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Published in Yeong Koo Yeo, Chemical Engineering Computation with MATLAB®, 2020
The first line of the file starts with function, which identifies the file as a function code file. The Editor colors this special word blue. The first line of the code file specifies the name of the function and describes both input arguments (or parameters) and output values. In this example, the function is called sinx. The file name without the “.m” extension and the function name should match. It is good practice to follow the first line of a function code file with one or more comment lines explaining what the code file does. If you do, “help” will automatically retrieve this information. For example:>> help sinx sinx calculates sin(x)/x for x = 10^(-a),where a = 1, ..., z.
Organizing with Unix
Published in Rafael A. Irizarry, Introduction to Data Science, 2019
As you may have noticed, Unix uses an extreme version of abbreviations. This makes it very efficient, but hard to guess how to call commands. To make up for this weakness, Unix includes complete help files or man pages (man is short for manual). In most systems, you can type man followed by the command name to get help. So for ls, we would type: man ls
Science as a game: conceptual model and application in scientific software design
Published in International Journal of Design Creativity and Innovation, 2022
Francisco Queiroz, Maria Lonsdale, Rejane Spitz
Most issues described were related to data visualization (Table 2), ranging from the need to generate multiple static graphs quicker (P1), finding ways to calculate and generate new graphs (P2), and interactive simulation and visualization in 3D (P3). P4, on the other hand, described issues related to the modeling phase: (a) time consumed using command line interface (CLI) to transfer files from an online repository to the university’s supercomputer where those files would help fine-tuning the model; and (b), difficulties accessing documentation and learning resources. P4 mentioned two additional issues: institutional approaches to open science, and inspection for Deep Learning models – both discarded given their scale and scope.
Optimization of stirred mill parameters for fine grinding of PGE bearing chromite ore
Published in Particulate Science and Technology, 2021
Santosh T., Rahul K. Soni, Eswaraiah C., Rao D. S., Venugopal R.
Equation (10) was optimized using mathematical software (MATLAB R2015a) with global minima search option to achieve the minimal value combination of product size (P80) and energy consumption (ECS) within the continuous domain of experimental data range. The problem of simultaneous optimization of more than one function was handled by minimizing the objective function as the sum of product size (P80) and energy consumption (ECS). The optimization was done with the help of MATLAB command Global Search which finds the global minima. The optimum levels of variables were found to be 621.5 rpm stirrer speed, 9.2 min grinding time, −150 + 106 µm feed size, and 50.1% of solids concentration. The product size (P80) of 11.6 μm was achieved with an expend of 21.8 kWh/t energy at optimal operating conditions. The improvement of grinding performance was verified by preforming three additional experiments at the optimal levels. The mean values of product size (P80) and energy consumption (ECS) along with their standard deviations (sd) for three experiments were 12.4 μm () and 21.3 kWh/t ( kWh/t), respectively. The presented work demonstrates how to achieve an as small as product size (P80) such as 11.6 μm with relatively lower and affordable energy consumption (ECS) for the low-grade chromite ore bearing PGE minerals in a laboratory stirred mill. The target product size (P80) is chosen based on the liberation size of PGE.
Are output disaggregation and energy variables key when measuring container terminal efficiency?
Published in Maritime Policy & Management, 2022
Thomas Spengler, Beatriz Tovar, Gordon Wilmsmeier
This equation is the most commonly solved envelopment form of the problem. The scalar θ is representing the efficiency of the container terminal and λ is a column vector ‘that describes the percentage of other companies, and is used for constructing the efficient company. X and Y are the companies’ input and output vectors, and [xi] and [yi] are the inputs and outputs of the company that is being evaluated’ (Pérez-Reyes and Tovar 2009). The calculations were carried out in Python with the help of NumPy.