Sharif Digital Repository

ARX algorithms are a class of symmetric-key algorithms constructed by Addition, Rotation, and XOR, which achieve the best software performances in low-end microcontrollers. To evaluate the resistance of an ARX cipher against differential cryptanalysis and its variants, the recent automated methods employ constraint satisfaction solvers, such as SMT solvers, to search for optimal characteristics. The main difficulty to formulate this search as a constraint satisfaction problem is obtaining the differential models of the non-linear operations, that is, the constraints describing the differential probability of each non-linear operation of the cipher. While an efficient bit-vector differential... 

This study presents a steady-state Markov chain model to predict the long-term probability of drought conditions. The research aims to propose a rigorous framework for statistical analysis of drought characteristics and its trends over time for a large area of aquifers and plains in Iran. For this purpose, two meteorological indicators called the Standardized Precipitation Index (SPI), and the Groundwater Resource Index (GRI) are examined. The groundwater drought study includes more than 26,000 wells in about 600 meteorological stations over 20 years being surveyed daily. This study discusses the spatial interpolation of drought steady-state probabilities based on recorded SPI and GRI data... 

In this paper, an analytical method is developed to compute the project completion time distribution in a dynamic PERT network, where the activity durations are exponentially distributed random variables. The projects are generated according to a renewal process and share the same facilities. Thus, these projects cannot be analyzed independently. The authors' approach is to transform this dynamic PERT network into a stochastic network and, then, to obtain the project completion time distribution by constructing a proper continuous-time Markov chain. This dynamic PERT network is represented as a network of queues, where the service times represent the durations of the corresponding activities... 

The aim of this work is to investigate the non-equilibrium effects of phase change in cavitating flows. For this purpose, the concept of phase change thermodynamic probability is used along with homogeneous model to simulate two-phase cavitating flows. For simulation of unsteady behaviors of cavitation, which have practical applications, unsteady PISO algorithm based on the non-conservative approach is utilized. For multi-phase simulation, single-fluid Navier-Stokes equations, along with the volume fraction transport equation, are employed. In this paper, phase change thermodynamics probabilities and cavitation model is briefly summarized. Thus, derivation of the cavitation model, starting... 

This paper introduces a probabilistic framework to quantify the spatial distribution of cracking and crushing in rectangular reinforced concrete shear walls at different drift ratios. In this research, a comprehensive probabilistic spatial analysis is conducted on an extensive collected database of reinforced concrete shear walls tested under the quasi-static cyclic loading. The database includes 235 images of 72 damaged walls with various geometry and material properties at different drift ratios between 0.0 and 4.0%. Various image processing filters are implemented to the images to highlight the wall areas that are more prone to cracking and crushing. Then, advanced statistical analysis is... 

Delay Tolerant Networks (DTNs) are sparse and highly dynamic networks where intermittent connectivity is a common event. In these networks, nodes have time-limited connection opportunity to other moving nodes. Therefore, routing is a major challenge in these networks and researchers have tried to design efficient routing algorithms. Important performance metrics of desired routing algorithms are high delivery probability, low energy consumption and low end to end latency. In this paper, we propose an energy-efficient routing algorithm which is based upon the encounter probabilities of nodes. We use these encounter probabilities to derive a utility metric. Moreover, we utilize assumptions and... 

Fast, accurate, and detailed Soft Error Rate (SER) estimation of digital circuits is essential for cost-efficient reliable design. A major step to accurately estimate a circuit SER is the computation of failure probability, which requires the computation of three derating factors, namely logical, electrical, and timing derating. The unified treatment of these derating factors is crucial to obtain accurate failure probability. Existing SER estimation techniques are either unscalable to large circuits or inaccurate due to lack of unified treatment of all derating factors. In this paper, we present fast and efficient algorithms to estimate SERs of circuit components in the presence of single... 

Discrete-time Markov Chains (MCs) and Markov Decision Processes (MDPs) are two standard formalisms in system analysis. Their main associated quantitative objectives are hitting probabilities, discounted sum, and mean payoff. Although there are many techniques for computing these objectives in general MCs/MDPs, they have not been thoroughly studied in terms of parameterized algorithms, particularly when treewidth is used as the parameter. This is in sharp contrast to qualitative objectives for MCs, MDPs and graph games, for which treewidth-based algorithms yield significant complexity improvements. In this work, we show that treewidth can also be used to obtain faster algorithms for the... 

Using a proper distribution function for speech signal or for its representations is of crucial importance in statistical-based speech processing algorithms. Although the most commonly used probability density function (pdf) for speech signals is Gaussian, recent studies have shown the superiority of super-Gaussian pdfs. A large research effort has focused on the investigation of a univariate case of speech signal distribution; however, in this paper, we study the multivariate distributions of speech signal and its representations using the conventional distribution functions, e.g., multivariate Gaussian and multivariate Laplace, and the copula-based multivariate distributions as candidates.... 

An embedded time interval data acquisition system (DAS) is developed for zero power reactor (ZPR) noise experiments. The system is capable of measuring the correlation or probability distribution of a random process. The design is totally implemented on a single Field Programmable Gate Array (FPGA). The architecture is tested on different FPGA platforms with different speed grades and hardware resources. Generic experimental values for time resolution and inter-event dead time of the system are 2.22 ns and 6.67 ns respectively. The DAS can record around 48-bit × 790 kS/s utilizing its built-in fast memory. The system can measure very long time intervals due to its 48-bit timing structure... 

