Sorting System
A Sorting System is a Data Processing System that implements a Sorting Algorithm to solve a Sorting Task.
- Context:
- It can range from being a Partial Sorting System to being a Total Sorting System.
- It can range from being a Comparative Sorting System to being a Non-Comparative Sorting System.
- It can range from being a Simple Sorting System to being an Complex Sorting System.
- Example(s):
- Bead Sort System,
- Bogosort System,
- Simple Pancake Sort System,
- Spaghetti (Poll) Sort System,
- Sorting Network System,
- Bitonic Sorter System,
- Stooge Sort System.
- Han's System,
- Thorup's System,
- an Index Sorting System,
- a String Sorting System,
- a Card Sorting System such as:
- a Comparative Sorting System such as:
- a Divide-and-Conquer Sorting System such as:
- an Efficient Sorting System such as:
- a Non-Comparative Sorting System such as:
- an External Sorting System such as:
- a Recursive Sorting System such as:
- a Simple Sorting System such as:
- …
- Counter-Example(s):
- See: Order Relation, Lexicographical Order, Search System, Merge System, Permutation, Index Data StructureComputer Science, System, List (Computing), Total Order, Numerical Order, Lexicographical Order, Sorting, Systemic Efficiency, Search System, Merge System, Canonicalization.
References
2020a
- (Wikipedia, 2020) ⇒ https://en.wikipedia.org/wiki/Sorting_algorithm Retrieved:2020-1-5.
- In computer science, a sorting algorithm is an algorithm that puts elements of a list in a certain order. The most frequently used orders are numerical order and lexicographical order. Efficient sorting is important for optimizing the efficiency of other algorithms (such as search and merge algorithms) that require input data to be in sorted lists. Sorting is also often useful for canonicalizing data and for producing human-readable output. More formally, the output of any sorting algorithm must satisfy two conditions:
- The output is in nondecreasing order (each element is no smaller than the previous element according to the desired total order);
- The output is a permutation (a reordering, yet retaining all of the original elements) of the input.
- In computer science, a sorting algorithm is an algorithm that puts elements of a list in a certain order. The most frequently used orders are numerical order and lexicographical order. Efficient sorting is important for optimizing the efficiency of other algorithms (such as search and merge algorithms) that require input data to be in sorted lists. Sorting is also often useful for canonicalizing data and for producing human-readable output. More formally, the output of any sorting algorithm must satisfy two conditions:
- Further, the input data is often stored in an array, which allows random access, rather than a list, which only allows sequential access; though many algorithms can be applied to either type of data after suitable modification.
Sorting algorithms are often referred to as a word followed by the word "sort," and grammatically are used in English as noun phrases, for example in the sentence, "it is inefficient to use insertion sort on large lists," the phrase insertion sort refers to the insertion sort sorting algorithm.
- Further, the input data is often stored in an array, which allows random access, rather than a list, which only allows sequential access; though many algorithms can be applied to either type of data after suitable modification.
2020b
- (Wikipedia, 2020) ⇒ https://en.wikipedia.org/wiki/Cognitive_flexibility Retrieved:2020-1-31.
- Cognitive flexibility has been described as the mental ability to switch between thinking about two different concepts, and to think about multiple concepts simultaneously.[1] Cognitive flexibility is usually described as one of the executive functions.[2] Two subcategories of cognitive flexibility are task switching and cognitive shifting, depending on whether the change happens unconsciously or consciously, respectively.
Cognitive flexibility varies during the lifespan of an individual.[3] In addition, certain conditions such as obsessive–compulsive disorder are associated with reduced cognitive flexibility. Since cognitive flexibility is a vital component of learning,[4] deficits in this area might have other implications.
Methods of measuring cognitive flexibility include the A-not-B task, Dimensional Change Card Sorting Task, Multiple Classification Card Sorting Task, Wisconsin Card Sorting Task, and the Stroop Test. Functional Magnetic Resonance Imaging (fMRI) research has shown that specific brain regions are activated when a person engages in cognitive flexibility tasks. These regions include the prefrontal cortex (PFC), basal ganglia, anterior cingulate cortex (ACC), and posterior parietal cortex (PPC).[5] Studies conducted with people of various ages and with particular deficits have further informed how cognitive flexibility develops and changes within the brain.
- Cognitive flexibility has been described as the mental ability to switch between thinking about two different concepts, and to think about multiple concepts simultaneously.[1] Cognitive flexibility is usually described as one of the executive functions.[2] Two subcategories of cognitive flexibility are task switching and cognitive shifting, depending on whether the change happens unconsciously or consciously, respectively.
- ↑ Scott, William A. (December 1962). “Cognitive complexity and cognitive flexibility". Sociometry. 25 (4): 405–414. doi:10.2307/2785779. JSTOR 2785779.
- ↑ Cooper-Kahn, Joyce; Dietzel, Laurie C. (2008). “What is executive functioning?". ldonline.org. National Center for Learning Disabilities and WETA-TV. Archived from the original on September 20, 2014.
- ↑ Chelune, Gordon J.; Baer, Ruth A. (1986). “Developmental norms for the Wisconsin Card Sorting Test". Journal of Clinical and Experimental Neuropsychology. 8 (3): 219–228. doi:10.1080/01688638608401314. PMID 3722348.
- ↑ Boger-Mehall, Stephanie R. (1996). “Cognitive flexibility theory: implications for teaching and teacher education". learntechlib.org. Association for the Advancement of Computing in Education. pp. 991–993. Archived from the original on March 9, 2018. Retrieved November 18, 2012.
- ↑ Leber, A B; Turk-Browne N B; Chun M M (September 9, 2008). “Neural predictors of moment-to-moment fluctuations in cognitive flexibility". Proceedings of the National Academy of Sciences. 105 (36): 13592–7. doi:10.1073/pnas.0805423105. PMC 2527350. PMID 18757744.