By Casey Reas, Nick Montfort, Ian Bogost, John Bell, Patsy Baudoin, Jeremy Douglass, Mark C. Marino, Michael Mateas, Mark Sample, Noah Vawter
A unmarried line of code bargains the way to comprehend the cultural context of computing.
This booklet takes a unmarried line of code--the super concise easy application for the Commodore sixty four inscribed within the title--and makes use of it aa a lens by which to contemplate the phenomenon of inventive computing and how machine courses exist in tradition.
The authors of this collaboratively written ebook deal with code no longer as basically sensible yet as a text--in the case of 10 PRINT, a textual content that seemed in lots of varied revealed sources--that yields a narrative approximately its making, its goal, its assumptions, and extra. they think about randomness and regularity in computing and paintings, the maze in tradition, the preferred uncomplicated programming language, and the hugely influential Commodore sixty four laptop.
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Based on our observations, we conclude that emerging soft computing methods can provide us with alternative solutions over classical schemes to challenging motor fault diagnosis problems. Nevertheless, they are not supposed to compete with conventional methods. Instead, more accurate and robust diagnosis approaches should be developed based on the fusion of these two categories of methodologies, soft computing and hard computing . References 1. Leonhard W. (1996), Control of Electrical Drives, Springer-Verlag, Berlin, Germany.
1996), Control of Electrical Drives, Springer-Verlag, Berlin, Germany. 2. Y. (1997), Motor fault detection and diagnosis, IEEE Industrial Electronics Newsletter, 44, no. 4, pp. 4-7. 3. J. (1996), Signal Processing for Industrial Diagnostics, John Wiley & Sons, West Sussex, UK. 4. A. (1994), Fuzzy logic, neural networks, and soft computing, Communications of the ACM, 37, no. 3, pp. 77-84. 5. A. A. 6. Y. (1997), Methodologies of Using Neural Network and Fuzzy Logic Technologiesfor Motor Incipient Fault Detection, World Scientific Publishing Co.
A. (1994), Fuzzy logic, neural networks, and soft computing, Communications of the ACM, 37, no. 3, pp. 77-84. 5. A. A. 6. Y. (1997), Methodologies of Using Neural Network and Fuzzy Logic Technologiesfor Motor Incipient Fault Detection, World Scientific Publishing Co. Pte. Ltd, Singapore. 7. Vas P. A. 8. , and Vas P. (2000), Recent developments of induction motor drives fault diagnosis using AI techniques, IEEE Transactions on Industrial Electronics, 47, no. 5, pp. 994-1004. 9. Special Section on Motor Fault Detection and Diagnosis (2000), IEEE Transactions on Industrial Electronics, 47, no.