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Random number generators (RNGs) are basic cryptographic primitives. They are used to generate cryptographic keys, initialization vectors, challenges and nonces in cryptographic protocols, and random masks in countermeasures against side channel attacks. RNGs designed for cryptography must generate unpredictable random numbers. According to recent security standards, the unpredictability of generated random numbers must be thoroughly evaluated. In this paper, we provide a concrete example – a phase-locked loop based RNG protected by novel dedicated embedded tests, on which we show how stringent security requirements including unpredictability of generated numbers can be met, while respecting the standards.

Stochastic computing (SC) is a promising approach for low-power and low-cost applications with the added benefit of high error tolerance. However, the high overhead of generating stochastic bitstreams can offset the advantages of SC especially when a large number of bitstreams are needed. In this paper, we propose a new stochastic number generator (SNG) that significantly reduces area and energy while improving accuracy. Experimental results show that the proposed SNG can reduce energy by more than 72% compared with the state-of-the-art designs.

The security of stored templates has become an important issue in biometric authentication systems this because most of the biometric attacks target the biometric database beside the difficulty of issuing the templates again. Thus, to protect the biometric templates it must be encrypted before storing in database. In this paper we proposed an efficient encryption method based on two invertible and random keys to enhance and overcome the weakness of hill cipher algorithm the keys generated using upper triangular matrices with Pseudo-Random Number Generator (PRNG) using two large and random encryption keys. The proposed encryption method provides sufficient security and protection for the biometric templates from attacks, where the experimental results showed high efficiency comparing with the traditional Hill Cipher and existing methods.

The world is now behind technology transforming every terminology in daily life, like banking, cash, paper, shopping, communication and so on into, e-world terminologies. In this fast growing e-world efficiency of cryptographic algorithms that ensure security of data is of primary concern. Randomness plays an important role in improving the efficiency of cryptographic algorithms. Compared to pseudo Random number generators true random number generators produce random series that exhibit randomness more. But it is better to combine the advantages of both true random number generators and pseudo random number generators. In this work a non-recurring random number generator is being experimented and proved to better generator when compared to the existing systems. In this system it is ensured that a sequence of numbers never repeats within the generated series and also every number occurs with same frequency. Both these qualities of the generated series prove itself to be better than the existing systems.

Robust statistical analysis of physical random number generators is studied. An estimate of randomness based on ranged amplitudes is proposed, complementing an analysis of entropy. The randomness of input data from an analog-to-digital converter is analyzed for a quantum random number generator based on homodyne detection.

An area-efficient FPGA-based annealing processor that is based on Ising model is proposed. The proposed processor eliminates random number generators (RNGs) and temperature schedulers, which are the key components in the conventional annealing processors and occupying a large portion of the design. Instead, a shift-register-based spin flipping scheme successfully helps the Ising model from stucking in the local optimum solutions. An FPGA implementation and software-based evaluation on max-cut problems of 2D-grid torus structure demonstrate that our annealing processor solves the problems 10-10[4] times faster than conventional optimization algorithms to obtain the solution of equal accuracy.

The datasets contained in this article are simulated data with respect to Sickle Cell Anaemia (SCA) in order to examine the mathematical inheritance formation of the SCA disease. The simulation is done using Monte Carlos Simulation (MCS) Technique to complement the Physical Simulation Smith's Statistical (PSSS) package used as random number generator for birth simulation. One hundred and fifty-six (156) births for seven (7) generations were considered in the simulation alongside non-gestating reproductive females with fertile male adults while immigration and emigration are not permitted. These datasets can effectively serve as benchmarks for both health, and marital counselling institutions. Keywords: Sickle cell anaemia, Population dynamics, Data simulation

In this paper, two modifications are proposed to the Progressive Random Walk (PRW) algorithm in order to address its potentially insufficient search space coverage. The first modification replaces the Pseudo-Random Number Generator (PRNG) with the uniform distribution by the chaotic map based PRNG for generating of the offset values and the second modification is called direction switching and is based on experiment observation. The modifications are implemented into the PRW and the resulting algorithm is called modified Progressive Random Walk. The search space coverage of the two algorithms is compared. Both algorithms are used in macro ruggedness estimation of the CEC2015 benchmark set and the results are discussed.

