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Retention and Comprehension of Information
Published in Robert W. Proctor, Van Zandt Trisha, Human Factors in Simple and Complex Systems, 2018
Robert W. Proctor, Van Zandt Trisha
Mnemonics can be particularly beneficial for elderly people, who may be at higher risk for memory failures (Poon, Walsh-Sweeney, & Fozard, 1980). However, those people who could most benefit from the use of mnemonics, such as the elderly, often forget to use them. Various sentence-based mnemonics have also been proposed to enable users to generate passwords that they will be able to remember but that will be difficult for a hacker to crack (Yang, Li, Chowdhury, Xiong, & Proctor, 2016). For example, think of a sentence that contains at least eight words, and then select a letter, number, or a special character to represent each word. The sentence might be, “I went to London four and a half years ago,” and the resulting password could be iwtl4&ahya. A potential drawback of this approach is that it requires remembering not only the sentence but also the conversions used for each word in the sentence.
Human Information Processing
Published in Julie A. Jacko, The Human–Computer Interaction Handbook, 2012
Robert W. Proctor, Kim-Phuong L. Vu
Mnemonic techniques can also be used to improve recall. The basic idea behind mnemonics is to connect the to-be-remembered material with an established organizational structure that can be easily accessible later on. Two widely used mnemonic techniques are the pegword method (Wood and Pratt 1987) and the method of loci (Verhaeghen and Marcoen 1996). In the pegword method, a familiar rhyme provides the organizational structure. A visual image is formed between each pegword in the rhyme and the associated target item. At recall, the rhyme is generated, and the associated items come to mind. For the method of loci, locations from a well-known place, such as your house, are associated with the to-be-remembered items. Although specific mnemonic techniques are limited in their usefulness, the basic ideas behind them (utilizing imagery, forming meaningful associations, and using consistent encoding and retrieval strategies) are of broad value for improving memory performance.
Source code plagiarism detection with low-level structural representation and information retrieval
Published in International Journal of Computers and Applications, 2021
As seen in Figure 7, the largest difference between low-level representation (used in VSM-LC) and source code token sequence (used in VSM-SC) occurs on level-2 category. Further observation shows that most renamed identifiers are considered as mismatched tokens at source code level (due to their different mnemonics with the original ones) while they are matched tokens at low-level representation (thanks to Java compiler's local variable renaming that renames all local variables according to their first-occurrence order).