In this letter, a new molecular modulation scheme for nanonetworks is proposed. To evaluate the scheme, a system model based on the Poisson distribution is introduced. The error probability of the proposed scheme as well as that of two previously known schemes, the concentration and molecular shift keying modulations, are derived for the Poisson model by taking into account the error propagation effect of previously decoded symbols. The proposed scheme is shown to outperform the previously introduced schemes. This is due to the fact that the decoding of the current symbol in the proposed scheme does not encounter propagation of error, as the decoding of the current symbol does not depend on... 

Wind and solar power are known to be highly influenced by weather events and may ramp up or down abruptly. Such events in the power production influence not only the availability of energy, but also the stability of the entire power grid. By analysing significant amounts of data from several regions around the world with resolutions of seconds to minutes, we provide strong evidence that renewable wind and solar sources exhibit multiple types of variability and nonlinearity in the time scale of seconds and characterise their stochastic properties. In contrast to previous findings, we show that only the jumpy characteristic of renewable sources decreases when increasing the spatial size over... 

In non-linear scales, the matter density distribution is not Gaussian. Consequently, the widely used two-point correlation function is not adequate anymore to capture the matter density field's entire behaviour. Among all statistics beyond correlation functions, the spherical contact (or equivalently void function), and nearest neighbour distribution function seem promising tools to probe matter distribution in non-linear regime. In this work, we use haloes from cosmological N-body simulations, galaxy groups from the volume-limited galaxy group and central galaxies from mock galaxy catalogues, to compare the spherical contact with the nearest neighbour distribution functions. We also... 

This paper proposes a robust investment and operation model to attend the power and heat needs of a microgrid (MG) connected to the distribution system. The optimization algorithm decides on the best investment and operation of combined heat and power (CHP), boilers, PV power generation and battery energy storage systems (BESS). For the BESS, the algorithm estimates the optimal energy storage capacity (MWh) as well as the maximum hourly delivery capacity (MW). The non-linear and non-concave heat rate chart is recast by a mix-integer linear model to have a tractable and precise model. The model considers the uncertain in some parameters using probability density function (pdf) to portrait its... 

In this paper, the Markov models, eigenvectors and eigenvalue concepts are used to propose a methodology for analyzing the transient reliability of a system with identical components and identical repairmen. The components of the systems under consideration can have two distinct configurations, namely; they can be arranged in series or in parallel. A third case is also considered, in which the system is up (good) if k-out-of-n components are good. For all three cases, a procedure is proposed for calculating the transient probability of the system availability and the duration of the system to reach the steady state. © Sharif University of Technology, February 2007  

Oil spills are serious environmental issues that potentially can cause adverse effects on marine ecosystems. In some marine areas, like the Baltic Sea, there is a large number of wrecks from the first half of the 20th century, and recent monitoring and field work have revealed release of oil from some of these wrecks. The risk posed by a wreck is governed by its condition, hazardous substances contained in the wreck and the state of the surrounding environment. Therefore, there is a need for a common standard method for estimating the risks associated with different wrecks. In this work a state-of-the-art model is presented for spatial and stochastic risk assessment of oil spills from... 

Different causes lead to accidental oil spills from fixed and mobile sources in the marine environment. Therefore, it is essential to have a systematic plan for mitigating oil spill consequences. In this research, a general DSS is proposed for passive and active response planning in Persian Gulf, before and after a spill. The DSS is based on NOAA's advanced oil spill model (GNOME), which is now linked with credible met-ocean datasets of CMEMS and ECMWF. The developed open-source tool converts the results of the Lagrangian oil spill model to quantitative parameters such as mean concentration and time of impact of oil. Using them, two new parameters, emergency response priority number (ERPN)... 

This paper presents an optimization model for the calculation of the minimum number of phasor measurement units (PMUs) in electrical power networks. The problem constraint is a predefined probability of observability associated with each bus. The mixed-integer programming is used for the proposed optimization and an efficient linearization technique is proposed to convert the nonlinear function representing the probability of observability into a set of linear expressions. The PMU placement is staged in a multi-year planning horizon due to financial and physical constraints. The average probability of observability is maximized at the intermediate planning stages, subject to a limited number... 

This paper presents an optimization model for the calculation of the minimum number of phasor measurement units (PMUs) in electrical power networks. The problem constraint is a predefined probability of observability associated with each bus. The mixed-integer programming is used for the proposed optimization and an efficient linearization technique is proposed to convert the nonlinear function representing the probability of observability into a set of linear expressions. The PMU placement is staged in a multi-year planning horizon due to financial and physical constraints. The average probability of observability is maximized at the intermediate planning stages, subject to a limited number... 

The performance guarantees in recovery of a sparse vector in a compressed sensing scenario, besides the reconstruction technique, depends on the choice of the sensing matrix. The so-called restricted isometry property (RIP) is one of the well-used tools to determine and compare the performance of various sensing matrices. It is a standard result that random (Gaussian) matrices satisfy RIP with high probability. However, the design of deterministic matrices that satisfy RIP has been a great challenge for many years now. The common design technique is through the coherence value (maximum modulus correlation between the columns). In this paper, based on the Paley graphs, we introduce...