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Wave shoaling, which involves an increase in wave amplitude due to changes in water depth, can damage shorelines. To mitigate this damage, we propose using porous structures such as mangrove forests. In this study, we use a mathematical model to examine how mangroves, acting as porous breakwater, can reduce wave shoaling amplitude. The shallow water equations are used as the governing equations and are modified to account for the presence of porous media. To measure the wave reduction generated by the porous media, the wave transmission coefficient is estimated using analytical and numerical approaches. The separation of variables method and the staggered finite volume method are utilized for each approach, respectively. The numerical results are then validated against the previously obtained analytical solutions. We then vary the friction and porosity parameters—determined by the presence and extent of porous media, to evaluate their effectiveness in reducing wave shoaling.

There are motor vehicle tax arrears in Pontianak which are increasing every year so it is necessary to examine whether the consumptive factor hanging around taxpayers can influence taxpayer compliance. This research aims to explore the influence of a consumer lifestyle, especially in the context of hanging out activities, on taxpayer compliance in paying Motor Vehicle Tax (PKB) in Pontianak, West Borneo. The research method used in this research is descriptive quantitative. The data used is primary data using a questionnaire via Google Form. The population of this study were taxpayers who were registered and domiciled in Pontianak, West Kalimantan with a sample size of 191 people and used a simple random sampling method. This research data was tested using the SPSS version 29 software. The analytical method used are Linear Multiple Regression and Moderated Regression Analysis (MRA). The results show that the variables of hanging out and group hanging out behavior have a significant effect on compliance with paying PKB. However, the frequency of hanging out and spending on hanging out activities did not show a significant influence. Tax awareness does not significantly moderate the relationship between hanging out variables and tax compliance. The implication of this research is to encourage the implementation of an approach that is more focused on utilizing social norms and social interactions in community hangout culture to strengthen tax awareness and obligations, especially related to motor vehicle taxpayer compliance.

Background Hormonal changes in pregnancy and their induced effect on periodontal health are well documented. The present study is aimed at the potential repercussions of multiple pregnancies on periodontal health. Materials and methods Our study utilized data from key sections of the NHANES. All the pertaining and relevant data for the study is collected. Our exposure variable was the number of pregnancies, and the outcome variable was periodontal disease. The number of pregnancies is classified as one, two, three, four, or more. Age, gender, race/ethnicity, education, poverty/income ratio, marital status, and other variables. Multiple logistic regression models were employed to assess the impact of multiple pregnancies on periodontal disease. Result The crude and multiple logistic regression analyses revealed that none of the variables were significantly associated with the prevalence of periodontitis. In univariate analysis, patients with one or two pregnancies had higher odds of experiencing periodontitis (OR 1.154, 95% CI 0.748-1.779), (OR 1.464, 95% CI 0.864-2.483) respectively. However, these associations did not reach statistical significance. Conclusion Within the limitation of the study, there is no significant relationship between parity and the prevalence of periodontitis, the longitudinal study may be warranted to delve deeper into any potential associations.

This research delves into the radial vibrations of dissipative poroelastic spherical shells, which are embedded within an elastic foundation and subjected to rotational dynamics. The analysis identifies that the inclusion of dissipative effects gives rise to a transcendental, complex-valued frequency equation. A numerical approach, specifically the bisection method, is employed in MATLAB for solution derivation. In instances where the argument is relatively small, the study leverages the asymptotic expansions of Bessel functions, facilitating the bifurcation of the frequency equation into two distinct real-valued equations. These equations are instrumental in computing the natural frequency as a function of the shell’s thickness. Furthermore, the research rigorously examines how rotational forces influence the natural frequency. The culmination of this study is presented through a series of graphical depictions, which succinctly illustrate the impact of rotational dynamics on the radial vibrations of thick-walled hollow structures situated in various elastic media. The overall findings contribute significantly to our understanding of the behavior of poroelastic materials in rotational environments, with implications for both theoretical and practical applications in material science and engineering. The results can benefit the theoretical development of orthopedic study projects connected to spherical poroelastic medium.

Penelitian ini menganalisis pengelolaan keuangan Yayasan Z sesuai ISAK 35 untuk laporan keuangan entitas nirlaba. Yayasan Z, LSM yang fokus pada pemberdayaan masyarakat dan konservasi lingkungan, menjadi objeknya. Metode deskriptif kualitatif dengan pendekatan studi kasus diterapkan, menggunakan teknik interaktif model Miles dan Huberman. Lima narasumber, pengurus Yayasan Z, diwawancarai. Hasilnya menunjukkan bahwa Yayasan Z masih menggunakan format donor untuk laporan keuangan, dengan laporan internal menggunakan format kas kecil dan besar. Implikasinya, laporan keuangan belum sepenuhnya memenuhi standar ISAK 35 sesuai temuan penelitian.

