Machine Learning Approaches for Heart Disease Detection: A Comprehensive Review

This paper presents a comprehensive review of the application of machine learning algorithms in the early detection of heart disease. Heart disease remains a leading global health concern, necessitating efficient and accurate diagnostic methods. Machine learning has emerged as a promising approach, offering the potential to enhance diagnostic accuracy and reduce the time required for assessments. This review begins by elucidating the fundamentals of machine learning and provides concise explanations of the most prevalent algorithms employed in heart disease detection. It subsequently examines noteworthy research efforts that have harnessed machine learning techniques for heart disease diagnosis. A detailed tabular comparison of these studies is also presented, highlighting the strengths and weaknesses of various algorithms and methodologies. This survey underscores the significant strides made in leveraging machine learning for early heart disease detection and emphasizes the ongoing need for further research to enhance its clinical applicability and efficacy

Development and construction of rotating polarizer analyzer ellipsometer

A detailed mathematical derivation and an experimental characterization of one to two ratio rotating polarizer analyzer ellipsometer (RPAE) are presented. The alignment, calibration, and testing of reference samples are also discussed. The optical properties of some known materials obtained by the proposed ellipsometer will be shown and compared to accepted values. Moreover, the constructed ellipsometer will be tested using two ellipsometry standards with different thicknesses

Theoretical spectroscopic scan of the sensitivity of asymmetric slab waveguide sensors

An extensive theoretical analysis is carried out to investigate the variation of the sensitivity of optical slab waveguide sensors with the wavelength of the guided wave. We consider a three-layer waveguide as an optical sensor. The sensitivity for both polarizations of light: s-polarized light (TE) and p-polarized light (TM), is derived using the characteristic equation of the structure. The dispersion of the materials is taken into account to study the sensitivity spectroscopic scan over the near IR-range from 1.2–2 µm. It is found that an optimum wavelength exists for each guiding layer thickness and this optimum value increases linearly with the thickness of the guiding layer

Comparing optical sensing using slab waveguides and total internal reflection ellipsometry

The sensitivity of the effective refractive index of slab waveguide sensors to variations in the refractive index of the cladding is compared to that of the ellipsometric parameters. The changes of the effective refractive index of a waveguide and the ellipsometric parameter\Delta, due to the index change of the cladding, were derived and plotted as a function of the guiding layer thickness and with the index of the cladding. It is found that these changes almost have the same overall feature but the ellipsometric parameters showed considerable higher sensitivity than the effective index of the conventional waveguide optical sensors

PCR-based assay for the rapid and precise distinction of Pseudomonas aeruginosa from other Pseudomonas species recovered from burns patients

Background. Pseudomonas aeruginosa is an important lifethreatening nosocomial pathogen which plays a prominent role in wound infections in burns patients. We designed this study to identify the isolates of P. aeruginosa recovered from burns patients at the genus and species levels by means of primers targeting oprI and oprL genes. Methods. During a 5-month period, wound samples were taken from burns patients and plated on MacConkey agar. All suspected colonies were screened for P. aeruginosa by means of a combination of phenotype tests. Specific primers for oprI and oprL genes were then used for the molecular identification of colonies. Results. During the 5-month period, bacterial isolates recovered from burn wound infections were analyzed. Phenotype identification tests identified 171 (34.8) P. aeruginosa isolates. However, molecular techniques that used species-specific primers to detect the amplicon of the oprL gene confirmed the exact identification of P. aeruginosa in only 133 cases; in the other isolates, the use of genus-specific primers detected the amplicon of the oprI gene, which confirmed the identification of fluorescent pseudomonads. Conclusions. This study indicates that molecular detection by means of an assay targeting the oprL gene is a useful technique for the rapid and precise detection of P. aeruginosa in burns patients. In addition to phenotype testing, PCR detection should be carried out in order to promptly ascertain the best aggressive antibiotic therapy for P. aeruginosa infections, thereby significantly improving clinical outcomes

Vibration Control for a Coupled Pitch- roll Ship Model Via a Negative Cubic Velocity Feedback Control

One of the most essential ship reactions to waves is roll motion. Due to the intricacy of ship wave interactions and their sensitivity, predicting such a reaction is extremely challenging. Because vibration motion is an undesirable occurrence, it must be removed, decreased, or controlled. A coupled Pitch- roll ship model with negative cubic velocity feedback control subjected to parametric excitations is premeditated and solved in this paper. The method of multiple time scales is applied to scrutinize the response of the two modes of the system neighbouring the simultaneous sub-harmonic, and internal resonance situation. Besides, the steady-state solution is determined through the Rung-Kutta Method (RKM) of fourth order. Stability of the steady state solution near this resonance case is discussed and studied applying Lyapunov’s first indirect method and Routh- Hurwitz criterion. The influences of the different parameters on the steady state solution are reconnoitred and discussed. The controller effects on the stability are clarified. Simulation results are accomplished with the help of MATLAB and Maple software programs

Numerical Solutions for the Time and Space Fractional Nonlinear Partial Differential Equations

We implement relatively analytical techniques, the homotopy perturbation method, and variational iteration method to find the approximate solutions for time and space fractional Benjamin-Bona Mahony equation. The fractional derivatives are described in the Caputo sense. These methods are used in applied mathematics to obtain the analytic approximate solutions for the nonlinear Bejamin-Bona Mahoney (BBM) partial fractional differential equation. We compare between the approximate solutions obtained by these methods. Also, we present the figures to compare between the approximate solutions. Also, we use the fractional complex transformation to convert nonlinear partial fractional differential equations to nonlinear ordinary differential equations. We use the improved -expansion function method to find exact solutions of nonlinear fractional BBM equation

Networking historic environmental standards to address modern challenges for sustainable conservation in HBIM

Awareness of the logic and context of original (and subsequent) design priorities is critical to informing decisions relating to valorisation, repair, refurbishment, energy retrofit or re-use of built heritage. A key benefit of collating data through Historic Building Information Modelling (HBIM) should be to assist others facing similar challenges. Here, examples for sharing understanding of how components belong to a system are outlined in the context of a newly completed dataset of public library buildings in the UK funded by Andrew Carnegie, predominantly built between 1900 and 1914. Demands for the functionality and economy of public library buildings, coupled with the emergent standardisation of building components at the time, provide a specific condition with potential for further iteration to other buildings of the period or related typologies. The work highlights the urgency of providing cost-efficient knowledge sharing structures in an era of altered priorities with respect to energy use for modern heritage. We propose the means for mapping common features to network knowledge amongst stakeholders through relevant open source pathways. The results demonstrate that integrating geographic approaches to knowledge sharing in HBIM with environmental considerations also supports wider questions of risk management related to the stewardship of historic buildings in the context of climate change