In the shape of an affected person’s proof, the medical report is an ever-developing supply of record for a medical institution. One of the complex issues that get up in the transplanted kidneys is glomerulonephritis. In AI, there are two methodologies: managed and solo mastering. Characterization is a method that falls underneath controlled learning. Out of numerous arrangement models, the maximum prevalently applied is the artificial neural community. While neural networks turn out tremendous in characterization and preparing a device, the precision of the outcome may also anyways be beneath inquiry. The enhancement of the artificial neural networks is completed by using the exactness and space of the result. For this, ANN may be hybridized with a metaheuristic algorithm referred to as the cat swarm optimization (CSO) set of rules. The benefits of optimization artificial neural community are normally the development in the precision of the order, translation of the statistics, and reduction in fee and time utilization for buying real outcomes and so forth within the prevailing study, a correlation between the aftereffects of an ANN decrease again propagation version and the proposed ANN-CSO version is carried out for medical assessment.
This study highlights the importance of entrepreneurial culture in educational institutions as an organization. This study emphasizes the relationship between entrepreneurial culture, entrepreneurship education, and entrepreneurial intention as study variables. This study highlights several aspects: the relationship between variables, study trend, contextual aspect like (country or educational institutions), population, publication type, and study design. A scoping review method is considered for this study based on both Scopus and Web of Science databases. The covered publications in the analyses were for the last 20 years ranging from the year 2003 till August 2021, with no limits on languages. After filtration, the eligible number of studies was (n = 94) out of 180 from both databases. The methodology part contains several sections based on the PRISM-ScR checklist. The findings show a significant relationship among the three variables with the possibility of entrepreneurial culture being a mediator between entrepreneurship education and entrepreneurial intention for future studies, which has not been tested yet. The highest publications werein 2015, especially by European Union countries, as studies in developed countries were more than developing and economies in transition countries. Quantitative studies were more than qualitative and mixed methods, as studies considered HEIs more than schools focusing on students and then teachers. To conclude, policymakers are encouraged to follow policies to improve entrepreneurial culture growth by promoting strategic cooperation among stakeholders and educational institutions implementing several concepts to enhance entrepreneurial culture. Future studies should validate and test these variables’ relationships through a standard and accurate instrument.
Writing anxiety leads to poor writing performance among learners as it hinders their writing. This study investigated the level, types, and causes of writing anxiety among Afghan EFL students. A total of 133 undergraduates was selected as the respondents. The study used a quantitative research method and the data was collected using a questionnaire derived from Second Language Writing Anxiety Inventory and Cause of Writing Anxiety Inventory. Both descriptive and inferential statistics of SPSS were used to analyze the data. The findings of the study indicated a moderate level of writing anxiety, with cognitive anxiety as the dominant type of writing anxiety. In addition, the inferential analysis showed no significant differences in the level of writing anxiety across gender and their years of study. However, a statistically significant difference was found among students from different backgrounds who possessed different English proficiency levels (beginner, intermediate, high-intermediate, and advanced). Moreover, linguistic problems, time pressure, the pressure to be perfect, and the fear of teachers’ negative evaluation were discovered to be the leading causes of writing anxiety. Finally, it is believed that the findings of this study may provide several implications for practitioners in this field to be more aware of students’ writing anxiety in English class. It may alert them of the negative effects of writing anxiety and they may try to make the class as stress-free as possible to improve students’ performance in writing.
Marine gravity anomalies are crucial parameters and elements for determining coastal and ocean geoid, tectonics and crustal structures, as well as offshore studies. This study aims to derive and develop a marine gravity anomaly model over Malaysian seas from multi-mission altimetry data. Universiti Teknologi Malaysia 2020 Mean Sea Surface Model is computed based on along-track data from nine satellite missions, incorporating TOPEX, Jason-1, Jason-2, ERS-2, Geosat Follow on (GFO), Envisat-1, CryoSat-2, SARAL/AltiKa, and Sentinel-3A. The data exploited are from 1993 to 2019 (27 years). Residual gravity anomaly is computed using Gravity Software, and two-dimensional planar Fast Fourier Transformation method is applied. The evaluation, selection, blunder detection, combination, and re-gridding of the altimetry-derived gravity anomalies and Global Geopotential Model data are demonstrated. Cross-validation procedure is employed for data cleaning and quality control using the Kriging interpolation method. Then, cross-validation procedure is applied to the tapering window width 200, which adopting the GECO model denotes the optimum gravity anomaly with root mean square errors in the range of ± 4.2472 mGal to ± 6.0202 mGal. The findings suggest that the estimated marine gravity anomaly is acceptable to be implemented in the marine geoid determination and bathymetry estimation over Malaysian seas. In addition, the results of this study are valuable for geodetic and geophysical applications in marine areas. Along-track altimetry data are used for mean sea surface derivation.Mean sea surface model is utilised in the estimation of marine gravity anomalies.Global Geopotential Model is crucial in the marine gravity estimation of a region. Along-track altimetry data are used for mean sea surface derivation. Mean sea surface model is utilised in the estimation of marine gravity anomalies. Global Geopotential Model is crucial in the marine gravity estimation of a region.
