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In this paper, we define and examine the concept of a fuzzy recognizer. If L(M) is the language recognized by an incomplete fuzzy recognizer M, we show that there is a completion M of M such that L(M) = L(M). We also show that if A is a recognizable set of words, then there is a complete accessible fuzzy recognizer M_A such that L(M_A) = A. We lay groundwork to determine rational decompositions of recognizable sets.

Profit analysis of a two non‐identical unit cold standby system model with mutual changeover of the units is carried out in this paper. With mutual changeover of the unit, the operating unit, after functioning for some random amount of time, becomes standby to take rest, and the standby unit becomes operative. The failure and repair times of each unit are jointly distributed as bivariate exponential (BVE) with different parameters. Various measures of system effectiveness useful to system engineers and designers are obtained by using the regenerative point technique. Behaviour of the mean time to system failure (MTSF) and availability have also been studied graphically.

This chapter studies the effects of the COVID-19 pandemic on the economic structure of the US and EU economies by measuring its impact on some reference macro-economic variables. We use a factor model approach on a set of variables available at different frequencies (daily, weekly, monthly, and quarterly) and provide evidence of instability in the primary factors driving the economy. A sequential analysis of the factors allows us to evaluate the model's forecasting performance and extract some instability measures based on the factor model's eigenvalues. Finally, we show how to use COVID-related variables, such as policy, economic, and health indicators, to compute conditional forecasts with factor models, and perform a scenario analysis on the variables of interest to understand economic instability.

This is the third in a series of papers aimed at providing models effective in predicting the degree of pain and discomfort in canines. The first two papers provided benchmarking and examination of dogs suffering from osteoarthritis (OA). In this chapter, we extend the study to include dogs suffering from OA, sarcoma, and oral mucositis (a side effect of chemotherapy and radiation treatments). The R programming language and SAS JMP are used to clean data, generate ANOVA, LSR regression, decision tree, and nominal logistic regression models to predict changes in activity levels associated with the progression of arthritis. The predictive models provide a diagnostic basis for determining the degree of disease in a dog (based on demographics and activity levels) and provide forecasts that assist in establishing appropriate medication dosages for suffering dogs.

The objective of this paper is to characterize the changes in the rankings of the top ten results of major search engines over time and to compare the rankings between these engines.

The papers compare rankings of the top‐ten results of the search engines Google and AlltheWeb on ten identical queries over a period of three weeks. Only the top‐ten results were considered, since users do not normally inspect more than the first results page returned by a search engine. The experiment was repeated twice, in October 2003 and in January 2004, in order to assess changes to the top‐ten results of some of the queries during the three months interval. In order to assess the changes in the rankings, three measures were computed for each data collection point and each search engine.

The findings in this paper show that the rankings of AlltheWeb were highly stable over each period, while the rankings of Google underwent constant yet minor changes, with occasional major ones. Changes over time can be explained by the dynamic nature of the web or by fluctuations in the search engines' indexes. The top‐ten results of the two search engines had surprisingly low overlap. With such small overlap, the task of comparing the rankings of the two engines becomes extremely challenging.

The paper shows that because of the abundance of information on the web, ranking search results is of extreme importance. The paper compares several measures for computing the similarity between rankings of search tools, and shows that none of the measures is fully satisfactory as a standalone measure. It also demonstrates the apparent differences in the ranking algorithms of two widely used search engines.

This study examines the impact of financial inclusion on the corporate sustainability of banks in both Organization of Islamic Cooperation (OIC) and non-OIC emerging economies, considering the COVID-19 pandemic.

The research utilizes data from 3,159 bank-years from 2007 to 2021 across 33 emerging markets.

Empirical findings indicate that firms operating in higher financial inclusion developing countries tend to exhibit higher levels of sustainable development. This positive relationship has become even more pronounced during the COVID-19 pandemic, suggesting the importance of financial inclusion in fostering corporate sustainability, especially in times of economic challenges. Interestingly, while the positive correlation between financial inclusion and sustainable development remains consistent across both OIC and non-OIC countries, firms in OIC countries do not show significant changes during the pandemic.

This observation suggests that the pandemic’s impact on corporate sustainability may vary between the two groups of countries. This study highlights the significance of financial inclusion in promoting corporate sustainability in developing economies. In times of recessions when accessing finance becomes expensive, policymakers in OIC countries should identify firms that adhere to Islamic principles, such as those sensitive to interest rates, and provide them with targeted support. This assistance can enable these companies to compete effectively and achieve their financial sustainability objectives.

There has been no attempt to investigate the effect of financial inclusion and the pandemic on the sustainable development of banks in developing countries.

The purpose of this paper is to empirically analyze the impact of social inclusion factors and foreign fund inflows on reducing gender-based unemployment in India.

A time series data set for the period of 1991–2021 has been considered, and an autoregressive distributed lag methodology has been applied to measure the short- and long-run impact of social inclusion and foreign fund inflows on reducing gender-based unemployment in India.

According to the study’s findings, both social inclusion and foreign fund inflows are critical factors for reducing male unemployment. However, in the case of female unemployment, only social inclusion factors play an important role, whereas foreign fund inflows have no role in it.

Analyzing the factors that affect gender-based unemployment has always been a grey area in literature. There are very few studies that capture gender-based unemployment in India, making this study a novice contribution. Second, it examines the relationship between foreign fund inflows, social inclusion and unemployment, which is another novel area of investigation. Finally, this study provides comprehensive and distinct results for both male and female unemployment that can help policymakers devise gender-based unemployment policies.

Although publicly listed firms in Sri Lanka have been increasingly adapting sustainability reporting into their annual reporting practices, a limited number of firms prepare sustainability reports by integrating sustainable development goals (SDGs) into reporting mechanisms. This study attempts to develop an index to monitor firms' sustainability reporting practices based on Global Reporting Institute (GRI) guidelines integrating SDGs.

This paper develops a sustainability score index using the 17 SDGs utilising the results of content analysis of corporate annual reports of a selected sample of 100 firms listed on the Colombo Stock Exchange (CSE). Principal component analysis was employed to examine the reliability of data in the developed index.

Findings show that the developed scoring index is efficient for evaluating the contents of the sustainability reports of Sri Lankan firms. Sustainability reporting practises with regard to the SDGs were observed to have a turbulent period from 2015 to 2019 and the SDGs 12 and 15 were identified to be mostly reported in Sri Lankan corporate sustainability reports.

The results of the study add to knowledge on the monitoring of sustainability reporting practises with reference to SDGs. The study outcomes are useful for the investors, stakeholders, and statutory bodies to measure the sustainable performance of business firms and assess the firm’s commitment towards the global sustainability agenda.

To the best of our knowledge, this is the first study that constructs a sustainability reporting score index integrating SDGs.