AlgorithmIn mathematics and computer science, an algorithm (ˈælɡərɪðəm) is a finite sequence of rigorous instructions, typically used to solve a class of specific problems or to perform a computation. Algorithms are used as specifications for performing calculations and data processing. More advanced algorithms can use conditionals to divert the code execution through various routes (referred to as automated decision-making) and deduce valid inferences (referred to as automated reasoning), achieving automation eventually.
PleurisyPleurisy, also known as pleuritis, is inflammation of the membranes that surround the lungs and line the chest cavity (pleurae). This can result in a sharp chest pain while breathing. Occasionally the pain may be a constant dull ache. Other symptoms may include shortness of breath, cough, fever, or weight loss, depending on the underlying cause. Pleurisy can be caused by a variety of conditions, including viral or bacterial infections, autoimmune disorders, and pulmonary embolism. The most common cause is a viral infection.
Aspiration pneumoniaAspiration pneumonia is a type of lung infection that is due to a relatively large amount of material from the stomach or mouth entering the lungs. Signs and symptoms often include fever and cough of relatively rapid onset. Complications may include lung abscess, acute respiratory distress syndrome, empyema, and parapneumonic effusion. Some include chemical induced inflammation of the lungs as a subtype, which occurs from acidic but non-infectious stomach contents entering the lungs. Infection can be due to a variety of bacteria.
Conditional varianceIn probability theory and statistics, a conditional variance is the variance of a random variable given the value(s) of one or more other variables. Particularly in econometrics, the conditional variance is also known as the scedastic function or skedastic function. Conditional variances are important parts of autoregressive conditional heteroskedasticity (ARCH) models. The conditional variance of a random variable Y given another random variable X is The conditional variance tells us how much variance is left if we use to "predict" Y.
