RANDOMIZATION OF MULTIPLE CHOICE QUESTIONS FOR COMPUTER ASSISTED TEST (CAT) IN STUDENT SELECTION

Computer Assisted Test (CAT) is a computer application designed to help selection process, particularly to examine multiple choice questions. This application requires random questions and answer choices derived from a question bank. One of the random number generator is computational algorithms, or the so-called pseudo-random number generators. In this research, the model and randomized algorithm had been developed to generate the initial development of Computer Assisted Test. Linear congruential was used as the method to generate random number. One-sample Chi-Square test was applied to test the model and algorithm for randomness of question items. The statistic test result show χ2 = 206 and critical values χ20.05,199 = 232.19, while the number of answer choices for randomness tests statistically obtained χ2= 4.0 and the critical value χ20.05,8 = 15:51. From both the results of these tests concluded that the randomness of questions and answer choices produce a number of questions and answer choices that number has an equal chance of being selected

Postprocessing for quantum random number generators: entropy evaluation and randomness extraction

Quantum random-number generators (QRNGs) can offer a means to generate information-theoretically provable random numbers, in principle. In practice, unfortunately, the quantum randomness is inevitably mixed with classical randomness due to classical noises. To distill this quantum randomness, one needs to quantify the randomness of the source and apply a randomness extractor. Here, we propose a generic framework for evaluating quantum randomness of real-life QRNGs by min-entropy, and apply it to two different existing quantum random-number systems in the literature. Moreover, we provide a guideline of QRNG data postprocessing for which we implement two information-theoretically provable randomness extractors: Toeplitz-hashing extractor and Trevisan's extractor.Comment: 13 pages, 2 figure

Improving the Statistical Qualities of Pseudo Random Number Generators

Pseudo random and true random sequence generators are important components in many scientific and technical fields, playing a fundamental role in the application of the Monte Carlo methods and stochastic simulation. Unfortunately, the quality of the sequences produced by these generators are not always ideal in terms of randomness for many applications. We present a new nonlinear filter design that improves the output sequences of common pseudo random generators in terms of statistical randomness. Taking inspiration from techniques employed in symmetric ciphers, it is based on four seed-dependent substitution boxes, an evolving internal state register, and the combination of different types of operations with the aim of diffusing nonrandom patterns in the input sequence. For statistical analysis we employ a custom initial battery of tests and well-regarded comprehensive packages such as TestU01 and PractRand. Analysis results show that our proposal achieves excellent randomness characteristics and can even transform nonrandom sources (such as a simple counter generator) into perfectly usable pseudo random sequences. Furthermore, performance is excellent while storage consumption is moderate, enabling its implementation in embedded or low power computational platforms.This research was funded by the Spanish Ministry of Science, Innovation and Universities (MCIU), the State Research Agency (AEI), and the European Regional Development Fund (ERDF) under project RTI2018-097263-B-I00 (ACTIS)

Quantum Cellular Automata Pseudo-Random Maps

Quantum computation based on quantum cellular automata (QCA) can greatly reduce the control and precision necessary for experimental implementations of quantum information processing. A QCA system consists of a few species of qubits in which all qubits of a species evolve in parallel. We show that, in spite of its inherent constraints, a QCA system can be used to study complex quantum dynamics. To this aim, we demonstrate scalable operations on a QCA system that fulfill statistical criteria of randomness and explore which criteria of randomness can be fulfilled by operators from various QCA architectures. Other means of realizing random operators with only a few independent operators are also discussed.Comment: 7 pages, 8 figures, submitted to PR