The deterministic description of the subgrid-scale land–atmosphere interaction in regional climate model (RCM) simulations is changed by using stochastic soil and vegetation parameterizations. For this, the land–atmosphere interaction parameterized in a land surface model (LSM) is perturbed stochastically by adding a random value to the input parameters using a random number generator. In this way, a stochastic ensemble is created that represents the impact of the uncertainties in these subgrid-scale processes on the resolved scale circulation. In a first step, stochastic stand-alone simulations with the VEG3D LSM are performed to identify sensitive model parameters. Afterward, VEG3D is coupled to the Consortium for Small-Scale Modeling–Climate Limited-Area Modeling (COSMO-CLM) RCM and stochastically perturbed simulations driven by ERA-Interim (2001–10) are performed for the Coordinated Downscaling Experiment–European Domain (EURO-CORDEX) at a horizontal resolution of 0.22°. The simulation results reveal that the impact of stochastically varied soil and vegetation parameterizations on the simulated climate conditions differs regionally. In central Europe the impact on the mean temperature and precipitation characteristics is very weak. In southern Europe and North Africa, however, the resolved scale circulation is very sensitive to the local soil water conditions. Furthermore, it is demonstrated that the use of stochastic soil and vegetation parameterizations considerably improves the variability of monthly rainfall sums all over Europe by improving the representation of the land–atmosphere interaction in the stochastic ensemble on a daily basis. In particular, inland rainfall during summer is simulated much better.

By the example of the RNGAVXLIB random number generator library, this paper considers some approaches to employing AVX vectorization for calculation speedup. The RNGAVXLIB library contains AVX implementations of modern generators and the routines allowing one to initialize up to 1019 independent random number streams. The AVX implementations yield exactly the same pseudorandom sequences as the original algorithms do, while being up to 40 times faster than the ANSI C implementations.

Sickle Cell Anaemia (SCA) is a serious inherited blood disorder where the red blood cells, which carry oxygen around the body develop abnormally. The mathematical dynamics of the disease remain poorly understood, as such this paper investigates the mathematical inheritance pattern of the disease by the application of Monte Carlos simulation technique which is a complementary approach to physical simulation Smith’s statistical package was used as random number generator in which the simulated birth from different mating indicates that SS has an average of 2.4% neonates, AS has 29.9% and AA has 67.7%. We thus, conclude that eradication of SCA is not visible. However, curative measure of SCA remains paramount.

This paper demonstrates the vulnerability of the Kirchhoff-Law-Johnson-Noise (KLJN) secure key exchanger to compromised random number generator(s) even if these random numbers are used solely to generate the noises emulating the Johnson noise of Alice's and Bob's resistors. The attacks shown are deterministic in the sense that Eve's knowledge of Alice's and/or Bob's random numbers is basically deterministic. Moreover, no statistical evaluation is needed, except for rarely occurring events of negligible, random waiting time and verification time. We explore two situations. In the first case, Eve knows both Alice's and Bob's random noises. We show that, in this situation, Eve can quickly crack the secure key bit by using Ohm's Law. In the other situation, Eve knows only Bob's random noise. Then Eve first can learn Bob's resistance value by using Ohm's Law. Therefore, she will have the same knowledge as Bob, thus at the end of the bit exchange period, she will know Alice's bit., Comment: arXiv admin note: substantial text overlap with arXiv:2005.10429

There are an increasing number of lightweight devices such as smart cards, radio frequency identification (RFID) tags, wireless sensor nodes and devices associated with the Internet of Things (IoT) concept, all of which need effective and lightweight security structures. One of the basic elements used in authentication protocols is the nonce values that are generated by PRNGs. Also random numbers are used for encryption process in secure communication. Proposed PRNG has demonstrated great suitability for devices with limited resources in terms of performance, resource usage and randomness. This generator is tested with NIST statistical test suite (NIST STS), which is one of the most comprehensive randomness test tools. It is also implemented, tested on wireless identification and sensing platform (WISP) passive RFID tag and compared with well-known PRNGs. As a result of the comparisons, it has better results than its rivals.

Computer algebra systems are complex software systems that cover a wide range of scientific and practical problems. However, the absolute coverage cannot be achieved. Often, it is required to create a user extension for an existing computer algebra system. In this case, the extensibility of the system should be taken into account. In this paper, we consider a technology for extending the SymPy computer algebra system with a low-level module that implements a random number generator., Comment: in English; in Russian

This paper analyzes the security of a random number generator (RNG) based on a 4-D chaotic hyperjerk system. An attack system is designed to reveal the security weaknesses of the proposed chaotic RNG. Knowing the structure of the RNG and observing one of the state variables of the chaotic system, convergence between attack and target systems is demonstrated by applying linear continuous coupling in master-slave synchronization scheme. Output bit sequence of the chaotic RNG is identically reproduced. The feasibility of the attack system is verified through numerical simulations. In this paper, a specific continuous-time chaos-based RNG is targeted as a case study. However, the cryptanalysis method presented in this paper is applicable to any continuous-time or discrete-time chaos-based RNGs. Therefore, this study highlights the security vulnerabilities of chaos-based RNGs and underlines that deterministic chaos itself cannot be considered as an entropy source for generation of random numbers. Copyright (C) EPLA, 2020.

