An extended hesitant fuzzy set using SWARA-MULTIMOORA approach to adapt online education for the control of the pandemic spread of COVID-19 in higher education institutions

The world has been challenged since late 2019 by COVID-19. Higher education institutions have faced various challenges in adapting online education to control the pandemic spread of COVID-19. The present study aims to conduct a survey study through the interview and scrutinizing the literature to find the key challenges. Subsequently, an integrated MCDM framework, including Stepwise Weight Assessment Ratio Analysis (SWARA) and Multiple Objective Optimization based on Ratio Analysis plus Full Multiplicative Form (MULTIMOORA), is developed. The SWARA procedure is applied to the analysis and assesses the challenges to adapt the online education during the COVID-19 outbreak, and the MULTIMOORA approach is utilized to rank the higher education institutions on hesitant fuzzy sets. Further, an illustrative case study is considered to express the proposed idea's feasibility and efficacy in real-world decision-making. Finally, the obtained result is compared with other existing approaches, confirming the proposed framework's strength and steadiness. The identified challenges were systemic, pedagogical, and psychological challenges, while the analysis results found that the pedagogical challenges, including the lack of experience and student engagement, were the main essential challenges to adapting online education in higher education institutions during the COVID-19 outbreak.

     

A computational method of forecasting based on high-order fuzzy time series

This paper presents a computational method of forecasting based on high-order fuzzy time series. The developed computational method provides a better approach to overcome the drawback of existing high-order fuzzy time series models. Its simplicity lies with the use of differences in consecutive values of various orders as forecasting parameter and a w-step fuzzy predictor in place of complicated computations of fuzzy logical relations. The objective of the present study is to examine the suitability of various high-order fuzzy time series models in forecasting. The general suitability of the developed method has been tested by implementing it in the forecasting of student enrollments of the University of Alabama and in the forecasting of crop (Lahi) production, a case of high uncertainty in time series data. The results obtained have been compared in terms of average error of forecast to show superiority of the proposed model.     

Top-down proteomic analysis by MALDI-TOF profiling: Concentration-independent biomarkers

Although numerous protein biomarkers have been correlated with advanced disease states, no new clinical assays have been developed. Goals often anticipate disease-specific protein changes that exceed values among healthy individuals, a property common to acute phase reactants. This review considers somewhat different approaches. It focuses on intact protein isoform ratios that present a biomarker without change in the total concentration of the protein. These will seldom be detected by peptide level analysis or by most antibody-based assays. For example, application of an inexpensive method to large sample groups resulted in observation of several polymorphisms, including the first structural polymorphism of apolipoprotein C1. Isoform distribution of this protein was altered and was eventually linked to increased obesity. Numerous other protein isoforms included C- and N-terminal proteolysis, changes of glycoisoform ratios and certain types of sulfhydryl oxidation. While many of these gave excellent statistical correlation with advanced disease, clinical utility was not apparent. More important may be that protein isoform ratios were very stable in each individual. Diagnosis by longitudinal analysis of the same individual might increase sensitivity of protein biomarkers by 20-fold or more. Protein changes that exceed the range of values found among healthy individuals may be uncommon.     

Modeling expert problem solving in a game of chance: a Yahtzee© case study

Although developments on software agents have led to useful applications in automation of routine tasks such as electronic mail filtering, there is a scarcity of research that empirically evaluates the performance of a software agent versus that of a human reasoner, whose problem-solving capabilities the agent embodies. In the context of a game of a chance, namely Yahtzee©, we identified strategies deployed by expert human reasoners and developed a decision tree for agent development. This paper describes the computer implementation of the Yahtzee game as well as the software agent. It also presents a comparison of the performance of humans versus an automated agent. Results indicate that, in this context, the software agent embodies human expertise at a high level of fidelity.     