The deployment of smart electricity meter (SEM) via the advanced metering infrastructure (AMI) has come under cyber-attacks as adversaries continue to exploit the communication links for possible evasion of electricity bill payments. Various detection models relying on energy consumption data offer a disadvantage of delayed detection and consequent huge financial losses before frauds are detected. Moreover, existing techniques mostly concentrate on detection of electricity thefts and rely on energy consumption data alone as the basis of theft perpetration whereas other potential parameters which could be exploited for electricity theft prevention exist in AMI. In this study, AMI parameters, which are indicative of electricity thefts are preselected and modelled for electricity theft prevention. First, a given AMI network is sectioned into zones with the selected parameters modelled to define security risks by formulated set of rules based on real-time scenarios. Fuzzy inference system is then employed to model the security risks to ascertain the compromised state of the monitored parameters at the defined scenarios. The result of the developed model at 50% weight of each of the modelled parameters with interdependencies show clear indications of the modelled parameters and their interactions in the determination of risks. The decisions on monitored parameters evaluated at every timestep reveal varied dense velocity behaviours for every scenario. The result is suitable for monitoring the AMI in reporting and/or disconnecting any compromised SEM within a considerable timestep before huge losses are incurred. Implementation of this scheme will contribute a significant success in the attempt to prevent electricity theft perpetration via the AMI.
A porous hollow fibre ceramic membrane derived from a low-cost natural material (silica sand) and fabricated by combine phase inversion and sintering technique followed by fluoroalkylsilane (FAS17) grafting to improve its hydrophobicity is reported in this study. Prior to the subjection of the silica sand ceramic hollow fibre membrane (SSCHFM) to a desalination performance test via direct contact membrane distillation (DCMD), characterization studies were performed on the SSCHFM before and after grafting using different characterization techniques, such as scanning electron microscopy (SEM), atomic force microscopy (AFM), 3-points bending, water liquid entry pressure (LEPw), and water contact angle measurement. Mercury porosimetry analysis (MIP) was also used to determine the pore size distribution and porosity of the SSCHFM. The grafting process caused an increasing of the contact angle from 0° to 142.5° ± 2.0, and LEPw value of (2.6 ± 0.4 bar) was achieved. AFM images showed an increment in the surface roughness of the grafted SSCHFM from 0.305 µm to 0.375 μm, with a slight decrease in the average pore size and porosity from 0.17 µm and 17% to 0.12 µm and 14.7% respectively. After the grafting process, the performance of the membrane in DCMD was evaluated on a salt solution for 32 h at different NaCl concentrations (8,16, 24, 32 and 40) g/L, feed flow rates and feed temperatures. The results showed a decrease in the permeate flux at increasing feed concentration, but the reverse was at higher feed flow rates and feed temperatures. The surface-modified membrane recorded a water flux value of 35 kg/m2.h and 100% salt rejection. The results indicate that the hydrophobic hollow fibre ceramic membranes derived from silica sand have significant potential to be developed for membrane distillation application in water purification and reclamation.
Bacterial endotoxin contamination in dialysate may pass through haemodialysis membrane and cause a silent chronic microinflammation to kidney patients. Dual-layer hollow fibre (DLHF) membranes with dual function, biocompatible adsorptive and antibacterial effects were developed to solve the problem of incompatible membrane and endotoxin contamination. All membranes were fabricated via the co-extrusion dry-wet phase inversion technique. In this study, silica/α-mangostin nanoparticle was incorporated into the inner layer of membrane to enhance the biocompatibility of the membrane while maintaining its adsorption capacity. Activated carbon (AC) was incorporated in the outer layer of membrane for improved antibacterial property. The DLHF membranes were characterised based on its morphology and surface hydrophilicity. The performance of the DLHF membranes was evaluated in terms of permeability, urea, and creatinine removal capabilities, bovine serum albumin (BSA) rejection and antibacterial properties. The dense and small pore size on the outer layer of AC created a smoother surface for the DLHF membrane. The BSA rejection of the DLHF membranes was enhanced by 6–8% compared to that of unmodified single layer hollow fibre membrane. Silica/α-mangostin nanoparticle in the inner layer of membrane enhanced the removal of urea and creatinine by chemisorption. Result also showed that the incorporation of AC in the outer layer of DLHF membrane successfully filtered bacteria by bacteria entrapment. DLHF membrane with the combination of silica/α-mangostin nanoparticle in the inner layer and AC in the outer layer possessed the higher bacteria inhibition into blood compartment against Escherichia coli and Staphylococcus aureus, with removal rate of 68% and 75%, respectively, and better urea and creatinine removal by 60.57% and 75.18%, respectively, compared to single-layer PSf based membrane. The development of co-adsorptive biocompatible DLHF membrane can play an important role in improvement of kidney patient life.
