The misinformation effect is a well-established phenomenon in false memory literature, with debated explanations. The present study adopts an activation-based account of the misinformation effect in order to support the hypothesis that true and suggested information can coexist in memory. After exposure to misinformation, participants were primed with semantic associates of either the true or s...

Elicited imitation (EI) is a testing method for learners’ oral language proficiency. One common criticism aimed at EI is that performance might not require linguistic knowledge, but mere rote memorization. This study explores the issue by administering two tests to the same group of students studying English as a second language: (1) a working memory test, and (2) an English EI test. Participan...

We first study the conf relation proposed by E. Brinksma and G. Scollo to formalize testing conformance. It is well-known from their work that, in order to test whether an implementation I is a valid implementation of a specification S (i.e. I conf S), it suffices to build, from S, a canonical tester T (S) such that, when T (S) is synchronized with an implementation I, it always reaches a corre...

In the context of formal language recognition, we demonstrate the superiority of streaming property testers against streaming algorithms and property testers, when they are not combined. Initiated by Feigenbaum et al., a streaming property tester is a streaming algorithm recognizing a language under the property testing approximation: it must distinguish inputs of the language from those that a...

We deal with the problem of designing one-sided error property testers for cycle-freeness in bounded degree graphs. Such a property tester always accepts forests. Furthermore, when it rejects an input, it provides a short cycle as a certificate. The problem of testing cycle-freeness in this model was first considered by Goldreich and Ron [13]. They give a constant time tester with two-sided err...

A tolerant tester with one-sided error for a property is a tester that accepts every input that is close to the property, with probability 1, and rejects every input that is far from the property, with positive probability. In this note we show that such testers require a linear number of queries.

Khot and Shinkar (RANDOM, 2016) recently describe an adaptive, O(n log(n)/ε)-query tester for unateness of Boolean functions f : {0, 1}n 7→ {0, 1}. In this note, we describe a simple non-adaptive, O(n log(n/ε)/ε) -query tester for unateness for real-valued functions over the hypercube.

This paper analyzed the working principle of the tester for yield stress of magnetorheological fluid based on the pulling test , combined with the Ohm's law of magnetic circuit and Ampere circuital theorem, calculated the magnetic circuit of the tester,using finite element software to simulate and analyze the magnetic circuit.

1 Overview 1.1 Last time • Proper learning for P implies property testing of P (generic, but quite inefficient) • Testing linearity (over GF[2]), i.e. P = {all parities}: (optimal) O 1-query 1-sided non-adaptive tester. • Testing monotonicity (P = {all monotone functions}: an efficient O n-query 1-sided non-adaptive tester.