Original Article
Javad Pourqasem; Duško Tešić; Eisa Abdolmaleki
Abstract
Smart water for the quality monitoring is to be gaining in importance with a advancements in communication technology. The Web of Things (IoT) gets the associations among different gadgets with the capacity to trade and getting information. IoT additionally stretches out its ability to ecological issues ...
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Smart water for the quality monitoring is to be gaining in importance with a advancements in communication technology. The Web of Things (IoT) gets the associations among different gadgets with the capacity to trade and getting information. IoT additionally stretches out its ability to ecological issues notwithstanding the computerization industry by utilizing industry 4.0. As water is one of the fundamental necessities of human endurance, it is expected to consolidate some instruments to screen water quality from the opportunity to time. Around 45% of passing’s are caused because of defiled water on the planet. Subsequently, there is a need to guarantee the supply of filtered drinking water for individuals both in urban areas and towns. Water Quality Monitoring is a practical and proficient framework intended to screen drinking water quality that utilizes Internet of Things (IoT) innovation. In this paper, the proposed framework comprises a few sensors to gauge different boundaries, for example, pH esteem, and turbidity in the water, level of water in the tank, temperature, and mugginess of the encompassing air. And for more, information the Microcontroller Unit (MCU) is connected to these sensors and handled with a Personal Computer (PC). The got information is shipped off the cloud by utilizing IoT based Think Speak application to screen the nature of the water.
Original Article
Muhammad Kamran; Aamir Hussain Khan; Zeeshan Anwar; Aiman Ishtiaq; Anns Uzair; Shanzay Noor Khan; Sawaira Saeed; Sajid Ali; Saara Fatima; Ajwa Faisal; Baqir Hussain; Misbah Rasheed; Saba Mehmood
Abstract
In the last few decades, nanomaterials have found widespread application in a variety of industries, including electronics, building, food processing, pharmaceuticals, cosmetics, and aviation. These nanoparticles could enhance medical therapy, diagnostics, and preventive methods. These days, drug delivery ...
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In the last few decades, nanomaterials have found widespread application in a variety of industries, including electronics, building, food processing, pharmaceuticals, cosmetics, and aviation. These nanoparticles could enhance medical therapy, diagnostics, and preventive methods. These days, drug delivery and cellular imaging are two applications of benzonoid systems in biotechnology and medicine. Non-kekulean benzoid hydrocarbons offer a great way to evaluate the structural characteristics of their series due to their regular structures. This work involves the computation of several degree-based topological indices that are helpful in figuring out how reactive the associated molecules are. In particular, we found these calculations to be helpful in examining the thermodynamic parameter entropy, which could be important for successfully reworking the structure of non-kekulean benzoid hydrocarbons.
Original Article
Muhammad Abid; Madiha Bibi; Nasir Yasin; Muhammad Shahid
Abstract
Accurate numerical solution of parabolic and elliptic partial differential equations governing two-dimensional heat transfer is critical for engineering simulations but computationally challenging.This work employs key numerical techniques finite differences, conjugate gradients, and Crank-Nicolson ...
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Accurate numerical solution of parabolic and elliptic partial differential equations governing two-dimensional heat transfer is critical for engineering simulations but computationally challenging.This work employs key numerical techniques finite differences, conjugate gradients, and Crank-Nicolson time stepping to solve the heat diffusion equation and analyze method performance.The Poisson equation is discretized using second-order central finite differences and solved with the conjugate gradient approach to determine the steady state solution. The transient heat equation is integrated in time via the Crank-Nicolson implicit scheme, also utilizing conjugate gradients.The methods effectively compute solutions matching analytical and boundary conditions. Convergence and stability are achieved while capturing transient thermal evolution. Insights are gained into discretization and iteration parameter impacts.The numerical framework demonstrates accurate and efficient simulation of two-dimensional conductive heat transfer. It provides a template for extension to more complex geometries and multiphysics phenomena, contributing to advances in computational engineering.
Original Article
Aqib Zafar; Shyam Sundra Santra; Muhammad Nasir
Abstract
In this article, Cubic Trigonometric B-Spline Collocation technique is used to solve Modified
Equal Width (MEW) Wave equation with application. The proposed scheme of major equation
is tested by three ways: Single Soliton Wave, train of Solitary Waves and final birth solution. The
efficiency and validity ...
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In this article, Cubic Trigonometric B-Spline Collocation technique is used to solve Modified
Equal Width (MEW) Wave equation with application. The proposed scheme of major equation
is tested by three ways: Single Soliton Wave, train of Solitary Waves and final birth solution. The
efficiency and validity i.e, of proposed method is checked by different time levels. The present
scheme is implemented to find out three invariants quantities and two error L2 and L1 norms.
The given scheme is stabled via Von Neumman method. The obtain results are improved from
earlier results. Some examples are listed to show the effusiveness and validity of the main results.
Original Article
Dipak Dulal; Ramin Goudarzi Karim; Carmeliza Navasca
Abstract
In this paper, we use tensor models to analyze the Covid-19 pandemic data. First, we use tensor models, canonical polyadic, and higher-order Tucker decompositions to extract patterns over multiple modes. Second, we implement a tensor completion algorithm using canonical polyadic tensor decomposition ...
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In this paper, we use tensor models to analyze the Covid-19 pandemic data. First, we use tensor models, canonical polyadic, and higher-order Tucker decompositions to extract patterns over multiple modes. Second, we implement a tensor completion algorithm using canonical polyadic tensor decomposition to predict spatiotemporal data from multiple spatial sources and to identifyCovid-19 hotspots. We apply a regularized iterative tensor completion technique with a practical regularization parameter estimator to predict the spread of Covid-19 cases and to find and identify hotspots. Our method can predict weekly, and quarterly Covid-19 spreads with high accuracy. Third, we analyze Covid-19 data in the US using a novel sampling method for alternating leastsquares. Moreover, we compare the algorithms with standard tensor decompositions concerning their interpretability, visualization, and cost analysis. Finally, we demonstrate the efficacy of the methods by applying the techniques to the New Jersey Covid-19 case tensor data.
Original Article
Aadil Rashid Sheergojri; Pervaiz Iqbal
Abstract
To better understand how things work in biology, you can use mathematics to figure things out. Cancer modelling is a complex biological process that is highly unpredictable, which fuzzy models in this study have achieved. Biomolecular components of malignant disorders and their analysis are frequently ...
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To better understand how things work in biology, you can use mathematics to figure things out. Cancer modelling is a complex biological process that is highly unpredictable, which fuzzy models in this study have achieved. Biomolecular components of malignant disorders and their analysis are frequently examined. Even though most documented investigations have not yet reached the competency needed for "curing cancer," research has contributed to understanding the statistical principles governing cancer cell development, invasion, and proliferation. This article begins with an overview of mathematical models for tumor development and treatment, which consider stochastic perturbations a therapeutic remedy. Also, it has been demonstrated that fuzzy modeling approaches may be used to investigate the impacts of various components on tumor development estimation, minimize tumor uncertainty, and attain a degree of realism.
