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• Open Access   Article

  Bi-Weighted Graph-Based Optimal Path Selection for a Network

  Laxminarayan Sahoo, Rakhi Das, Sovan Samanta

  Research Paper | Journal-Paper (IJSRMSS)

  Vol.10 , Issue.4 , pp.1-8, Aug-2023

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  Abstract
  With the aid of the Bi-Weighted Graph concept, this research attempts to determine the most effective path (optimal path) for a transportation network. Identifying the most effective path (a low-risk path over the network that traverses the shortest or nearly shortest distance) from a source node to the destination node is commonly referred to as optimal path selection. We have used a kind of shortest path algorithm known as the Dijkstra Algorithm to select the shortest path. Here, we have utilized the risk matrix to determine the risk of the path in a network. Due to risk factors that we commonly ignore, it sometimes becomes apparent that the shortest path is not always the most effective or "best path" of a network. Therefore, we have considered a path`s risk factor in this study when figuring out the best network path. The road network system has been imitated in this paper utilizing the idea of a bi-weighted graph, and the shortest path through it has been identified. In this scenario, we have used an actual transportation network for illustration purposes and the estimated outcomes have been presented.

  Key-Words / Index Term
  Shortest path algorithm, Bi-weighted graph, Optimal Path, Risk matrix

  References
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  Citation
  Laxminarayan Sahoo, Rakhi Das, Sovan Samanta, "Bi-Weighted Graph-Based Optimal Path Selection for a Network," International Journal of Scientific Research in Mathematical and Statistical Sciences, Vol.10, Issue.4, pp.1-8, 2023

• Open Access   Article

  Coordinate Transformation of GPS Measurement Results using the Cartesian-to-Ellipsoidal Transformation System

  Thomas U. Omali

  Research Paper | Journal-Paper (IJSRMSS)

  Vol.10 , Issue.4 , pp.9-13, Aug-2023

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  Abstract
  GPS is generally applied in geodetic techniques for determining the three-dimensional location of points on the earth’s surface. While the points are fixed in a global geocentric coordinate system, most work requires positional data based on the local coordinate system in terms of geodetic or local plane coordinates. As a result, conversion of coordinates of points from the geocentric coordinate system to the geodetic coordinate system becomes a necessity. It is normally achieved by using the method of coordinate transformation based on a mathematical model that creates a geometrical link between the coordinates of points in different reference frames. This study is aimed at the transformation of Global Positioning System measurement results based on the Cartesian-to-Ellipsoidal transformation model. Specifically, the iterative and closed-form solutions are presented. It was revealed that using the closed-form systems are fast and effective because the used parameters are directly recovered by using precise formulae without solving any nonlinear equation. However, the iterative algorithms has shown more advantages as it can produce precise information about the unknowns.

  Key-Words / Index Term
  Closed solution, iterative solution, local coordinate system, transformation parameters, WGS-84, reference frame

  References
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  Citation
  Thomas U. Omali , "Coordinate Transformation of GPS Measurement Results using the Cartesian-to-Ellipsoidal Transformation System," International Journal of Scientific Research in Mathematical and Statistical Sciences, Vol.10, Issue.4, pp.9-13, 2023

• Open Access   Article

  Modeling Cash Conversion Cycle on Hospital Performance with Machine Learning Feature Selection Techniques: Subset Selection and Shrinkage Methods

  Richmond Essieku, Solomon Eshun, Eric Ayamga, Prince Bosompim, James Ladzekpo, Makafui Komla Akatu

  Research Paper | Journal-Paper (IJSRMSS)

  Vol.10 , Issue.4 , pp.14-22, Aug-2023

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  Abstract
  In data science, model selection instability is a major concern, especially when dealing with a high number of features. This paper seeks to contribute by empirically modeling the cash conversion cycle on hospital performance using two supervised machine learning feature selection techniques. We employed methods such as best subset selection coupled with an exhaustive search using linear regression and shrinkage methods (Lasso, Ridge, and ElasticNet) to model a real dataset. The empirical results indicated that the Lasso outperformed the other shrinkage methods in feature selection even though the average root mean squared error (rmse) were close. Again, Account Receivable Days (ARD), Account Payable Days (APD), Inventory Turnover Days (INV), and Debt Ratio were found to be predictors of hospital performance, which are components of the Cash Conversion Cycle. Finally, the results show that, on average, a day decrease in the hospital’s collection period will decrease performance by 1%, and a one-unit increase in a day in the account payable decrease performance by 0.003 times.