Straw pretreatment enhances the cellulose accessibility and increases the methane yield from anaerobic digestion. This study investigated the effects of alkali pretreatments with different chemical agents (NaOH, KOH, and Na2CO3) on the physicochemical and thermal characteristics of barley straw, as well as methane production from codigestion with sewage sludge. Artificial neural network modeling with a feedforward neural network (FFNN) and slime mold optimization (SMO) techniques were used to predict methane production. NaOH pretreatment was shown to be the best pretreatment for removing hemicellulose and lignin and for increasing the cellulose accessibility. Moreover, there was a 2.57-fold higher level of methane production compared to that from codigestion with untreated straw. The removal ratios for the total solids, volatile solids, and chemical oxygen demand reached 59.3, 67.2, and 73.4%, respectively. The modeling results showed that the FFNN-SMO method can be an effective tool for simulating the methane generation process, since training, validating, and testing produced very high correlation coefficients. The FFNN-SMO accurately predicted the amount of methane produced, with an R2 of 0.998 and a 3.1x10-5 root mean square error (RMSE).

Statistical process control basically involves inspecting a random sample of the output from a process and deciding whether the process is producing products with characteristics that fall within a predetermined range. It is used extensively in the field of reliability engineering. The reliability of the production process is thoroughly monitored for any internal variation using the SPC. The aim is always to settle such variations through a proper control monitoring. If the underlying distribution of the process is known to the researcher than the use of parametric control charts are useful but in many cases when there is doubt about the distribution of the process then it is preferred to use non parametric control charts. In this paper we propose the modified Exponentially weighted moving average (EWMA), Double Exponentially weighted moving average (DEWMA), Hybrid Exponentially weighted moving average (HEWMA), Extended Exponentially weighted moving average (EEWMA), Modified Exponentially weighted moving average (MEWMA) and mix- type control charts by mixing these control charts with Tukey control chart EWMA-TCC, DEWMA-TCC, HEWMA-TCC, EEWMA-TCC, MEWMA-TCC for the shape parameter of the Kumaraswamy Lehmann-2 Power function distribution (KL2PFD).

Diabetes is a chronic disease and a major public health concern all over the world, even when made feasible to learn about the root cause of the disease by awareness along with the methods of prevention. This study introduces a mathematical deterministic model that describes the progression of type 2 diabetes, integrating a component of awareness and a saturation treatment function named Holling type II. The presented work investigates and numerically analyzes the impact of various treatment strategies, such as consistent physical activity, a healthy diet, access to medical services, and the efficacy of treatments. The research findings indicate that the use of Holling type II treatment functions can prevent minor and major complications related to diabetes.

The study and investigation of the behavior of monetary phenomena is an interesting subject for actuaries and practitioners. In the recent age and development in the monetary and financial phenomena, cryptocurrency has gained much attention from actuaries. Over the past decade, several research studies have emerged on modeling and forecasting cryptocurrency exchange rates. This paper also contributes to the modeling of cryptocurrency exchange rates using a new version of the Logistic distribution, namely, a new cotangent-Logistic distribution. The mathematical properties and estimators of the new cotangent-logistic distribution's parameters are obtained. We illustrate the new cotangent-Logistic distribution using two financial data sets representing the log-returns of the Bitcoin and Ethereum prices. We compare the new cotangent-Logistic distribution with the baseline Logistic distribution and its modified version. Using the p-value and three other statistical tests, we show that the new cotangent-Logistic distribution repeatedly provides the optimal fit to cryptocurrency exchange rates.

Smoking exposure among pregnant women is correlated with the risk of low birth weight. The policy factors are believed to contribute to the rate or prevalence of smoking activities. This study aims to simultaneously portray the incidence of low-birth-weight newborns correlated with smoking exposure. The samples were 160 respondents, with 57 and 103 respondents in Hospital A and G respectively. A mixed-method analysis was utilized by combining a retrospective approach to identify the key findings and be equipped with a narrative analysis of the socio-demographic - law enforcement process. The Spearman correlation analysis was used for investigating correlation among variables. Spearman correlation test smoking exposure per day in minutes (rho= -0.595, p

