A Proposed Framework to Improve Diagnosis of Covid-19 Based on Patient’s Symptoms using Feature Selection Optimization

Recently, an epidemic called COVID-19 appeared, and it was one of the largest epidemics that affected the world in all economic, educational, health, and other aspects due to its rapid spread worldwide. The surge in infection rates made traditional diagnostic methods ineffective. Systems for automatic diagnosis and detection are crucial for controlling the outbreak. Other than PCR-RT, further diagnostic and detection techniques are needed. Individuals who receive positive test results often experience a range of symptoms, ranging from mild to severe, including coughing, fever, sore throats, and body pains. In more extreme cases, infected individuals may exhibit severe symptoms that make breathing challenging, ultimately leading to catastrophic organ failure. A hybrid approach called SDO-NMR-Hill has been developed for diagnosing COVID-19 based on a patient’s initial symptoms. This approach incorporates traits from three models, including two distinct feature selection optimization methods and a local search. Supply-demand optimization and the naked mole rat were preferred among metaheuristic methods because they have fewer parameters and a lower computing overhead, which can help you find superfluous and uninformative characteristics. Hill climbing was preferred among local search methods to maximize a criterion among several candidate solutions. We used decision trees, random forests, and adaptive boosting machine-learning classifiers in various experiments on three COVID-19 datasets. We carried out a natural selection of the classifier’s hyper-parameters to optimize outcomes. The optimal performance was attained using the adaptive boosting classifier, with an accuracy of 88.88% and 98.98% for the first and third datasets, respectively. The optimal performance for the second dataset was attained using the random forest classifier, with an accuracy of 97.97%. The suggested SDO-NMR-Hill model is evaluated using nine benchmark UCI datasets, and 15 different optimization techniques are contrasted

Interactive Bi-Level Multi-Objective Integer Non-linear Programming Problem

Abstract This paper presents a bi-level multi-objective integer non-linear programming (BLMINP) problem with linear or non-linear constraints and an interactive algorithm for solving such model. At the first phase of the solution algorithm to avoid the complexity of non convexity of this problem, we begin by finding the convex hull of its original set of constraints using the cutting-plane algorithm to convert the BLMINP problem to an equivalent bi-level multi-objective non-linear programming (BLMNP) problem. At the second phase the algorithm simplifies an equivalent (BLMNP) problem by transforming it into separate multi-objective decision-making problems with hierarchical structure, and solving it by using ε -constraint method to avoid the difficulty associated with non-convex mathematical programming. In addition, the author put forward the satisfactoriness concept as the first-level decision-maker preference. Finally, an illustrative numerical example is given to demonstrate the obtained results. Mathematics Subject Classification: 90C29; 90C30; 41A58; 90C1

Multi-level Multi-objective Quadratic Fractional Programming Problem with Fuzzy Parameters: A FGP Approach

The motivation behind this paper is to present multi-level multi-objective quadratic fractional programming (ML-MOQFP) problem with fuzzy parameters in the constraints. ML-MOQFP problem is an important class of non-linear fractional programming problem. These type of problems arise in many fields such as production planning, financial and corporative planning, health care and hospital planning. Firstly, the concept of the -cut and fuzzy partial order relation are applied to transform the set of fuzzy constraints into a common crisp set. Then, the quadratic fractional objective functions in each level are transformed into non-linear objective functions based on a proposed transformation. Secondly, in the proposed model, separate non-linear membership functions for each objective function of the ML-MOQFP problem are defined. Then, the fuzzy goal programming (FGP) approach is utilized to obtain a compromise solution for the ML-MOQFP problem by minimizing the sum of the negative deviational variables. Finally, an illustrative numerical example is given to demonstrate the applicability and performance of the proposed approach

Dynamics of Decision Making in Traditional Companies Using Three-Level Quadratic Programming Problem with Random Rough Coefficient in Constraints

This paper presents three-level quadratic programming problem with random rough coefficient in constrains. At the first phase of the solution algorithm, and to avoid the complexity of this problem, we begin with converting the rough nature in constraints into equivalent crisp form. At the second phase, a membership function is constructed to develop a fuzzy model for obtaining the optimal solution of the three-level quadratic programming problem. An auxiliary problem is discussed as well as an example is presented