  Key-Words / Index Term
  Cash Conversion Cycle, Machine Learning, Modeling, Subset Selection, Shrinkage Methods, Hospital performance

  References
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  Citation
  Richmond Essieku, Solomon Eshun, Eric Ayamga, Prince Bosompim, James Ladzekpo, Makafui Komla Akatu, "Modeling Cash Conversion Cycle on Hospital Performance with Machine Learning Feature Selection Techniques: Subset Selection and Shrinkage Methods," International Journal of Scientific Research in Mathematical and Statistical Sciences, Vol.10, Issue.4, pp.14-22, 2023

• Open Access   Article

  Article on the application of Cauchy–Bunyakovsky–Schwarz Inequality in Simplifying and Solving Inequality Problems

  Toyesh Prakash Sharma, Etisha Sharma

  Research Paper | Journal-Paper (IJSRMSS)

  Vol.10 , Issue.4 , pp.23-29, Aug-2023

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  Abstract
  As it is mentioned in the title that through this article there, we will deal with various problems based on classic Cauchy-Bunyakovsky-Schwarz inequality. Previously we have done work on applications of Jensen inequality and their application. Under the title applications, there we’d discuss two aspects of Jensen’s Inequality which are the application of Jensen`s inequality in proving well-known inequalities such as Köber`s inequality, Jordan’s Inequality etc. and another aspect is the application of Jensen’s Inequality in solving and simplifying problems proposals in the similar manner we are trying to deal problems based upon Cauchy-Bunyakovsky-Schwarz inequality and further there is a section dealing with the problems that reads have to solve.

  Key-Words / Index Term
  Inequality, Cauchy Bunyakovsy Schwarz Inequality, AM-GM inequality, Jensen’s Inequality, Natural Numbers, Variables etc

  References
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  [2]. Toyesh Prakash Sharma, "Article on the applications of the Jensen’s Inequality in Alternative proofs and Problems," International Journal of Scientific Research in Mathematical and Statistical Sciences, Vol.9, Issue.6, pp.36-42, 2022.
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  Citation
  Toyesh Prakash Sharma, Etisha Sharma, "Article on the application of Cauchy–Bunyakovsky–Schwarz Inequality in Simplifying and Solving Inequality Problems," International Journal of Scientific Research in Mathematical and Statistical Sciences, Vol.10, Issue.4, pp.23-29, 2023

• Open Access   Article

  Statistical Models for Predicting the Expected Time of Diabetes Mellitus Using Exponentiated Gamma Distribution

  Ezhilvanan Mani, Kannadasan Karuppaiah, Vinoth Raman

  Research Paper | Journal-Paper (IJSRMSS)

  Vol.10 , Issue.4 , pp.30-34, Aug-2023

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  Abstract
  In order to produce effective medical diagnoses, knowledge discovery from medical datasets is critical. With the rising prevalence of diabetes, which now affects about 346 million people worldwide and more than one-third of whom go undiagnosed in the early stages, there is an urgent need to help medical decision-making. Diabetes mellitus is a chronic disease that has become a major public health issue around the world. The model is used to calculate the diabetes mellitus anticipated time. The analytical findings are supported by numerical examples.

  Key-Words / Index Term
  Non Communicable Diseases, Diabetes mellitus, Expected Time, Threshold and Exponentiated Gamma distribution.

