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Sensor-based sorting, is an umbrella term for all applications in which particles are detected using a sensor technique and rejected by an amplified mechanical, hydraulic or pneumatic process. The technique is generally applied in mining, recycling and food processing and used in the particle size range between 0.5 and 300 mm (0.020 and 11.811 in).
In the mining sorting industry, color sorting is also called sensor-based sorting technology. Optical color sorters (CCD color camera) combine X-ray sorting technology and NIR (near infrared spectrometry) to pick out the impurities of ore, minerals, stone and sand products, or separate ore into two or more categories.
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More generally objects can be sorted based on a property. Such a component or property is called a sort key. For example, the items are books, the sort key is the title, subject or author, and the order is alphabetical. A new sort key can be created from two or more sort keys by lexicographical order.
More efficient algorithms such as quicksort, timsort, or merge sort are used by the sorting libraries built into popular programming languages such as Python and Java. [2] [3] However, if parallel processing is allowed, bubble sort sorts in O(n) time, making it considerably faster than parallel implementations of insertion sort or selection ...
Example: The following table shows the steps for sorting the sequence {3, 7, 4, 9, 5, 2, 6, 1}. In each step, the key under consideration is underlined. The key that was moved (or left in place because it was the biggest yet considered) in the previous step is marked with an asterisk.
[3] Quicksort is a divide-and-conquer algorithm. It works by selecting a 'pivot' element from the array and partitioning the other elements into two sub-arrays, according to whether they are less than or greater than the pivot. For this reason, it is sometimes called partition-exchange sort. [4] The sub-arrays are then sorted recursively.
An example of such is the classic merge that appears frequently in merge sort examples. The classic merge outputs the data item with the lowest key at each step; given some sorted lists, it produces a sorted list containing all the elements in any of the input lists, and it does so in time proportional to the sum of the lengths of the input lists.