The fractional regularized long wave equation and the fractional nonlinear shallow-water wave equation are the noteworthy models in the domains of fluid dynamics, ocean engineering, plasma physics, and microtubules in living cells. In this study, a reliable and efficient improved F-expansion technique, along with the fractional beta derivative, has been utilized to explore novel soliton solutions to the stated wave equations. Consequently, the study establishes a variety of reliable and novel soliton solutions involving trigonometric, hyperbolic, rational, and algebraic functions. By setting appropriate values for the parameters, we obtained peakons, anti-peakon, kink, bell, anti-bell, singular periodic, and flat kink solitons. The physical behavior of these solitons is demonstrated in detail through three-dimensional, two-dimensional, and contour representations. The impact of the fractional-order derivative on the wave profile is notable and is illustrated through two-dimensional graphs. It can be stated that the newly established solutions might be further useful for the aforementioned domains.

Abstract In distributed networks, wind turbine generators (WTGs) are to be optimally sized and positioned for cost‐effective and efficient network service. Various meta‐heuristic algorithms have been proposed to allocate WTGs within microgrids. However, the ability of these optimizers might not be guaranteed with uncertainty loads and wind generations. This paper presents novel meta‐heuristic optimizers to mitigate extreme voltage drops and the total costs associated with WTGs allocation within microgrids. Arithmetic optimization algorithm (AOA), coronavirus herd immunity optimizer, and chimp optimization algorithm (ChOA) are proposed to manipulate these aspects. The trialed optimizers are developed and analyzed via Matlab, and fair comparison with the grey wolf optimization, particle swarm optimization, and the mature genetic algorithm are introduced. Numerical results for a large‐scale 295‐bus system (composed of IEEE 141‐bus, IEEE 85‐bus, IEEE 69‐bus subsystems) results illustrate the AOA and the ChOA outperform the other optimizers in terms of satisfying the objective functions, convergence, and execution time. The voltage profile is substantially improved at all buses with the penetration of the WTG with satisfactory power losses through the transmission lines. Day‐ahead is considered generic and efficient in terms of total costs. The AOA records costs of 16.575M$/year with a reduction of 31% compared to particle swarm optimization.

The effect of nanoparticle volume concentration on the thermo-physical characteristics of hybrid nanofluid has been a major area of study. Since hybrid nanofluid combines the chmical and physical properties of nanoparticles in a useful way, they overcome the limitations of mono nanofluids. The goal of this work is to examine how the Cu-Al2O3 nanoparticles affect the thermal conductivity, dynamic viscosity and rheological characteristics of kerosene oil-based hybrid nanofluids. The focus on this study is to analyze the magnetized hybrid nanofluid flow over a stretching/shrinking cylinder with the influence of different physical effects. For this, a mathematical model of a hybrid nanofluid is formulated in the form of PDEs. Then these PDEs are converted into ODEs by applying similarity conversion and tackled numerically. To understand the flow behavior, friction drag enhancement, thermal distribution, and heat transport phenomenon of Cu-Al2O3/kerosene oil, the graphical results are sketched. The results show that nanoparticle inclusion boosts the skin friction coefficient and heat transport rate. Here, ϕ1 , ϕ2 symbolize the Copper ϕCu and Aluminum Oxide ϕAl2O3 volume fractions, respectively. It is discovered that the values of Re1/2Cf and Re−1/2Nu grow when the values of nanoparticles volume fractions ϕ1 , ϕ2 increase. Further, increasing magnetic strength lowers the fluid velocity and increases the thermal distribution of the liquid. Additionally, the temperature of the liquid is increased by rising Biot number and thermal radiation, respectively.

The current manuscript critically examines the propagation of horizontally polarized shear waves on the dispersion of a highly inhomogeneous thin bonded bi-material plate when a load due to the Winkler's elastic foundation is prescribed. An analytical procedure of solution is deployed for the study; in addition to the exploitation of effective boundary conditions approach for the asymptotic examination. The overall inference of the current study is the realization of the fact that the vibrational displacements in both layers are enhanced by an increase in the inhomogeneity parameter; at the same time lessened with an increment in the foundation parameter. Moreover, a perfect approximation of the dispersion relation has been realized, with its validity extending to almost the entire low-frequency range. Lastly, the influence of the material inhomogeneity has been noted to affect fundamental mode, as against the presence of the foundation parameter which affects the first harmonic curve. More so, an increase in the two parameters narrows the chances of low-frequency propagation.

