Two-sources Randomness Extractors for Elliptic Curves

This paper studies the task of two-sources randomness extractors for elliptic curves defined over finite fields $K$, where $K$ can be a prime or a binary field. In fact, we introduce new constructions of functions over elliptic curves which take in input two random points from two differents subgroups. In other words, for a ginven elliptic curve $E$ defined over a finite field $\mathbb{F}_q$ and two random points $P \in \mathcal{P}$ and $Q\in \mathcal{Q}$, where $\mathcal{P}$ and $\mathcal{Q}$ are two subgroups of $E(\mathbb{F}_q)$, our function extracts the least significant bits of the abscissa of the point $P\oplus Q$ when $q$ is a large prime, and the $k$-first $\mathbb{F}_p$ coefficients of the asbcissa of the point $P\oplus Q$ when $q = p^n$, where $p$ is a prime greater than $5$. We show that the extracted bits are close to uniform. Our construction extends some interesting randomness extractors for elliptic curves, namely those defined in \cite{op} and \cite{ciss1,ciss2}, when $\mathcal{P} = \mathcal{Q}$. The proposed constructions can be used in any cryptographic schemes which require extraction of random bits from two sources over elliptic curves, namely in key exchange protole, design of strong pseudo-random number generators, etc

I2PA : An Efficient ABC for IoT

Internet of Things (IoT) is very attractive because of its promises. However, it brings many challenges, mainly issues about privacy preserving and lightweight cryptography. Many schemes have been designed so far but none of them simultaneously takes into account these aspects. In this paper, we propose an efficient ABC scheme for IoT devices. We use ECC without pairing, blind signing and zero knowledge proof. Our scheme supports block signing, selective disclosure and randomization. It provides data minimization and transactions' unlinkability. Our construction is efficient since smaller key size can be used and computing time can be reduced. As a result, it is a suitable solution for IoT devices characterized by three major constraints namely low energy power, small storage capacity and low computing power

RELATIVE IMPACT OF NATIONAL AND FOREIGN SAVINGS IN THE PROCESS OF ECONOMIC GROWTH: THE CASE OF SENEGAL

The basic questions we address in this dissertation are the following: What was the relation between national savings and foreign savings during the 1960-1976 period for Senegal? What was the relative contribution of these two types of financing to economic growth? A review of the literature reveals the coexistence of two main hypotheses. The first one stipulates that foreign financing and domestic financing are substitutes, whereas, the second one claims that they are, at the best, complements. Numerous empirical studies using single equation models support the substitutability hypothesis. In other terms, they show a negative relationship between national and external savings. We discuss the various limitations of the single equation models and we propose a translog model which allows us to compute the elasticities of substitution between national and external savings. The empirical evidence shows that the elaticities were positive, low and stable for Senegal during the period of study. The positive sign of these elasticities supports the substitutability hypothesis. The next step was to find the net contribution of both foreign finance to the growth rate of income. To reach this goal, a growth model was proposed and the empirical results indicate that the impact of foreign savings was very limited. However, we point out that if foreign aid had been sued to improve the productive capacities of the Senegalese industries, its real impact could have been far greater than the one obtained from the model. The empirical evidence shows, also, that national savings did contribute to economic growth, especially, during the 1960-63 and 1968-76 subperiods. The substitute effect of foreign savings on domestic savings and their limited impact on economic growth lead us to make some policy recommendations about the ways and means to raise and to allocate national savings toward productive investment. Moreover, some suggestions are made about a better use of foreign finance in the process of economic growth and development

Inequality decomposition using the Gibbs output of a Mixture of lognormal distributions

In this paper we model the income distribution using a Bayesian approach and a mixture of lognormal densities. The size of the mixture is determined by Chib (1995)'s method. Using the Federal Expenditure Survey data for the United Kingdom, we detect three groups corresponding to the three classes (poor, middle class and rich). The marked growth in UK income inequality during the late 1970s is increasingly attracting attention. The increasing gap between the poorest and the richest was accompanied by changes in the clustering of incomes in between. Using the decomposable Generalised Entropy (GE) inequality indices, we carry out a within-between group analysis of income inequality in the three identified groups in UK during 1979 to 1996 and show the evolution of the importance of each group. Whereas during the late 1970s the concentration of people around middle income levels began to break up and polarise towards high and low incomes as shown by Jenkins (1996), our Bayesian results show that the inequality within the low and middle income group do not change much and the importance of the high income is the most affected by the fight against inequality that followed the Thatcher period.Income distribution; Generalised Entropy; Mixture models; Gibbs sampler; Marginal likelihood