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A novel attack system is proposed to reveal the vulnerabilities threats of a microcomputer-based random number generator (RNG). Convergence of the proposed attack system is proved using auto-synchronization. Unknown parameters of the microcomputer-based RNG are revealed where the available information are the design of the RNG and a scalar time series observed from the chaotic system used as the core of the RNG. Numerical results verifying the feasibility of the attack system are given such that, next bit can be predicted while the same output sequence of the RNG can be generated.

This paper presents a comparative study on continous-time chaos-based random number generation methods regarding their robustness against changes in chaos controlling parameters and external interference. Chaotic systems suggest enabling high throughput random data without need for post-processing and with less complex hardware. However, due to effects of aging or fabrication process variations, the chaos controlling parameters of the random number generator may change. Furthermore, external interference can be applied on the chaotic oscillator to manipulate its output. Therefore, in a chaotic RNG, the bit generation method should be immune to parameter variation and external interference. In this study, two widely used methods for random number generation have been compared: 1) Regular sampling of chaotic waveform (RSCW), and 2) Chaotic sampling of regular waveform (CSRW). A double-scroll chaotic system is chosen as the chaotic oscillator and it is numerically simulated in normalized time domain to generate random bit sequences using both methods. Applying the concepts of autocorrelation and approximate entropy to the output bitstreams, the robustness of the two bit generation methods against parameter variation and external interference have been compared. It is demonstrated that chaotic sampling of regular waveform method provides more robustness against parameter changes and external interference compared to regular sampling of chaotic waveform method.

Many problems in daily life cannot be solved by using classical mathematical methods for having an infinite solution space. Therefore, it is recommended to use meta-heuristic optimization methods that reduce the infinite solution space and based on the mathematical prediction principle in solving similar problems. In order to increase the performance of meta-heuristic optimization methods, number generator and chaotic maps are used. In this article, a new method of chaotic optimization has been developed and logistic and singer maps are used in the proposed optimization method. In order to test the performance of the proposed method, 6 different benchmarking functions and 3 different swarm-based optimization methods were used. The proposed method has produced more optimum results for all functions. In this way, it has been tried to prevent the integration of swarm optimization methods into local solutions.

Deterministic methods of processing bit-streams have been proposed to produce completely accurate results with stochastic logic. Long latency is the main issue with these methods. To process m n-bit precision numbers, bit-streams of 2^m×n) bits must be generated. In this work, we propose a context-aware bit-stream generator that improves the performance of these deterministic methods.

A novel estimate system is proposed to discover the security vulnerabilities of a chaos based RSA algorithm and a chaos based random number generator (RNG) it contains. Convergence of the estimate system is proved using auto-synchronization. Secret parameter of the target chaos based RNG are recovered where the available information are the structure of the chaos based RSA algorithm and a scalar time series observed from the target chaotic system. Simulation and numerical results verifying the feasibility of the estimate system are given such that, next bit can be predicted while the same output bit sequence of the chaos based RNG, used together with RSA algorithm, can be regenerated.

In this paper, we investigate how special is the choice of parameter values in the three-dimensional nonlinear system, proposed by Akgul and Pehlivan (2016), in producing a system, which exhibits chaos but has no real equilibrium states. Also, a data hiding method with a three-dimensional chaotic system without equilibrium point, developed by Akgul and Pehlivan, is realized. Numerous encryption studies have recently been made based on chaos. Encryption processes that are used with chaos bring about some security deficiencies in some cases. Steganography, unlike encryption studies, helps communicate the secret data by hiding it in an innocent-looking cover in order to avoid detection by third parties at first glance. In this work, a novel chaos-based data hiding method that hides an image with a different color into color images is proposed. Via the proposed method, data are hidden in bit spaces with the help of the chaotic random number generator (RNG). The generated random numbers are found with a chaotic system without equilibrium point, which is new in the literature. Shilnikov method cannot be applied to find whether the system is chaotic or not because they cannot have homoclinic or heteroclinic orbits. Thus, it can be useful in several engineering applications, especially in chaos-based cryptology and coding information. In the study, bits are hidden in pixels indicated by numbers generated by RNG. As the order of the hiding process is made randomly on a chaotic level, it has made data hiding algorithm stronger. The proposed method hides the data in cover image in such a way that it cannot be easily detected. Furthermore, the proposed method has been evaluated with steganalysis methods and image distortion measurement method PSNR. The chaos-based steganography method realized here has produced more best results in image distortion measurement method PSNR than other studies in the literature.