The current study addresses the flow of steady electrically conducting hybrid nanofluid (HNF) across an impermeable slender stretchable sheet. The flow distribution takes into consideration the effects of variable magnetic fields, heat production, Hall current and chemical reactions. A computational model is established for the purpose to amplify the energy communication rate and enhance the productivity and performance of thermal energy propagation for several industrial and biological purposes. The hybrid nanofluid is comprised of silver and magnesium oxide nanomaterials in the working fluid water. Among transition metals and alloys, magnesium oxide and silver nanoparticles (NPs) have been extensively documented to have broad-spectrum antibacterial properties. Silver NPs are the most extensively employed inorganic NP, having several applications in biomaterial detection and antibacterial actions. The scenario has been expressed as a system of PDEs. Which are simplified to the system of ODEs through similarity replacements. The computing approach PCM is used to subsequently evaluate the acquired 1st order differential equations. The outcomes are checked with the bvp4c package and existing literature for consistency and validity. It has been noticed that the axial velocity profile enhances with the effect of Hall current m and velocity power index constraint n, while reducing with the variation of nanoparticles volume friction ϕ1,ϕ2 and slender sheet wall thickness parameter δ.

Soil erosion triggers several global environmental and economic problems. The Universal Soil Loss Equation (USLE) and its updates are the most widely used models for soil erosion evaluation. USLE includes several parameters that describe rainfall and soil characteristics. The application of the USLE is challenging due to the variability of accuracy and resolution of the required data for each parameter from one region to another. In the current study, a methodology to collect and process the required data for the USLE is proposed. Remote sensing is utilized to estimate the soil components percentages and land cover. ArcGIS is used to evaluate the topographic slope and length parameters. Lastly, synthetic SCS type II storm distribution is used to distribute the available daily rainfall events to calculate the rainfall erosivity factor. The results showed good agreement between the calculated and measured catchment sediment release for two catchments in the Sinai Peninsula in Egypt.

Background Minimally invasive surgical methods have lately become popular in heart surgery. Ministernotomy and minithoracotomy are the most commonly used incisions in minimally invasive aortic valve replacement. It is still debated if one incision is better than the other. Patients and methods A prospective comparative analysis was used to examine the outcomes of 30 patients who underwent isolated aortic valve replacement. A minimally invasive right anterior minithoracotomy approach was used in group A (n = 15), whereas a mini-upper sternotomy method was used in group B (n = 15). Results The results in both groups reveal no statistical difference. However, the hospital stay, ventilation time, and blood loss had better results in the right minithoracotomy group, whereas in the upper-ministernotomy group, postoperative pain had better results. In group A, blood loss was 335.3174.5, while in group B, it was 433.3 ± 169.5. In group B, postoperative pain was 1.7 ± 0.7, which is better than group A 2.5 ± 0.6. Group B had a longer total hospital stay (7.2 ± 1.3 days) than group A (5.6 ± 0.6 days). In both groups, inotropes were determined to be negligible. Conclusion The results of a right anterior minithoracotomy and an upper-ministernotomy approach in patients undergoing isolated Aortic valve replacement (AVR) are similar, with no notable differences. However, a right anterior minithoracotomy reduces the need for blood transfusions, assisted ventilation time, and hospital stay, while an upper-ministernotomy reduces postoperative pain. Furthermore, the cross-clamping and total operative time is highly significantly increased in right anterior minithoracotomy approach.

Back ground The purpose of this study is to determine the role of the viability study to solve the dilemma of management of moderate ischemic mitral regurgitation (IMR): when to do revascularization alone or revascularization and mitral valve repair?. Patients and methods A retrospective study included 120 patients with ischemic heart disease (IHD) who underwent coronary artery bypass surgery (CABG) with IMR aged from 40 to 65 years of both sexes. They were divided into two groups of patients: Group I: 60 patients with IHD and moderate IMR had CABG for revascularization only. Group II: 60 patients with IHD and moderate IMR had CABG for revascularization combined with mitral valve repair. Preoperative viability was done by MRI study for all patients of moderate IMR, to assess the viability of the posteroinferior wall regardless the ejection fraction of the heart. Results After 1 week, five patients had severe MR in group I, compared with only one patient in group II. In addition, after 6 months, eight patients had severe MR in group I, whereas in group II, only one patient had severe MR. Conclusion Patients with nonviable posteroinferior segment had better results when revascularization was combined with mitral valve repair, than those who only experienced revascularization alone. However, if that territory is viable, the results are similar in both groups.

