The pioneering WiSARD weightless neural classifier is based on the collective response of RAM-based neurons. The ability of producing prototypes, analog to “mental images”, from learned categories, was first introduced in the DRASiW model. By counting the frequency of write accesses at each RAM neuron during the training phase, it is possible to associate the most accessed addresses to the corr...

Oblivious RAM (O-RAM) is a useful primitive that allows a client to hide its data access patterns from an untrusted server in storage outsourcing applications. This paper proposes novel O-RAM constructions that achieves poly-logarithmic worst-case cost, while consuming constant client-side storage. Our techniques for constructing Oblivious RAM are fundamentally different from previous approache...

A word-RAM consists of: • A fixed set of instructions P1, . . . , Pq. Allowed instructions are: – Modular arithmetic and integer division on registers; the standard model for a RAM machine does not have negative numbers, but you can verify that allowing signed integers doesn’t chance the power of the model. – Bitwise operations on registers. – Loading a constant into a register. – Transfering v...

We apply the two-sector production function developed by Ram (1986) to estimate the threshold regression model for Iran, concerning the effect of government size on economic growth. Three government size indicators are used to find out the different threshold points. The results show a non-linear relationship of the Armey curve in Iran, in which the threshold effects corresponding to total gove...

This paper uses the accurate and computationally efficient complex image technique (CIT) to find the electric field and SAR distributions inside a human head illuminated by a finite-length dipole. The human head model used consists of 3 planar layers of lossy dielectrics. The accuracy of the results is verified by comparison with HFSS software. It was found that the CIT requires about 1 minute ...

More generally, the goal of fusion trees is to support the operations insert(x), delete(x), successor(x) and predecessor(x) in o(lgn) time on a transdichotomous RAM. The transdichotomous RAM model of computation was intrdouced in Lecture 2 (Feb. 12, 2003). The data-structure problem defined by these four operations is called the fixed-universe successor problem which was introduced in Lecture 1...

In the faulty-memory RAM model, the content of memory cells can get corrupted at any time during the execution of an algorithm, and a constant number of uncorruptible registers are available. A resilient data structure in this model works correctly on the set of uncorrupted values. In this paper we introduce a resilient priority queue. The deletemin operation of a resilient priority queue retur...

We introduce a Random Attention Model (RAM) allowing for a large class of stochastic consideration maps in the context of an otherwise canonical limited attention model for decision theory. This model relies on a new restriction on the stochastic consideration map, termed Monotonic Attention, which is intuitive and nests many recent contributions in the literature, is implied by the classical L...

BACKGROUND  Improved thromboprophylaxis for acutely ill medical patients relies on valid predictions of thrombotic risks. Our aim was to compare the performance of the Improve and Geneva clinical risk assessment models (RAMs), and to simplify the current Geneva RAM. METHODS  Medical inpatients from eight Swiss hospitals were prospectively followed during 90 days, for symptomatic venous thromb...

Ram seminal plasma increases the fertility of frozen-thawed ram spermatozoa deposited into the cervix. The aim of the current study was to compare the effect of ram seminal plasma to that of bull seminal plasma, dog prostatic fluid, protein-free TALP TrilEq (Triladyl with 0.5 mt of Equex STM paste added to each 100 mt) and heat-treated skim milk on longevity and percentages of progressively mot...