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This study describes the construction of a new algorithm where image processing along with the two-step quasi-Newton methods is used in biomedical image analysis. It is a well-known fact that medical informatics is an essential component in the perspective of health care. Image processing and imaging technology are the recent advances in medical informatics, which include image content representation, image interpretation, and image acquisition, and focus on image information in the medical field. For this purpose, an algorithm was developed based on the image processing method that uses principle component analysis to find the image value of a particular test function and then direct the function toward its best method for evaluation. To validate the proposed algorithm, two functions, namely, the modified trigonometric and rosenbrock functions, are tested on variable space.

Efficient management of working capital is essential for firms to avoid overinvesting in short-term assets for maximum profitability while guaranteeing much-needed liquidity to run their operations. This study examines the impact of working capital management on firms’ profitability in the automotive industry in Europe before and during the COVID-19 pandemic period. The automotive industry is vital to the European economy, being a major component of the total industrial value added to the GDP of the continent. Existing research on this topic is inconclusive, and there is a gap in the literature exploring the working capital management effect on firm performance in periods of crisis. Unlike most research, this study focuses on a single industry to better capture the impact of working capital management on firm profitability. It also adds the COVID-19 dimension to stress the importance of proper working capital management, especially in periods of economic distress. The results show that the receivables collection period, inventory conversion period, accounts payable period, and cash conversion cycle have a significant negative impact on ROA for both the pre-pandemic and pandemic period, suggesting that managers must be prudent regarding their firm’s credit policy by not being overly generous with credit terms and making every effort to promptly collect their receivables. Moreover, excessive levels of inventory impair profitability by locking up valuable cash reserves, which are vital, especially in periods of crisis. Though seemingly counterintuitive, being profitable also means not postponing payables settlement unnecessarily.

The Coronavirus disease (COVID-19) most likely began in an animal species and subsequently transmitted to humans in Wuhan, China, a city of 11 million people, on December 29, 2019, when the first case was recorded. The Coronavirus then transmitted from person to person by infected droplets from a sick person's coughing, sneezing, or contaminated hands. Hence, the purpose of the study is to see the impact of the outbreak of COVID-19 daily tests on the Pakistani rupee against the US dollar exchange rate using Vector Autoregressive approach. The data is gathered from February 26, 2020 to March, 2021. This period was selected, because the pandemic expanded, and the first case was observed in Pakistan on Feb 26th 2020. To verify this effect, a Vector Autoregressive Model was developed. A generalized version of the Autoregressive Model is a Vector Autoregressive (VAR) model. As a result of the COVID-19 pandemic, the Pakistani rupee devalued against the US dollar throughout the abovementioned period. When analyzing the Pakistani rupee vs. the US dollar exchange rate using a Vector Autoregressive Model, the values of the lags (1, 4, 6, and 7) of the explanatory variable have a significant impact. Besides, under the VAR model, the IRF (Impulse Response Function) asserted the actual impact of the daily COVID-19 tests, as well as Decomposition of Variance was shown to provide for the daily COVID-19 tests just a small part in understanding the volatility of the Pakistani rupee against the US dollar exchange rate. The Granger Causality suggests that the short-term and long-term changes in the Pakistani rupee against the US dollar exchange rate are caused by daily COVID-19 tests.

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