Background During the past decade, the number of percutaneous coronary interventions (PCI) performed before coronary artery bypass grafting (CABG) has risen significantly. Patients with more serious coronary pathology are referred for CABG, which can affect the postoperative outcome. Patients and methods Outcomes of 60 CABG patients, who were recruited in a prospective comparative study, were compared. Group A (n = 30) underwent primary CABG and group B (n = 30), had prior PCI before CABG. Results Total morbidity was substantially higher in the second group than in the first, with six patients in group A (nonstent group) and 19 patients in group B being affected (stent group). Inotropes and intraaortic balloon pump were used more in the previous PCI community than in group A. Group B had a longer ICU stay (50.45 ± 33.49 h in group A vs. 79.56 ± 60.44 h in group B). Conclusion Previous PCI can have a detrimental effect on the morbidity outcome of the subsequent CABG. However, postoperative mortality has not been affected significantly. Thus, percutaneous coronary revascularization should be carefully weighed against the increased risk of CABG afterward. The guidelines for intervention should be strictly followed, particularly in patients with complex coronary lesions who are more likely to be referred for CABG.

Background In cardiac surgery, minimally invasive surgical procedures have recently been adopted. These innovative procedures have a number of benefits, including less postoperative discomfort, fewer morbidity and mortality, faster recovery, and shorter hospital stays at lower costs. Patients and methods Outcomes of 30 patients who underwent isolated aortic valve replacement, were subjected to a prospective comparative study, were compared. In group A (n = 15) minimally invasive right anterior mini-thoracotomy approach and in group B (n = 15) conventional median sternotomy approach had been used. Results The second group had much higher total morbidity than the first. In group A, blood loss was 335.3 ± 174.5, while in group B, it was 633.3 ± 179.9. In group B, postoperative discomfort was much higher. In both groups, inotropes were determined to be negligible. Group B had a longer total hospital stay (101.7 days) than group A (5.60.6 days). Conclusion In patients undergoing isolated aortic valve replacement, a right anterior mini-thoracotomy lowers postoperative pain, the requirement for blood transfusions, assisted ventilation time, and hospital stay.

The transesterification of Amygdalus scoparia oil to biodiesel was performed and examined through the electrolysis method in the presence of KOH/Al2O3 as a heterogeneous catalyst at room temperature. A KOH/Al2O3 as solid base catalyst was prepared through the impregnation of Al2O3 with KOH solution (concentration of 25g in 100 mL deionized water). The catalyst was analyzed using X-ray diffraction (XRD), scanning electron microscopy (SEM) and Energy-dispersive X-ray spectroscopy (EDS). The transesterification key variables such as reaction time, methanol to oil molar ratio, and catalyst weight were optimized by applying the central composite design (CCD) approach. The maximum yield of 94% was obtained at the methanol to oil ratio of 10:1, catalyst weight of 1.6 wt/v%, voltage of 10 V, a reaction time of 2.30 h, 10 wt% acetone at room temperature (25 ᵒC). The characterizations of Amygdalus scoparia oil and biodiesel were specified using a gas chromatography-mass spectrometry (GC-MS) and Fourier-transform infrared spectroscopy (FTIR) analyses.

Many Chinese cities have severe air pollution due to the rapid development of the Chinese economy, urbanization, and industrialization. Particulate matter (PM2.5) is a significant component of air pollutants. It is related to cardiopulmonary and other systemic diseases because of its ability to penetrate the human respiratory system. Forecasting air PM2.5 is a critical task that helps governments and local authorities to make necessary plans and actions. Thus, in the current study, we develop a new deep learning approach to forecast the concentration of PM2.5 in three major cities in China, Beijing, Shijiazhuang, and Wuhan. The developed model is based on the Informer architecture, where the attention distillation block is improved with a residual block-inspired structure from efficient networks, and we named the model ResInformer. We use air quality index datasets that cover 98 months collected from 1 January 2014 to 17 February 2022 to train and test the model. We also test the proposed model for 20 months. The evaluation outcomes show that the ResInformer and ResInformerStack perform better than the original model and yield better forecasting results. This study’s methodology is easily adapted for similar efforts of fast computational modeling.

In this paper, long-wave anti-plane shear motion in a multilayered laminate composed of pre-stressed compressible elastic layers is investigated. The layers of the laminate are perfectly bonded, while a fixed-free boundary condition is prescribed on the outer faces of the laminate. The solution of the model is determined analytically via the propagator matrix and numerically through the asymptotic approach. Moreover, the numerical results featuring harmonic curves are presented graphically, together with an asymptotic long-wave analysis of the vibration modes. As a special case of materials, linear isotropic with one shear modulus is considered. A polynomial long-wave low-frequency approximation of the related dispersion relation is also studied. It governs dispersion curves including the lowest harmonic. It is revealed that a low-frequency mode exists in both the two- and three-layered laminates, which are taken as prototypical structures. Lastly, comparisons between the exact and approximate asymptotic results are presented, and excellent agreement is observed.

