Methods of presenting the fundamentals of bookkeeping

Thesis (Ed.M.)--Boston Universit

Alien Registration- Pinette, Florette (Jackman, Somerset County)

https://digitalmaine.com/alien_docs/6804/thumbnail.jp

In-text and out-of-text engagement: interactional features in students\u27 academic writing and academic engagement

While student engagement theory recognizes writing as an engaging activity, there have been few studies that explore the levels of engagement within college students\u27 academic writing. Analyses of in-text interactions between writers and their imagined reader(s) can uncover writers\u27 attitudes about themselves as writers and as participants in the academic community. This study looked specifically at students\u27 in-text interaction in the context of overall student engagement. Making a connection between interactional features in writing and overall student engagement provided a new perspective by which professors and administrators can evaluate students\u27 academic integration. This study combined text analysis and interviews with seven College Composition I students at a public university to investigate students\u27 out-of-text engagement, in-text engagement, and the relationship between the two. Findings suggested that participants consider themselves engaged student participants, but not writers participating in the academic community. Students\u27 in-text interactions included self-mentions, attitude markers, and reader references, which often reflected participants\u27 reported comfort and confidence within the community

A GIS Analysis of the Environmental Variables Related to Rift Valley Fever Outbreaks

Rift Valley fever is a mosquito-borne disease that causes widespread febrile illness and mortality in domestic animals as well as humans (Gaff, 2007). Rift Valley fever virus was first isolated in 1931 (Daubney, 1931), and since then, outbreaks have occurred in sub-Saharan Africa, southern Africa, Egypt, Saudi Arabia, Yemen and Madagascar, proving it to be a virus able to invade ecologically diverse regions (Gaff, 2007). The potential introduction of Rift Valley fever into the United States suggests the potential for human infection and major economic disruption. It is important to understand the role environmental variables have played in historical outbreaks to further understand the disease and the possibility of translocation of the virus. This study examines the relationship between both temperature and rainfall rates and Rift Valley fever outbreaks in Kenya, Madagascar, and South Africa. Datasets employed in the analysis are several including a long term dataset (1982-2004), short term datasets (1999-2005; 1999-2007) and datasets covering the Rift Valley fever outbreaks in Kenya (2006, 2007), Madagascar (2008, 2009), and South Africa (2008, 2009). Geographic information systems analysis, time series analysis, and statistical analyses are used to gauge the relationships among temperature, rainfall, and Rift Valley fever outbreak events. Results of this study show a relationship between rainfall and Rift Valley fever in Kenya, but not in Madagascar or South Africa. Although a positive rainfall anomaly was found at the beginning of the Rift Valley fever outbreak in Kenya, further analysis finds above average rainfall anomalies prior to the outbreak with no Rift Valley fever activity reported. No significant differences are found among the historical temperature ranges and temperature ranges during Rift Valley fever outbreaks in Kenya, Madagascar or South Africa. By better understanding these two important variables, disease transmission models for Rift Valley will later be able to predict future outbreaks and spread of disease. Studies about variables related to disease transmission models like this further strengthen these models, thus providing policymakers the ability to design systems to enhance preventative and control measures

Cryptanalysis of a Generalized Subset-Sum Pseudorandom Generator

We present attacks on a generalized subset-sum pseudorandom generator, which was proposed by von zur Gathen and Shparlinski in 2004. Our attacks rely on a sub-quadratic algorithm for solving a vectorial variant of the 3SUM problem, which is of independent interest. The attacks presented have complexities well below the brute-force attack, making the generators vulnerable. We provide a thorough analysis of the attacks and their complexities and demonstrate their practicality through implementations and experiments

Un parcours de l'informe vers la ligne

Le travail plastique présenté ici doit être compris comme un parcours de l’informe vers la ligne. Il s’agit donc de comprendre les enjeux de ces deux notions tout en mettant en dialogue les travaux proposés avec la peinture des années 60 en particulier, ainsi que la calligraphie chinoise, mais aussi la poésie. Comment envisager l’idée d’informe ? Quelle est sa relation avec le hasard et le temps ? Quel mouvement transforme une tache en ligne ? Quel est le rôle du regard et de l’attention dans ce projet

A Variation on Knellwolf and Meier\u27s Attack on the Knapsack Generator

Pseudo-random generators are deterministic algorithms that take in input a random secret seed and output a flow of random-looking numbers. The Knapsack generator, presented by Rueppel and Massey in 1985 is one of the many attempt at designing a pseudo-random generator that is cryptographically secure. It is based on the subset-sum problem, a variant of the Knapsack optimization problem, which is considered computationally hard. In 2011 Simon Knellwolf et Willi Meier found a way to go around this hard problem and exhibited a weakness of this generator. In addition to be able to distinguish the outputs from the uniform distribution, they designed an algorithm that retrieves a large portion of the secret. We present here an alternate version of the attack, with similar costs, that works on the same range of parameters but retrieves a larger portion of the secret

Practical Seed Recovery of Fast Cryptographic Pseudo Random Number Generators

Trifork is a family of pseudo-random number generators described in 2010 by Orue et al. It is based on Lagged Fibonacci Generators and has been claimed as cryptographically secure. In 2017 was presented a new family of lightweight pseudo-random number generators: Arrow. These generators are based on the same techniques as Trifork and designed to be light, fast and secure, so they can allow private communication between resource-constrained devices. The authors based their choices of parameters on NIST standards on lightweight cryptography and claimed these pseudo-random number generators were of cryptographic strength. We present practical implemented algorithms that reconstruct the internal states of the Arrow generators for different parameters given in the original article. These algorithms enable us to predict all the following outputs and recover the seed. These attacks are all based on a simple guess-and-determine approach which is efficient enough against these generators. We also present an implemented attack on Trifork, this time using lattice-based techniques. We show it cannot have more than 64 bits of security, hence it is not cryptographically secure

Attacks on Pseudo Random Number Generators Hiding a Linear Structure

We introduce lattice-based practical seed-recovery attacks against two efficient number-theoretic pseudo-random number generators: the fast knapsack generator and a family of combined multiple recursive generators. The fast knapsack generator was introduced in 2009 by Von Zur Gathen and Shparlinski. It generates pseudo-random numbers very efficiently with strong mathematical guarantees on their statistical properties but its resistance to cryptanalysis was left open since 2009. The given attacks are surprisingly efficient when the truncated bits do not represent a too large proportion of the internal states. Their complexities do not strongly increase with the size of parameters, only with the proportion of discarded bits. A multiple recursive generator is a pseudo-random number generator based on a constant-recursive sequence. A combined multiple recursive generator is a pseudo-random number generator based on combining two or more multiple recursive generators. L’Écuyer presented the general construction in 1996 and a popular instantiation deemed MRG32k3a in 1999. We use algebraic relations of both pseudo-random generators with underlying algebraic generators to show that they are cryptographically insecure. We provide a theoretical analysis as well as efficient implementations