A novel estimating system is proposed to find out the security weaknesses of a random number generator (RNG) based on a chaotic jerk system. Convergence of the estimating system is proved using auto-synchronization. Unknown parameter of the target RNG is revealed where the public information are the design of the RNG and a scalar time series observed from the target chaotic jerk system. Simulation and numerical results verifying the feasibility of the estimating system are given such that, next bit can be predicted while the same output bit sequence of the RNG can be regenerated.

We have developed a random-number-generator (RNG) named “spin dice,” which employs the stochastic nature of spin-torque switching (STS) in a magnetic tunnel junction. The principle of the idea is that the switching probability first tuned around 0.5 is varied linearly with the applied current. After that, the switching results are converted into binary random numbers. We fabricated several types of “spin dice” by combining magnetic tunnel junctions and single-board microcomputer, and achieved generation speed of random numbers up to several hundred kbit/sec. Because STS is scalable and magnetic tunnel junctions have compatibility to semiconductor fabrication process, “spin dice” can be considered as a promising candidate for truly random-number-generator (TRNG) for security applications.

A novel predicting system is proposed to find out the security weaknesses of a chaotic random number generator (RNG). Convergence of the predicting system is proved using auto-synchronization. Secret parameter of the target chaotic RNG is revealed where the public information are the design of the chaotic RNG and a scalar time series observed from the target chaotic system. Simulation and numerical results verifying the feasibility of the predicting system are given such that, next bit can be predicted while the same output bit sequence of the chaotic RNG can be regenerated.

This paper proposes a well-optimized FPGA implementation of a chaos-based cryptosystem for real-time image encryption and decryption. A highly sensitive Pseudo-Random Number Generator (PRNG) based on the Lorenz chaotic system is designed to generate pseudo-random numbers. A high-quality encryption key is acquired by encrypting the numbers of a 128-bit counter using the PRNG. For image encryption, the image is first decomposed into 128-bit blocks. Then, the blocks are encrypted by XORing pixels with the key stream. [Formula: see text] cycles of encryption can be achieved to increase complexity. Finally, the blocks are concatenated to form an encrypted image. The algorithm is designed, implemented, and validated on the Xilinx Zynq FPGA platform using the Vivado/System Generator tool. The hardware design is well optimized for pipeline processing and low resource utilization. The experimental synthesis indicates that the provided architecture achieves high performance in terms of frequency and throughput. The encryption scheme is evaluated and analyzed by several tools and tests using different images. The experimental simulation results demonstrate that the hardware implementation is faster than a software implementation while maintaining the technique’s effectiveness. The proposed hardware implementation is extremely adopted for secret image encryption and decryption that can be used in real-time applications.

Objective: To determine attitude of undergraduate medical student's towards immigration, including preferred choice and reasons for immigration. Study Design: Cross-Sectional Study. Place and Duration of Study: The study was carried out on students of Wah Medical College, from January 2019 to June 2019. Materials and Methods: All students at medical college were included in the sampling frame. A sample of 300 students was taken by random sampling using random number generator. A questionnaire was formulated comprisingoftwoparts.Thefirstpartofquestionnairecomprisedofcloseended questionsabouttheageof students their gender, year of education, preferred choice for specialization, desire to migrate or not and preferred destination for migration The second part included reasons for migration and non-migration. The data was analyzed on SPSS version 21. Results: Almost half of the students (48.3%) showed intention towards migration. Those who wanted to migrate, United Kingdom was the top choice (27.9%). Better job opportunities, family reasons and medical facilities were the most common reasons for migration while intention to serve the country, family issues and lack of financial resources were the main reasons to stay in the country. Conclusion: Half of the students intend to migrate to other countries and favorite destination for work is United Kingdom.

