Usability Determination Using Multistage Fuzzy System

AbstractThe evaluation of software is important for enhancing the modification and improvement in a software development process. There are many factors to evaluate a software process. One of the factors is the Quality of software, which cannot be calculated with ease; as Quality of software is dependent on other factors. Software Usability is one of the significant aspects on which quality of software depends. A number of software usability models have been proposed by a number of researchers, each model considers a set of factors. In real world, we are facing many obstacles in implementing any of these proposed usability models as there is a lack in its precise definition and the concept of globally accepted usability. This paper aims to define the term ‘usability’ using a detailed taxonomy which includes all the aspects of usability and is globally accepted. Generalized Usability Model (GUM) with taxonomy has been proposed in this paper. This paper also shows how to determine the usability of a software application using a fuzzy based system which has been implemented using multistage fuzzy logic toolbox

Data-Efficient Training of CNNs and Transformers with Coresets: A Stability Perspective

Coreset selection is among the most effective ways to reduce the training time of CNNs, however, only limited is known on how the resultant models will behave under variations of the coreset size, and choice of datasets and models. Moreover, given the recent paradigm shift towards transformer-based models, it is still an open question how coreset selection would impact their performance. There are several similar intriguing questions that need to be answered for a wide acceptance of coreset selection methods, and this paper attempts to answer some of these. We present a systematic benchmarking setup and perform a rigorous comparison of different coreset selection methods on CNNs and transformers. Our investigation reveals that under certain circumstances, random selection of subsets is more robust and stable when compared with the SOTA selection methods. We demonstrate that the conventional concept of uniform subset sampling across the various classes of the data is not the appropriate choice. Rather samples should be adaptively chosen based on the complexity of the data distribution for each class. Transformers are generally pretrained on large datasets, and we show that for certain target datasets, it helps to keep their performance stable at even very small coreset sizes. We further show that when no pretraining is done or when the pretrained transformer models are used with non-natural images (e.g. medical data), CNNs tend to generalize better than transformers at even very small coreset sizes. Lastly, we demonstrate that in the absence of the right pretraining, CNNs are better at learning the semantic coherence between spatially distant objects within an image, and these tend to outperform transformers at almost all choices of the coreset size

Design and construction of double-Blumlein HV pulse power supply

A double Blumlein pulse generator is constructed using a coaxial cable. This power supply is capable of providing a voltage up to 20 kV across a matched load and 40kV across an open load with a charging voltage of 10 kV. It is designed to provide a pulse width of 110ns. A rise time of ~10ns is obtained with present spark gap. A rotating spark gap is also designed and constructed to get a pulse repetition rate of 25Hz. Although, in the present work this pulse generator is used to study the streamer discharge in air, it is useful in many other applications also

Investigation of Trapezoidal-Cut Twisted Tape Insert in a Double Pipe U-Tube Heat Exchanger using Al2O3/Water Nanofluid

AbstractAn attempt is made to enhance the rate of heat transfer in heat exchangers using Al2O3 nanofluid. In this work an experimental analysis on trapezoidal-cut twisted tape insert in a double pipe U-tube heat exchanger using Al2O3 water based nanofluid is presented. The heat transfer coefficients and the corresponding friction factors required for performance analysis are determined taking into account the typical operating conditions of the heat exchangers in turbulent flow regimes with particle volume concentration of 0.01% and 0.03% and twist ratios ranging between 5 and 20. Experimental data is generated at flow rates ranging from 0.0333kg/s to 0.2667kg/s. Experimental data is generated with water and nanofluid for Reynolds number in the range 3000<Re<30000, the Nusselt number of entire pipe for 0.03% concentrations of nanofluid with trapezoidal-cut twisted tape inserts of H/D = 5 is enhanced by 34.24% as compared to water. The friction factor of entire pipes for 0.03% concentration of nanofluid with trapezoidal-cut twisted tape inserts of H/D=5 is enhanced by 1.29 times as compared to water. The results of the investigation indicate an enhancement in the performance parameters of the heat exchanger namely heat transfer coefficient and friction factor with an increase in volume concentration of the nanoparticle