Temperature-dependent variability in lifetime prediction of thermally activated systems

The lifetime of high-temperature systems is often controlled by thermally activated mechanisms such as diffusion. The variability in the lifetime of such systems is analyzed when the operating temperature varies according to a normal (Gaussian) distribution. Linear approximation analysis is employed to obtain simple closed form results for the probability density function (pdf) for the lifetime. The Gaussian variation in temperature is shown to transform to a log-normal distribution for the lifetime. The standard deviation of the log-normal distribution can be predicted from the activation energy, the peak temperature, and the standard deviation of the temperature distribution. Higher activation energy and lower operating temperature increase the variability of the lifetime. This approximate result is compared with the exact transformation. Lifetime experiments with incandescent tungsten lamps are compared to the theoretical prediction.     

Anatomy of a portable digital mediaprocessor

Portable devices equipped with imaging, video, and audio functionality are proliferating rapidly, and manufacturers are shipping hundreds of millions of such devices. A general-purpose processor (GPP) typically consumes tens of watts to nearly a hundred watts, while a high-performance digital still cameras main processor consumes only hundreds of milliwatts to nearly half a watt. Designing a mediaprocessor with performance comparable to that of a GPP at a power budget two orders of magnitude lower and a cost more than an order of magnitude lower poses quite a challenge. To meet requirements and reduce overall system cost, mediaprocessor designers must integrate the device with an extensive set of peripherals. For performance, cost, and power reasons, application-specific integrated circuits have traditionally been the most popular choice for portable media systems. We discuss the architecture of the DM310, a highly integrated portable digital mediaprocessor, manufactured in a 0.13-micron process.     

Surface Alloying of Nitrogen to Improve Corrosion Resistance of Steels and Stainless Steels

It is well known that the addition of nitrogen to steels and stainless steels enhances the passivity and localized corrosion resistance, in addition to improving the mechanical properties. Selective alloying of surfaces of steels and stainless steels with nitrogen could also enhance the corrosion resistance and improve the mechanical properties without affecting the bulk properties. Techniques like ion implantation, laser alloying, nitriding, etc. can be effectively used to introduce very high levels of nitrogen. In addition, these techniques can also produce modified surfaces with novel microstructures to further improve the properties. The surface alloying methods also provide an opportunity to selectively nitrogenate the surface of finished components in order to obtain better properties. The review highlights the techniques, modifications and the properties obtained further.     

Seismic Deformation of Bar Mat Mechanically Stabilized Earth Walls. II: A Multiblock Model

A relatively simple rigid plastic multiblock computational model has been developed to predict the permanent seismic displacement of mechanically stabilized earth (MSE) walls. The model formulation was based on many observations made from a series of centrifuge tests carried out on many different configurations of MSE walls. The proposed model is similar to the sliding block method of Newmark. The approach accounted for the variation in acceleration within the backfill and the nonuniform nature of the permanent wall face deformation. The predictive capability of the proposed model has been verified using centrifuge test results obtained for four MSE walls each subjected to three earthquake excitations with strength varying between 0.48 and 0.9g. The analytical model captures many aspects of the characteristic deformation behavior of MSE walls observed in the centrifuge tests. In each of the eleven wall displacement cases studied, the backfill friction angle that yielded a good match between the computed and measured maximum wall displacement was consistent with the corresponding laboratory measured values.     

Comparison of urea clearance in low‐efficiency low‐flux vs. high‐efficiency high‐flux dialyzer membrane with reduced blood and dialysate flow: An in vitro analysis

Rapid removal of small molecules during hemodialysis places an acutely ill patient with kidney failure at an increased risk of hemodynamic instability and for dialysis disequilibrium syndrome. The use of high‐flux, high‐efficiency (HEF) dialyzers may increase this risk despite reductions in blood and dialysate flow. We performed in vitro experiments to compare urea clearance at low dialysate flow and various blood flows using a low‐efficiency low‐flux (LEF) and a HEF membrane. Compared to LEF, there was a significant increase in the clearance of urea at all blood flows with the HEF (all P values < 0.005). HEF dialyzer (F180NR) had higher urea clearance at a blood flow of 150 mL/min than LEF dialyzer (F5) at blood flow of 300 mL/min (144.1 ± 0.99 vs. 130.1 ± 0.001 mL/min for F180 vs. F5, respectively, P < 0.002). Our data suggest that use of HEF dialyzer are not as safe as LEF in high‐risk acute dialysis patients since these are associated with more rapid removal of urea despite reduction in blood and dialysate flow as compared to LEF.