Volterra type integral equations have diverse applications in scientific and other fields. Modelling physical phenomena by employing integral equations is not a new concept. Similarly, extensive research is underway t...Volterra type integral equations have diverse applications in scientific and other fields. Modelling physical phenomena by employing integral equations is not a new concept. Similarly, extensive research is underway to find accurate and efficient solution methods for integral equations. Some of noteworthy methods include Adomian Decomposition Method (ADM), Variational Iteration Method (VIM), Method of Successive Approximation (MSA), Galerkin method, Laplace transform method, etc. This research is focused on demonstrating Elzaki transform application for solution of linear Volterra integral equations which include convolution type equations as well as one system of equations. The selected problems are available in literature and have been solved using various analytical, semi-analytical and numerical techniques. Results obtained after application of Elzaki transform have been compared with solutions obtained through other prominent semi-analytic methods i.e. ADM and MSA (limited to first four iterations). The results substantiate that Elzaki transform method is not only a compatible alternate approach to other analytic methods like Laplace transform method but also simple in application once compared with methods ADM and MSA.展开更多
This paper aims to establish a relative study between a relational Microsoft SQL Server database and a non-relational MongoDB database within the unstructured representation of data in JSON format. There is a great am...This paper aims to establish a relative study between a relational Microsoft SQL Server database and a non-relational MongoDB database within the unstructured representation of data in JSON format. There is a great amount of work done regarding comparison of multiple database management applications on the basis of their performances, security etc., but we have limited information available where these databases are assessed on the basis of provided data. This study will mainly focus on looking at all the possibilities that both these database types offer us when handling data in JSON. We will accomplish this by implementing a series of experiments while taking into consideration that the subjected data does not require to be normalized;and therefore, evaluate the outcome to conclude the result.展开更多
Hepatitis C is a contagious blood-borne infection,and it is mostly asymptomatic during the initial stages.Therefore,it is difficult to diagnose and treat patients in the early stages of infection.The disease’s progre...Hepatitis C is a contagious blood-borne infection,and it is mostly asymptomatic during the initial stages.Therefore,it is difficult to diagnose and treat patients in the early stages of infection.The disease’s progression to its last stages makes diagnosis and treatment more difficult.In this study,an AI system based on machine learning algorithms is presented to help healthcare professionals with an early diagnosis of hepatitis C.The dataset used for our Hep-Pred model is based on a literature study,and includes the records of 1385 patients infected with the hepatitis C virus.Patients in this dataset received treatment dosages for the hepatitis C virus for about 18 months.A former study divided the disease into four main stages.These stages have proven helpful for doctors to analyze the liver’s condition.The traditional way to check the staging is the biopsy,which is a painful and time-consuming process.This article aims to provide an effective and efficient approach to predict hepatitis C staging.For this purpose,the proposed technique uses a fine Gaussian SVM learning algorithm,providing 97.9%accurate results.展开更多
文摘Volterra type integral equations have diverse applications in scientific and other fields. Modelling physical phenomena by employing integral equations is not a new concept. Similarly, extensive research is underway to find accurate and efficient solution methods for integral equations. Some of noteworthy methods include Adomian Decomposition Method (ADM), Variational Iteration Method (VIM), Method of Successive Approximation (MSA), Galerkin method, Laplace transform method, etc. This research is focused on demonstrating Elzaki transform application for solution of linear Volterra integral equations which include convolution type equations as well as one system of equations. The selected problems are available in literature and have been solved using various analytical, semi-analytical and numerical techniques. Results obtained after application of Elzaki transform have been compared with solutions obtained through other prominent semi-analytic methods i.e. ADM and MSA (limited to first four iterations). The results substantiate that Elzaki transform method is not only a compatible alternate approach to other analytic methods like Laplace transform method but also simple in application once compared with methods ADM and MSA.
文摘This paper aims to establish a relative study between a relational Microsoft SQL Server database and a non-relational MongoDB database within the unstructured representation of data in JSON format. There is a great amount of work done regarding comparison of multiple database management applications on the basis of their performances, security etc., but we have limited information available where these databases are assessed on the basis of provided data. This study will mainly focus on looking at all the possibilities that both these database types offer us when handling data in JSON. We will accomplish this by implementing a series of experiments while taking into consideration that the subjected data does not require to be normalized;and therefore, evaluate the outcome to conclude the result.
文摘Hepatitis C is a contagious blood-borne infection,and it is mostly asymptomatic during the initial stages.Therefore,it is difficult to diagnose and treat patients in the early stages of infection.The disease’s progression to its last stages makes diagnosis and treatment more difficult.In this study,an AI system based on machine learning algorithms is presented to help healthcare professionals with an early diagnosis of hepatitis C.The dataset used for our Hep-Pred model is based on a literature study,and includes the records of 1385 patients infected with the hepatitis C virus.Patients in this dataset received treatment dosages for the hepatitis C virus for about 18 months.A former study divided the disease into four main stages.These stages have proven helpful for doctors to analyze the liver’s condition.The traditional way to check the staging is the biopsy,which is a painful and time-consuming process.This article aims to provide an effective and efficient approach to predict hepatitis C staging.For this purpose,the proposed technique uses a fine Gaussian SVM learning algorithm,providing 97.9%accurate results.