IDMs are getting more effective and secure with biometric recognition and more privacy-preserving with advanced cryptosystems. In order to meet privacy and security needs of an IDM, the cryptographic background should rely on reliable random number generation. In this study, a Biometric Random Number Generator (BRNG) is proposed which plays a crucial role in a typical cryptosystem. The proposed novel approach extracts the high-frequency information in biometric signal which is associated with uncertainty existing in nature of biometrics. This bio-uncertainty, utilized as an entropy source, may be caused by sensory noise, environmental changes, position of the biometric trait, accessories worn, etc. The filtered nondeterministic information is then utilized by a postprocessing technique to obtain a random number set fulfilling the NIST 800-22 statistical randomness criteria. The proposed technique presents random number sequences without need of an additional hardware.

This paper presents the results of research that aims to find a suitable, reliable, and lightweight pseudorandom number generator for constrained devices used in the Internet of things. Within the study, three reduced versions of the xorshift+ generator are built. They are tested using the TestU01 suite as well as the NIST suite to measure their ability to produce randomness and performance values along with some other existing generators. The best of our reduced variations according to our tests, called the xorshiftR+, demonstrated great suitability for lightweight devices considering its randomness, performance, and resource usage.

The advent of more complicated control charting schemes has necessitated the use of Monte Carlo simulation (MCS) methods. Unfortunately, few sources exist to study effective design and validation of MCS methods related to control charting. This paper describes the design, issues, considerations and limitations for conducting normal-based control chart MCS studies, including choice of random number generator, simulation size requirements, and accuracy/error in simulation estimation. This paper also describes two design strategies for MCS for control chart evaluations and provides the programming code. As a result, this paper hopes to establish de facto MCS schemes aimed at guiding researchers and practitioners in validation and control-chart evaluation MCS design.

Random numbers can be generated from a calculation of mathematical formulas. Such random numbers are often referred to as pseudo random numbers, random numbers are used for various algorithms, especially cryptographic algorithms such as AES, RSA, IDEA, GOST that require the use of Middle-Square Method random numbers which is very useful for adding research references to algorithms concerning random number generator and better understand how random numbers are generated using the Middle-Square Method algorithm. Both data collection and report making as for the objectives achieved in the form of understanding random numbers and knowing the algorithm process, compile a program designed to be used as an alternative to random numbers for various purposes, especially in cryptographic algorithms.

The Regional Song Game is a game that educates players to hone the ability of knowledge about folk songs in the form of questions given the Regional Song game. With the game Regional Songs, players can expand the ability of players about the knowledge of regional songs. Aside from being a means of entertainment, games can also be an exciting learning medium and do not make players bored, so it becomes a pleasant learning atmosphere. The linear congruent method (LCM) is a random number generator method that is widely used by computer programs. The application of the Linear Congruent Method (LCM) in the Regional Song game is intended to randomize the questions that will be displayed by the Regional Song game. Regional Songs Game is an application designed to provide insights about folk songs for the players. This game aims to reintroduce folk songs to the people lost by the ages.

Proper operation of the power substations is of great importance for power network reliability, stability and uninterrupted power supply. Distributed generation provides higher reliability in power supply, but still, there are contingencies in the electric power production and supply process, which lead to outages in the power supply. In this paper, a method for substations’ reliability estimation with distributed generation is presented based on Markov Chain Monte Carlo method. The method considers the possible substation operation states and using random number generator in MATLAB, it simulates faults and calculates the substations’ reliability. The method is demonstrated on two cases of 110/35 kV substations, each consisting of two transformers and distributed generator, analysing the best placement for the distributed generation.

The output randomness from a random number generator can be certified by observing the violation of quantum contextuality inequalities based on the Kochen-Specker theorem. Contextuality can be tested in a single quantum system, which significantly simplifies the experimental requirements to observe the violation comparing to the ones based on nonlocality tests. However, it is not yet resolved how to ensure compatibilities for sequential measurements that is required in contextuality tests. Here, we employ a modified Klyachko-Can-Binicio\u{g}lu-Shumovsky contextuality inequality, which can ease the strict compatibility requirement on measurements. On a trapped single \Ba ion system, we experimentally demonstrate violation of the contextuality inequality and realize self-testing quantum random number expansion by closing detection loopholes. We perform $1.29 \times 10^8$ trials of experiments and extract the randomness of $8.06 \times 10^5$ bits with a speed of 270 bits s$^{-1}$. Our demonstration paves the way for the practical high-speed spot-checking quantum random number expansion and other secure information processing applications., Comment: Main text: 12 pages, 5 figures, Supplementary Materials: 5 pages

The low-latency requirements of a practical loophole-free Bell test preclude time-consuming post-processing steps that are often used to improve the statistical quality of a physical random number generator (RNG). Here we demonstrate a post-processing-free RNG that produces a random bit within 2.4(2) ns of an input trigger. We use weak feedback to eliminate long-term drift, resulting in 24 hour operation with output that is statistically indistinguishable from a Bernoulli process. We quantify the impact of the feedback on the predictability of the output as less than 6.4×10(−7) and demonstrate the utility of the Allan variance as a tool for characterizing non-idealities in RNGs.