A novel singly fed Dielectric Resonator Antenna (DRA) is proposed here for milli meter wave 5G (Fifth Generation) frequency band applications. The DRA has achieved wide dual bandwidth with circular polarization at the defined 5G frequency bands. The resonances of this dual band antenna occur at 22.06 GHz, 24.5 GHz and 29.84 GHz. The percentage bandwidth |S11| < −10 dB of 26.3% is achieved at the first band (19.52–26.36 GHz) and 7.69% at the second band |S11| < −10 dB (28.26–30.26 GHz). Both the achieved bands here are covered under the Band 30 GHz category of 5G frequency spectrum. Compared to the conventional rectangular DRA, a novel trapezoidal shaped DRA is designed here which is fed by a microstrip line with characteristics impedance of 50 Ohm. The defined electrical dimensions of the DRA are 0.25λ0 × 0.29λ0 × 0.22λ0 considering 26 GHz as its resonating frequency. The DRA is placed over a Rogers substrate with dimensions 0.5λ0 × 0.5λ0 × 0.1λ0 and permittivity of 2.2. The DRA is circularly polarized and has a 3-dB axial ratio bandwidth of 5.23%. The DRA has achieved a gain value of 3.28 dB. Milli meter wave communications require wideband antennas with circular polarization features to support high throughput communication channels. This singly fed DRA has achieved wide dual bandwidth with circular polarization and is more suitable for indoor 5G small cell applications.
This paper explains a new Adaptive Path Sensing Method (APSM) for indoor radio wave propagation prediction. Measurement campaigns, which cover indoor line-of-sight (LoS), non-line-of-sight (NLoS) and different room scenarios, are conducted at the new Wireless Communication Centre (WCC) block P15a) of Universiti Teknologi Malaysia (UTM), Johor, Malaysia. The proposed APSM is evaluated through a computerized modelling tool by comparing the Received Signal Strength Indicator (RSSI) with measurement data and the conventional Shooting-Bouncing Ray Tracing (SBRT) method. Simulations of the APSM and SBRT are performed with the same layout of the new WCC block P15a by using the exact building dimensions. The results demonstrate that the proposed method achieves a better agreement with measured data, compared to the conventional SBRT outputs. The reduced computational time and resources required are also important milestones to ray tracing technology. The proposed APSM method can assist engineers and researchers to reduce the time required in modelling and optimizing reliable radio propagation in an indoor environment.
In this paper, a fractional-order Hantavirus infection model incorporating harvesting is formulated and investigated. The populations are divided into susceptible mice, infected mice and alien species. Mathematical analysis and numerical simulations are performed to clarify the characteristics of the proposed fractional-order Hantavirus infection model. The existence, uniqueness, non-negativity and boundedness of the solutions are examined. The local stability of the equilibrium points of the fractional-order model is studied. The mathematical proof of the existence of transcritical bifurcation is given by using Sotomayor’s theorem. The theoretical findings are illustrated by numerical simulations. The impact of fractional-order, competitive effect of alien species on mice, competitive effect of mice on alien species, carrying capacity and harvesting efforts on the stability of the Hantavirus infection model are studied. The basin of attraction regions is also illustrated.