The purpose of this study was to analyze the distribution dynamics and TSS concentrations based on four different seasons and different years for five years. Image processing of TSS included Correction with Dark Object Substraction and Atmospheric correction method, and Syarif Budhiman algorithm used to extract TSS. The image processing of coastal ecosystem was composed of eight main steps including: atmospheric correction, cropping, masking, depth invariant index, Unsupervised Classification, ground truthing, reclassify, and accuracy assessment. The distribution of suspended sediments is the highest and dominant content in the coastal area adjacent to the river estuary. In addition, based on quality standards for marine biota and TSS values for fisheries purposes, it can be revealed that the fertility of Spermonde coastal waters crosses the quality standard and is not good for fisheries activities.

This study analyses changes in shoreline and mangroves status at the gulf coast of Sayung-Demak, Indonesia. Data on shoreline changes were from high-resolution imagery in 2005, 2010 and 2017 by ArcGIS 10.3, while mangrove diversity data were observed from field studies using the transect method at three locations at the Semarang-Demak beach frontier. Based on the analysis and calculations, it was found that the coastline was decline by 0.49 km from 2005 to 2010, and incline by 3.30 km from 2010 to 2017. Abrasion occurred was 285.07 ha and accretion of 2.40 ha. The composition of mangroves on the border of Semarang-Demak consists of A. alba, A. marina, R. mucronata, R. stylosa, S. casseolaris. For this reason, it is necessary to monitor changes in shoreline and the status of mangroves on the Semarang-Demak border. In addition, it is essential to do integrated environmental management in coping with abrasion.

In this paper, we study the applications of metaheuristics (MH) optimization algorithms in human activity recognition (HAR) and fall detection based on sensor data. It is known that MH algorithms have been utilized in complex engineering and optimization problems, including feature selection (FS). Thus, in this regard, this paper used nine MH algorithms as FS methods to boost the classification accuracy of the HAR and fall detection applications. The applied MH were the Aquila optimizer (AO), arithmetic optimization algorithm (AOA), marine predators algorithm (MPA), artificial bee colony (ABC) algorithm, genetic algorithm (GA), slime mold algorithm (SMA), grey wolf optimizer (GWO), whale optimization algorithm (WOA), and particle swarm optimization algorithm (PSO). First, we applied efficient prepossessing and segmentation methods to reveal the motion patterns and reduce the time complexities. Second, we developed a light feature extraction technique using advanced deep learning approaches. The developed model was ResRNN and was composed of several building blocks from deep learning networks including convolution neural networks (CNN), residual networks, and bidirectional recurrent neural networks (BiRNN). Third, we applied the mentioned MH algorithms to select the optimal features and boost classification accuracy. Finally, the support vector machine and random forest classifiers were employed to classify each activity in the case of multi-classification and to detect fall and non-fall actions in the case of binary classification. We used seven different and complex datasets for the multi-classification case: the PAMMP2, Sis-Fall, UniMiB SHAR, OPPORTUNITY, WISDM, UCI-HAR, and KU-HAR datasets. In addition, we used the Sis-Fall dataset for the binary classification (fall detection). We compared the results of the nine MH optimization methods using different performance indicators. We concluded that MH optimization algorithms had promising performance in HAR and fall detection applications.

The current study examines the propagation of surface waves in an asymmetric rotating doubly coated nonhomogeneous half space. The coating layers are assumed to be made of different homogeneous isotropic materials, while the overlaying nonhomogeneous half space layer is considered to be of exponentially varying material properties. The consequential exact vibrational displacements and dispersion relation are determined analytically, in addition to the approximate validation of the dispersion relation via the application of an asymptotic procedure within the long wave limit. Two cases of unloaded and loaded end surface scenarios are analyzed by examining the posed fundamental modes. More precisely, an elastic Winkler foundation was considered in the case of a mechanically loaded end surface condition and was found to proliferate the transition between having a fundamental mode over the frequency axis to the wave number axis as the angular velocity increased. Moreover, the rotational effect was found to have a direct impact on the surface wave propagation with a long wave and low frequency. Aside from that, an increase in the nonhomogeneity parameter resulted in propagation with a relatively long frequency.