuracy and the reliability of the projected algorithm, numerical simulation is presented, and the nature of attained results is captured in diverse order. Finally, the achieved consequences enlighten that the solutions obtained by the proposed scheme give better convergence to the actual solution than the results available in the literature. 2021 The Author(s). -
Unleashing economic potential: decoding the FDI-economic growth nexus in G-15 economies amidst unique host country traits
This study examined the impacts of ForeignDirectInvestment (FDI) on economic growth across top the five G-15 countries over a period of 33years, while considering the influence of key host country traits, namely macroeconomic stability, financial development, human capital, and trade openness. The selection of these variables was firmly supported by both theoretical foundations and empirical studies that highlight their significant role in shaping the FDIgrowth interconnection. Panel data derived from World Bank Indicators, spanning the period from 1989 to 2021, were analyzed using a feasible generalized least squares method (FGLS), a rigorous approach, including descriptive statistics, correlation analysis, cross-sectional dependence tests, unit root tests, and multiple regression models. By exploring the interconnection between FDI and the characteristics of the host country, this study sheds light on how these factors collectively contributed to economic growth in the G-15 economies. Descriptive statistics indicated a favorable trend in economic growth, with an average of 3.470 and a standard deviation of 4.289. Correlation analysis revealed significant positive relationships between Economic Growth and Gross Capital Formation, Human Capital, and Liquid Liabilities. Conversely, FDI, Inflation, and Trade Openness displayed insignificant positive correlations with Economic Growth. The findings also demonstrated that favorable host country traits magnified the impact of FDI on economic growth. Specifically, increased Financial Development, Human Capital, and Trade Openness enhanced the positive effects of FDI on economic growth. However, Inflation had a dampening effect on the growth factor. Policymakers in G-15 countries should give precedence to developing strong financial markets, promoting trade liberalization, and investing in human capital to optimize the advantages of FDI. This research addresses a critical gap in the literature as limited empirical work has been conducted on the FDIgrowth relationships specific to the G-15 economies, which hold substantial influence in the global investment landscape and showcase remarkable economic growth. By employing rigorous panel data methodology and a long-term dataset, we provides original insights into the interaction between FDI and host country characteristics, contributing to the existing body of knowledge. The Japan Section of the Regional Science Association International 2024. -
Calendar anomalies in the Indian stock markets: Monsoon effect
This paper deals with identifying the presence of monsoon effect in the Indian stock market using EGARCH model as well as the impact on the volatility of returns of the selected indices during the monsoon months in India. Daily time series data of closing price of four major indices i.e. Nifty 50, Nifty Smallcap 100, Nifty Midcap 100 and Nifty 500 over a period of sixteen years (April 2002 to March 2018) were collected and analysed. The results substantiate the fact that monsoon effect is present in the Indian equity market. The returns of Nifty 50 and Nifty 500 indices during the month of September were significantly higher. There was also a significant increase in the volatility during the month of September. No significant change was detected during the monsoon months for Midcap 100 and Nifty Smallcap 100. Monsoon effect was found in indices tracking top performing 50 stocks and 500 stocks listed in NSE. Hence, it can be inferred that monsoon effect is present in the Indian stock market. 2019, Allied Academies. -
Vicarious Trauma in Law Students: Role of Gender, Personality, and Social Support
Law student trainees are exposed to trauma-related work which puts them at higher risk of being adversely affected by it. Since they are not directly related to the event, their distress goes unnoticed. The repetitive account of traumatic instances leads to traumatization of their own which is referred to as vicarious traumatization. The purpose of this paper was to delve into the degree to which the role of gender, personality, and social support impact law students vulnerability to vicarious trauma. For the current research, exploratory design was utilized. All one hundred and twenty participants were selected using purposive sampling. Self-report measures were employed to investigate social support, personality traits, and vicarious trauma in sixty male and sixty female law students. The results revealed that female law students and those law students who are high on Neuroticism and low on Extraversion are more vulnerable to experiencing vicarious trauma. Implications for trainees and educators are discussed and suggestions are provided for future research. 2021 International Journal of Criminal Justice Sciences. All Rights Reserved.