Membrane-based fuel cells, particularly methanol-based fuel cells, are thriving areas with high efficiency, less material consumption, and low emission of pollutants. But commercial membranes have less thermal withstanding ability and high cost, so alternative polymeric membranes have been developed with desired properties to overcome this issue. The SPEEK membrane was fabricated with halloysite nanoclay and functionalized graphene oxide (f-GO) nanocomposites at various concentrations via dry phase inversion. The sulfonic acid group in the SPEEK and silane functionalization of GO enhanced the Ion exchange capacity from 0.22 to 0.35 meq/g which enhances the proton conductivity. Furthermore, the thermal stability and hydrophilicity of the pristine SPEEK membrane were reformed with addition of halloysite nanoclay and f-GO in SPEEK membrane. The presence of nanocomposite on the surface of the SPEEK membranes was confirmed via scanning electron microscope (SEM) analysis. The 3 wt% halloysite nanoclay and 2 wt% of f-GO composite membrane was hold the 0.47 mS cm⁻¹ of proton conductivity and 72.2 mW cm⁻² of power density, whereas pristine SPEEK membrane was 0.31 mS cm⁻¹ and 28 mW cm⁻², respectively. The 3 wt% halloysite incorporated SPEEK membrane and 1.5 wt% f-GO incorporated SPEEK membrane was shown better proton conductivity, which act as a prominent membrane for direct methanol fuel cell (DMFC) applications.
Rapid industrialization and urbanization significantly contribute to air pollution in China. Essential constituents of air pollution are fine and coarse particulate matter which are the total mass of aerosol particles with aerodynamic diameters smaller than ≤2.5 μm (PM2.5) and ≤10 μm (PM10), respectively. These particles may cause severe health effects, and impact the atmospheric environment and climate. However, the limited number of ground-based measurements at sparsely distributed air quality monitoring stations hamper long-term air pollution impact studies over large areas. Although spatial data on PM2.5 and PM10 are available from reanalysis models, the accuracy of such data may be reduced in comparison with ground data and may vary regionally and seasonally. Therefore, a long-term evaluation of reanalysis-based PM2.5 and PM10 against ground-based measurements is needed for China. In this study, surface-level PM2.5 and PM10 concentrations from 2014 to 2020 obtained from the Copernicus Atmospheric Monitoring Service (CAMS), and from the second version of Modern-Era Retrospective analysis for Research and Applications (MERRA-2) were evaluated using ground-based measurements obtained from 1675 air quality monitoring stations distributed across China. High PM2.5 and PM10 (μg/m3) concentrations from ground-based measurements were observed in many parts of China (including the North China Plain: NCP, Yangtse River Delta:YRD, Pearl River Delta: PRD, Central China, Sichuan Basin: SB, and northwestern region: Tarim Basin). The patterns of the spatial distributions of PM2.5 and PM10 obtained from CAMS and MERRA-2 across China are similar to those of the ground-based monitoring data, but the concentrations from both models are substantially different. CAMS significantly overestimates PM2.5 and PM10 over most regions, in particular over urban and desert areas, whereas MERRA-2 seasonal and annual mean concentrations were more accurate over the highly polluted areas in central and eastern China. The lowest PM2.5 and PM10 concentrations were observed over the Tibetan Plateau and Qinghai, where CAMS and MERRA-2 datasets were substantially underestimated. Furthermore, both CAMS and MERRA-2 under-and over-estimate the PM concentrations in both low and high pollution conditions. Overall, this study contributes to understanding of the reliability of reanalysis data and provides a baseline document for improving the CAMS and MERRA-2 datasets for studying local and regional air quality in China.
This paper presents the impact of surface roughness on the performance of a three –dimensional (3D) metal printed waveguide coupler designed at 28 GHz. The surface roughness is a significant factor that may affect 3D printed structures and post processing may be needed. It may degrade the performance of the printed devices in term of the reflection coefficient and increases the insertion loss. Thus, this work analyses the surface roughness impact on the 3D metal printed coupler designed at 28 GHz. The hybrid coupler is a waveguide-based structure with coupled resonators and the coupling is controlled by tuning the iris dimensions. The measurement is done without any post processing procedure to ensure the validation of the printed coupler with simulation results. The surface roughness measurement is performed with six tested areas of coupler structure using advanced 3D optical microscope. Then, the measured surface roughness values are included in CST software to re-simulate and compare with the original and measured results. The analysis shows that the surface roughness has a moderate influence on the reflection coefficient with 7 dB loss and 0.7 dB increased in insertion loss at 28 GHz.
Approximately 17.9% of fuel energy is used to overcome engine friction in passenger cars with engine frictional losses further broken down into losses along hydrodynamic (40%), elastohydrodynamic – due to pure sliding motion (40%), mixed (10%) and boundary (10%) lubrication regimes. Therefore, to assess the tribological influence of TMP trioleate as an eco-friendly additive to a low viscosity Polyalphaolefin (PAO) at different lubrication regimes, the present study adopted a Stribeck-type analysis. Through this study, the viscosity index of PAO was found to increase significantly when blended with 5-vol% TMP trioleate. Tribologically, across the tested conditions at different sliding velocities and applied normal loads, it was determined that this blend could potentially reduce friction power and wear scar diameter by up to 6.09% and 39.65%, respectively, when compared with the neat PAO. Such an improvement was demonstrated to also synergistically enhance the friction modifier effect of this blend at the mixed lubrication regime, delaying the onset of boundary lubrication regime when the contact is lubricated by this mixture.