Measuring the technical efficiency of local banks in UAE using rough bi-level linear programming technique

The aim of this paper is to use a bi-level linear programming technique with rough parameters in the constraints, for measuring the technical efficiency of local banks in UAE and Egypt, while the proposed linear objective functions will be maximized for different goals. Based on Dauer's and Krueger's goal programmingmethod, the described approach was developed to deal with the bi-level decision-making problem. The concept of tolerance membership function together was used to generate the optimal solution for the problem under investigation. Also an auxiliary problem is discussed to illustrate the functionality of the proposed approach

Assessing architectural evolution: A case study

This is the post-print version of the Article. The official published can be accessed from the link below - Copyright @ 2011 SpringerThis paper proposes to use a historical perspective on generic laws, principles, and guidelines, like Lehman’s software evolution laws and Martin’s design principles, in order to achieve a multi-faceted process and structural assessment of a system’s architectural evolution. We present a simple structural model with associated historical metrics and visualizations that could form part of an architect’s dashboard. We perform such an assessment for the Eclipse SDK, as a case study of a large, complex, and long-lived system for which sustained effective architectural evolution is paramount. The twofold aim of checking generic principles on a well-know system is, on the one hand, to see whether there are certain lessons that could be learned for best practice of architectural evolution, and on the other hand to get more insights about the applicability of such principles. We find that while the Eclipse SDK does follow several of the laws and principles, there are some deviations, and we discuss areas of architectural improvement and limitations of the assessment approach

Observation of Parity Nonconservation in Moller Scattering

We report a measurement of the parity-violating asymmetry in fixed target electron-electron (Moller) scattering: A_PV = -175 +/- 30 (stat.) +/- 20 (syst.) parts per billion. This first direct observation of parity nonconservation in Moller scattering leads to a measurement of the electron's weak charge at low energy Q^e_W = -0.053 +/- 0.011. This is consistent with the Standard Model expectation at the current level of precision: sin^2\theta_W(M_Z)_MSbar = 0.2293 +/- 0.0024 (stat.) +/- 0.0016 (syst.) +/- 0.0006 (theory).Comment: Version 3 is the same as version 2. These versions contain minor text changes from referee comments and a change in the extracted value of Q^e_W and sin^2\theta_W due to a change in the theoretical calculation of the bremsstrahulung correction (ref. 16

Precision Measurement of the Weak Mixing Angle in Moller Scattering

We report on a precision measurement of the parity-violating asymmetry in fixed target electron-electron (Moller) scattering: A_PV = -131 +/- 14 (stat.) +/- 10 (syst.) parts per billion, leading to the determination of the weak mixing angle \sin^2\theta_W^eff = 0.2397 +/- 0.0010 (stat.) +/- 0.0008 (syst.), evaluated at Q^2 = 0.026 GeV^2. Combining this result with the measurements of \sin^2\theta_W^eff at the Z^0 pole, the running of the weak mixing angle is observed with over 6 sigma significance. The measurement sets constraints on new physics effects at the TeV scale.Comment: 4 pages, 2 postscript figues, submitted to Physical Review Letter

Measurement of high-p_T Single Electrons from Heavy-Flavor Decays in p+p Collisions at sqrt(s) = 200 GeV

The momentum distribution of electrons from decays of heavy flavor (charm and beauty) for midrapidity |y| < 0.35 in p+p collisions at sqrt(s) = 200 GeV has been measured by the PHENIX experiment at the Relativistic Heavy Ion Collider (RHIC) over the transverse momentum range 0.3 < p_T < 9 GeV/c. Two independent methods have been used to determine the heavy flavor yields, and the results are in good agreement with each other. A fixed-order-plus-next-to-leading-log pQCD calculation agrees with the data within the theoretical and experimental uncertainties, with the data/theory ratio of 1.72 +/- 0.02^stat +/- 0.19^sys for 0.3 < p_T < 9 GeV/c. The total charm production cross section at this energy has also been deduced to be sigma_(c c^bar) = 567 +/- 57^stat +/- 224^sys micro barns.Comment: 375 authors from 57 institutions, 6 pages, 3 figures. Submitted to Physical Review Letters. Plain text data tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.htm