Sentence examples for machines for different from inspiring English sources

"It's almost the same thing, save for a few minor adjustments," Mr. Ferreira said of the workout set-up, which positions 10 hydraulic resistance machines for different parts of the body inside a mock boxing ring.

Since virtual machines are cheap and easy to create, users tend to create distinct virtual machines for different tasks.

The range of available and new commercial HPP machines for different groups of food producers is presented.

The attachment can be mounted onto a variety of machines for different applications, including CNC milling machines, industrial robots, and CMM.

A dairy cattle farm consists of several facilities, such as housing system, yards, manure pits, milking center, environmental protection structures, forage storage, and several machines for different facilities.

Although the presented methodology is framed on the design of a wind energy generator, it can be extended to the design of permanent magnet machines for different application fields.

Concorde was a lost cause – a fatally flawed time machine for different times.

Investigations were performed for the parametric optimization of single screw extruder machine for different mechanical/metallurgical properties (like: porosity, peak elongation, break strength, Shore D hardness) with the help of case study of recycled high density polyethylene (HDPE 100%, HDPE90% + Fe10%, low density polyethylene (LDPE 100% and LDPE94 + 6% (by wt.).

The material removal tests were conducted using a computer numerical control (CNC) abrasive jet cutting machine for different parameters of nozzle feed rate (10, 15, 20 and 25 mm·min−1), abrasive flow rate (50, 150, 250 and 350 g·min−1), spindle speed (25, 50, 75 and 100 min−1) and standoff distance (2, 5, 8 and 11 mm).

It will discuss the kind of machine required for different Xen installations, the methods for installing Xen, and how to configure Xen to get the virtual machine up and running.

We used text parsing to extract typed dependencies, which represent syntactic and grammatical relationships between words, and are shown to capture 'othering' language - consistently improving machine classification for different types of cyber hate beyond the use of a Bag of Words and known hateful terms, which have been the main method for identifying cyber hate previously.