In this paper, an intelligent method for fault detection and classification for a microgrid (MG) was proposed. The idea was based on the combination of three computational tools: signal processing using the maximal overlap discrete wavelet packet transform (MODWPT), parameter optimization by the augmented Lagrangian particle swarm optimization (ALPSO), and machine learning using the support vector machine (SVM). The MODWPT was applied to preprocess half cycle of the post-fault current samples measured at both ends of feeders. The wavelet coefficients derived from the MODWPT were statistically evaluated using the mean, standard deviation, energy, skewness, kurtosis, logarithmic energy entropy, max, min, and Shannon entropy. These were the input feature datasets and were used to train the SVM classifier. The ALPSO was utilized to reduce the feature subsets and select the sensitive parameters of the SVM (i.e., penalty factor and the slack variable) to further improve the performance of the SVM. The intelligent relaying scheme was executed on a real-time digital simulator (RTDS) which is integrated with Matlab. The performance of SVM-based protection method is compared to several different protection models in terms of signal processing tools, optimization techniques used for selecting datasets and sensitive parameters, and classifiers under different operating conditions. Numerous operating conditions, including islanded or non-islanded operation modes and radial and or loop topologies introducing different characteristics of fault were included as the case studies for the proposed technique. A comprehensive evaluation study of the consortium for electric reliability technology solutions (CERTS) MG system and IEEE 34-bus confirms that the proposed protection scheme is accurate, fast, and robust to noisy measurements. In addition, the obtained results illustrate that the proposed method is superior to the recently published works in the literature.
Due to the widespread proliferation of distributed generation resources and the current market situation, ensuring the security and reliability of power grids against fault events has become a more challenging task. The aim of this paper is to compare different power flow techniques for power grid vulnerability assessment against symmetrical fault incidents using bus impedance matrix. In this study, first, the relationship of the post-fault voltage phasor at each bus with the pre-fault voltage phasors at that bus and the faulted bus, impedance matrix elements, and fault impedance is investigated through power system analysis under pre-fault and post-fault circumstances. Subsequently, the accuracy of different iterative and non-iterative power flow algorithms, i.e. Newton Raphson (NR), Fast Decoupled (FD), and Direct Current (DC) methods, for the power grid vulnerability assessment is compared. To achieve this, the fault analysis at each bus is performed commencing with a very large fault impedance and ending with the fault impedance at which one of the buses reaches the low voltage violation limit. Finally, to appraise the proposed strategy, several simulations have been undertaken on IEEE 14 bus system using MATLAB software. The simulation results indicate that the power grid vulnerability against symmetrical faults is highly influenced by the type of applied power flow technique.
Herein, magnetic polyaniline was modified with lanthanum nanoparticles ([email protected]) as adsorbent, aiming to the treatment of high phosphate-containing aquatic solutions. High valent lanthanum doped with polyaniline was a promising adsorbent to uptake phosphate ions with possible electrostatic interaction and cation exchange process. The functional groups, composition, surface morphology, and magnetic property of the adsorbent were investigated using Fourier Transform-Infrared Spectroscopy (FTIR), Energy Dispersive X-ray (EDX), Scanning Electron Microscopic (SEM), and Vibrating Sample Magnetometer (VSM), respectively. During the experimental process, [email protected] has removed phosphate ions from water >90%, with 80 mg adsorbent, and shaking for 150 min at room temperature. In this regard, the process was fitted with the Pseudo-second-order kinetic model (R2 > 0.999) and the Langmuir isotherm (R2 > 0.99). The proposed nanoparticles provided an appropriate adsorption capacity (qm) of 45.24 mg.g-1 at pH 4 for phosphate ions. Besides, the adsorbent can be used with an efficiency of 92.49% up to three times that reduced to 52.89% after ten times. In addition, the adsorption process was justified by thermodynamics which confirmed the proposed adsorption mechanism. Hence, the models were provided surface adsorption, monolayer pattern, and the physical mechanism of the phosphate removal process using [email protected] Hence the proposed adsorbent can be used as an alternative adsorbent in environmental water remediation.
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