This study was aimed at verifying the possibility of mentally influencing from a distance an electronic device based on a True Random Number Generator (TRNG). Thirteen adult participants contributed to 100 trials, each comprised of three samples of data each of 15 minutes’ duration: one for mental pre-interaction, one for mental interaction, and one for mental post-interaction. For each of these samples, at the end of each minute, the data sequence generated by the random number generator was analysed with two specific tests called “Frequency” and “Runs”, in order to determine the degree of randomness of the sequence. The only evidence of an effect of distant mental interaction is an average increase of approximately 50%, with respect to control data, of the number of samples within which the pre-determined statistical threshold was exceeded in both tests. Although the effect of distant mental interaction is still weak, we believe that the results of this study represent a proof-of-concept for the construction of electronic devices susceptible to distant mental influence.

Computer system security has related to security of software or the information processed. The underlying hardware used for information processing has considered to as trusted. The emerging attacks from Hardware Trojans (HTs) violate this root of trust. The attacks are in the form of malicious modification of electronic hardware at different stages; possess major security concern in the electronic industries. An adversary can mount HT in a net of the circuit, which has low transition probability. In this paper, the improvement of the transition probability by using test points and weighted random patterns is proposed. The improvement in the transition probability can accelerate the detection of HTs. This paper implements weighted random number generator techniques to improve the transition probability. This technique is evaluated on ISCAS 85’ benchmark circuit using PYTHON and SYNOPSYS TETRAMAX tool.

Security ceremonies extend cryptographic protocols with models of human users to allow us to take human behaviors into account when reasoning about security. Actor-network procedures (ANPs) are a well-known formal model of security ceremonies, and procedure derivation logic (PDL) allows us to reason logically about ANPs. In a security ceremony, different nodes may have different capabilities: computers can encrypt and decrypt messages, whereas humans cannot; a biometric device can capture biometric information, whereas a random number generator used in e-banking cannot; and so on. Furthermore, even if a node has the decryption capability, it must also know the encryption key to decrypt a message. ANPs do not support explicitly specifying node capabilities. In this paper, we extend ANPs to deal with heterogeneous devices by explicitly specifying the nodes’ capabilities. We also modify PDL to take into account the knowledge of participants at different points in time. All this allows us to reason about secrecy and authentication in ceremonies with different kinds of devices and human users.

The encryption algorithms discussed in Chapter 2 require a source of random data to generate new private/public key pairs or symmetric keys. Most computers do not have a hardware-based random number generator, so software developers need to use a software-based implementation to generate random numbers that are suitable. In this chapter we will look at how to generate secure random numbers in the .NET Framework / .NETCore.

The paper proposes a new general method for producing a multilevel permutation functioning as an m-tree traversal. It is composed of two basic steps: a random number generator of period length equal m to determine which child to traverse, and recursive permutation in which permutated the subtree if found. The test results proved that the suggested method of permutation is successful depending on the correlation measure.

Review of Skoog Stahlgren G, Tyrstrup M, Edlund C, et al . Penicillin V four times daily for five days versus three times daily for 10 days in patients with pharyngotonsillitis caused by group A streptococci: randomised controlled, open label, non-inferiority study. BMJ 2019;367:l5337. Open label, randomised controlled non-inferiority study. Allocation: central randomisation by computerised random number generator. Setting: 17 primary health centres in Sweden. Intervention: randomised to either Penicillin V 800mg four times per day for 5 days (total 16g) or Penicillin V 1000mg three times per day for 10 days. (total 30g). Patients: 422 patients, aged 6 years and older with pharyngotonsillitis caused by group A streptococci and with three or …

This paper introduces a random number generator (RNG) based on the avalanche noise of two diodes. A true random number generator (TRNG) generates true random numbers with the use of the electronic noise produced by two avalanche diodes. The amplified outputs of the diodes are sampled and digitized. The difference between the two concurrently sampled and digitized outputs is calculated and used to select a seed and to drive a pseudo-random number generator (PRNG). The PRNG is an xorshift generator that generates 1024 bits in each cycle. Every sequence of 1024 bits is moderately modified and output. The TRNG delivers the next seed and the next cycle begins. The statistical behavior of the generator is analyzed and presented.