  References
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  [14]. Quan Zou, Kaiyang Qu, Yamei Luo, Dehui Yin, Ying Ju and Hua Tang. Predicting Diabetes Mellitus with Machine Learning Techniques. Frontiers in Genetics, Vol.9, (6), pp.1-10, 2018.
  [15]. Robertson, G., Lehmann, E. D., Sandham, W., and Hamilton, D. “Blood glucose prediction using artificial neural networks trained with the AIDA diabetes simulator: a proof-of-concept pilot study”. J. Electr. Comput. Eng. 2011.
  [16]. Van Dieren S, Beulens JW, van der Schouw YT, Grobbee DE, Neal B. “The global burden of diabetes and its complications: an emerging pandemic”. Eur J Cardiovasc Prevention Rehab. Vol.17, (Suppl 1):S3-8, 2010.
  [17]. Yanan Z. “Research on risk prediction of type 2 diabetes mellitus based on data mining technology”. Master Thesis. Yanshan University. 2017.

  Citation
  Ezhilvanan Mani, Kannadasan Karuppaiah, Vinoth Raman, "Statistical Models for Predicting the Expected Time of Diabetes Mellitus Using Exponentiated Gamma Distribution," International Journal of Scientific Research in Mathematical and Statistical Sciences, Vol.10, Issue.4, pp.30-34, 2023

• Open Access   Article

  An Easy Method For Solving nth Order Linear Ordinary Differential Equation with Variable Coefficients

  Toyesh Prakash Sharma, Ankush Kumar Parcha

  Research Paper | Journal-Paper (IJSRMSS)

  Vol.10 , Issue.4 , pp.35-40, Aug-2023

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  Abstract
  With the help of this paper authors are putting forward their findings that makes un an easy method for finding solution of second order linear ordinary differential equations with variable coefficients and third-order linear ordinary differential equations with variable coefficients further applicable for nth order provided there must be some differential relation between introduced coefficients in the given differential equation then only we can solve with the help of here introduced method, the basic idea for reducing second and third order linear ordinary differential equation with variable coefficient is to use well known first order linear differential equation but of course, it limits this method and needs differentiable coefficients. In this paper authors also provide an application part that may help for understanding whether we can apply this method or not!

  Key-Words / Index Term
  Differential Equations, Linear Ordinary Differential Equations, Second Order Linear Ordinary Differential Equations, Third Order Linear Ordinary Differential Equations, Variable Coefficients, First Order Linear Ordinary Differential Equation, nth Order Linear Ordinary Differential Equation.

  References
  [1]. Birkhoff, G. and Rota, G.-C. (1989) Ordinary Differential Equation. 4th Edition, Wily, New York.
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  [6]. T. Bakkyaraj, R. Sahadevan , “An Approximate Solution To Some Classes Of Fractional Nonlinear Partial Differential-Difference Equation Using Adomian Decomposition Method”, Journal of Fractional Calculus and Applications, Vol. 5(1), pp. 37-52. (2014).
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  [9]. Shohal Hossain, Samme Akter Mithy, "Methods for solving ordinary differential equations of second order with coefficients that is constant," International Journal of Scientific Research in Mathematical and Statistical Sciences, Vol.10, Issue.2, pp.9-16, 2023.
  [10]. S. M. Yahya, "Solution of Second-Order Ordinary Differential Equations with Constant Coefficients," International Journal of Mathematics and Mathematical Sciences, vol. 2014, Article ID 121950, 12 pages, 2014. https://doi.org/10.1155/2014/121950.