Evaluation of Woodchip Bioreactor Denitrification Kinetics

Agricultural subsurface drainage is a water management practice used to remove excess water in poorly drained soil. The use of fertilizers combined with subsurface drainage practice affects negatively surface water quality due to nutrient loss. Woodchip bioreactors have previously been used as a technology for removing nitrate from agricultural subsurface drainage. Understanding the mechanism that governs nitrate removal in woodchip bioreactors is crucial for field bioreactor design and application. The objective of this project is to determine woodchip bioreactor denitrification kinetics parameters under different operating conditions including hydraulic retention time, temperature and influent nitrate concentrations. Laboratory column experiments were conducted with influent nitrate concentrations varying from 50 mg N/L to 3 mg N/L at a HRT of 12 hours. The integrated Michaelis Menten equation was used to determine the denitrification kinetics parameters. The half saturation constant was found to be 2.17 mg N/L and the maximum nitrate removal rate was 0.86 mg N/L/H at 22 degree Celsius. The woodchips bioreactor achieved a denitrification rate ranging from 3.02 g NO3 - N/m3/d to 9.80 g NO3 - N/m3/d. At 5 degree Celsius, the bioreactor had a half saturation of 0.58 mg N/L and a maximum removal rate of 0.045 mg /L/H with denitrification rate ranging from 0.52 g N/ m3 /d to 0.28 g N/ m3 /d. At HRTs of 24 hours and 6 hours with an influent nitrate concentration of 10 mg N/L, a 98.70 % and 29.4 % percentage removal was achieved respectively. Nitrite accumulation was observed in all experiments with the highest nitrite effluent concentration of 1.4 mg N/L, observed at 50 mg N/L under 12 hours HRT. The results of this study a better understanding of denitrification kinetics in woodchip bioreactors

Nitrate and Phosphate Removal from Denitrification Bioreactors Using Woodchips, Steel Chips And Agricultural Residue Media

Nitrate and phosphate present in agricultural subsurface drainage water can impact surface water quality thus impacting the environment and human health by causing eutrophication and Methemoglobinemia in young infant. Biological denitrification and phosphate adsorption filters are treatments options that can help reduce nitrate and phosphate concentration from agricultural subsurface drainage before it can be discharged in surface water. The first objective of this dissertation was to determine the Michaelis-Menten kinetics model parameters for nitrate removal in bioreactors using the fresh, aged, and composted woodchips. The composted woodchips achieved a denitrification rate 2.4 times higher than the fresh woodchips which was in term achieved 2.9 times higher denitrification rate than the aged woodchips. Denitrification rates decreased at 5ºC compared to 22ºC for composted woodchips and fresh woodchips. The composted still performed better at low temperatures compared to fresh woodchips. The second objective was to determine the impact of different pairing configurations of woodchips and steel chips on nitrate and phosphate removal capacity and how the pairing configurations affect the DOC and iron leaching from the reactors. Three different reactors pairing configurations were evaluated in this project including woodchips followed by steel chips, steel chips followed by woodchips, and mixed woodchips/steel chips. The effect of low temperature (5℃) on phosphate removal capacity was studied. There was no statistical difference in nitrate and phosphate removed between all three reactors configurations. Three different reactors pairing configurations were evaluated in this project including woodchips followed by steel chips, steel chips followed by woodchips, and mixed woodchips/steel chips. The effect of low temperature (5℃) on phosphate removal capacity was studied. There was no statistical difference in nitrate and phosphate removed between all three reactors configurations

Oceanic-Atmospheric and Hydrologic Variability in Long Lead-Time Forecasting

Water managers throughout the world are challenged with managing scarce resources and therefore rely heavily on forecasts to allocate and meet various water demands. The need for improved streamflow and snowpack forecast models is of the utmost importance. In this research, the use of oceanic and atmospheric variables as predictors was investigated to improve the long lead-time (three to nine months) forecast of streamflow and snowpack. Singular Value Decomposition (SVD) analysis was used to identify a region of Pacific and Atlantic Ocean SSTs and a region of 500 mbar geopotential height (Z500mb) that were teleconnected with streamflow and snowpack. The resulting Pacific and Atlantic Ocean SSTs and Z500mb regions were used to create indices that were then used as predictors in a non-parametric forecasting model. The majority of forecasts resulted in positive statistical skill, which indicated an improvement of the forecast over the climatology or no-skill forecast. The results indicated that derived indices from SSTs were better suited for long lead-time (six to nine month) forecasts of streamflow and snowpack while the indices derived from Z500mb improved short lead-time (3 month) forecasts. In all, the results of the forecast model indicated that incorporating oceanic-atmospheric climatic variability in forecast models can lead to improved forecasts for both streamflow and snowpack

Parliamentary voting rules and strategic candidacy

In this paper we study the vulnerability of parliamentary voting procedures to strategic candidacy. Candidates involved in an election are susceptible to influence the outcome by opting out or opting in. In the context of three-alternative elections and under the impartial anonymous culture assumption, we evaluate the frequencies of such strategic candidacy opportunities.strategic candidacy, parliamentary voting procedures, opting out, opting in, impartial anonymous culture.

Handover Necessity Estimation for 4G Heterogeneous Networks

One of the most challenges of 4G network is to have a unified network of heterogeneous wireless networks. To achieve seamless mobility in such a diverse environment, vertical hand off is still a challenging problem. In many situations handover failures and unnecessary handoffs are triggered causing degradation of services, reduction in throughput and increase the blocking probability and packet loss. In this paper a new vertical handoff decision algorithm handover necessity estimation (HNE), is proposed to minimize the number of handover failure and unnecessary handover in heterogeneous wireless networks. we have proposed a multi criteria vertical handoff decision algorithm based on two parts: traveling time estimation and time threshold calculation. Our proposed methods are compared against two other methods: (a) the fixed RSS threshold based method, in which handovers between the cellular network and the WLAN are initiated when the RSS from the WLAN reaches a fixed threshold, and (b) the hysteresis based method, in which a hysteresis is introduced to prevent the ping-pong effect. Simulation results show that, this method reduced the number of handover failures and unnecessary handovers up to 80% and 70%, respectively