  Citation
  Toyesh Prakash Sharma, Ankush Kumar Parcha, "An Easy Method For Solving nth Order Linear Ordinary Differential Equation with Variable Coefficients," International Journal of Scientific Research in Mathematical and Statistical Sciences, Vol.10, Issue.4, pp.35-40, 2023

• Open Access   Article

  Existence of Fully and Accurately Defined Systems as Per Gödel’s Incompleteness Theorems

  Sk Asraful Karim

  Review Paper | Journal-Paper (IJSRMSS)

  Vol.10 , Issue.4 , pp.41-46, Aug-2023

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  Abstract
  Gödel’s incompleteness theorems only have implications for the foundations of mathematics and logic. Now if we apply Gödel’s incompleteness theorems to every individual system, we come to know that the definitions (theorems, equations, and laws) are also incomplete and inconsistent for individual systems; in other words, a completely defined system doesn’t exist. For an isolated system: 1. In an isolated system, for any individual system: - For existing definitions: i. The definition of the system is wrong. ii. If the definition is right, then it contradicts the existence of the system. For the process of definition: In the process of defining a system (within an isolated system), the interaction between the definition and the existence of a system goes such a way that: i. The system can change into another system or systems (similar or absolutely different) at the end of the process of definition. ii. The system can change at every step of the definition, ensuring that the definition must be wrong or the existence of the system may hamper iii. If the definition is correct and changing the system is not possible, the system will destroy itself. The ability of a system to change depends on its amount of energy and the possible stages within that energy. A system can’t be changed into any other system; the change is only possible and sustainable if the change or changes do not break the causality. 2. For an open system and a closed system: As open and closed systems interact with their surroundings, their definitions are disrupted by the presence of other systems, while they also react as per the above-mentioned relation as isolated systems do with their definitions.

  Key-Words / Index Term
  Gödel’s Incompleteness Theorems , System, Definition, Incompleteness, Inconsistency, Existence

  References
  [1]K. Gödel, “Über formal unentscheidbare Sätze der Principia Mathematica und verwandter Systeme I,” Monatshefte für Mathematik, Dec. 1931,Volume: 38,Issue: 1,Pages: 173-198doi: 10.1007/bf01700692.
  [2] Gödel, K. ,"On Formally Undecidable Propositions of Principia Mathematica and Related Systems I, “Proceedings of the London Mathematical Society,1931,Volume: 2,Issue: 1,Pages: 5-39
  DOI: N/A
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  Citation
  Sk Asraful Karim, "Existence of Fully and Accurately Defined Systems as Per Gödel’s Incompleteness Theorems," International Journal of Scientific Research in Mathematical and Statistical Sciences, Vol.10, Issue.4, pp.41-46, 2023

• Open Access   Article

  Introducing a Method of Solving Third Order Ordinary Linear Differential Equation with Variable Coefficients

  Toyesh Prakash Sharma

  Research Paper | Journal-Paper (IJSRMSS)

  Vol.10 , Issue.4 , pp.47-52, Aug-2023

  Abstract

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  Citation

  Abstract
  With the help of this paper author is introducing a method of solving third order ordinary linear differential equation with variable coefficients. The method proposed here is generalized method for solving ordinary linear differential equations of third order, but sometimes it becomes difficult

  Key-Words / Index Term
  Differential Equation, Ordinary Differential Equation, Linear Differential Equation, Third Order Ordinary Linear Differential Equation, Integration, Integration by Parts etc.

  References
  [1]. Schrödinger, Erwin . Collected Papers on Wave Mechanics (3rd ed.). American Mathematical Society. ISBN 978-0-8218-3524-1. 1982
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  [6]. Toyesh Prakash Sharma, Etisha Sharma, "Putting Forward Another Generalization of The Class of Exponential Integrals And Their Applications.," International Journal of Scientific Research in Mathematical and Statistical Sciences, Vol.10, Issue.2, pp.5, 2023.
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  [10]. A. Cabada, F. Minhós, and A.I. Santos, Solvability for a third order discontinuous full equation with nonlinear functional boundary conditions, J. Math. Anal. Appl.,322:735–748, 2006.

  Citation
  Toyesh Prakash Sharma, "Introducing a Method of Solving Third Order Ordinary Linear Differential Equation with Variable Coefficients," International Journal of Scientific Research in Mathematical and Statistical Sciences, Vol.10, Issue.4, pp.47-52, 2023