589 research outputs found
The difficulties of staging Shakespeare in the high school
Thesis (M.A.)--Boston Universit
Multi-User Multi-Carrier Differential Chaos Shift Keying Communication System
In this paper, a multi user Multi-Carrier Differential Chaos Shift Keying
(MC-DCSK) modulation is presented. The system endeavors to provide a good
trade-off between robustness, energy efficiency and high data rate, while still
being simple. In this architecture of MC-DCSK system, for each user, chaotic
reference sequence is transmitted over a predefined subcarrier frequency.
Multiple modulated data streams are transmitted over the remaining subcarriers
allocated for each user. This transmitter structure saves energy and increases
the spectral efficiency of the conventional DCSK system.Comment: Accepted in the IEEE International Wireless Communications and Mobile
Computing Conference (IWCMC 2013
Random right eigenvalues of Gaussian quaternionic matrices
We consider a random matrix whose entries are independent Gaussian variables taking values in the field of quaternions with variance . Using logarithmic potential theory, we prove the almost sure convergence, as the dimension goes to infinity, of the empirical distribution of the right eigenvalues towards some measure supported on the unit ball of the quaternions field. Some comments on more general Gaussian quaternionic random matrix models are also made
Quantifying MEV On Layer 2 Networks
This paper addresses the lack of research on quantifying Maximal Extractable
Value (MEV) on Ethereum Layer 2 networks (L2s). Our findings reveal a
substantial amount of MEV to be extracted on L2s, particularly on Polygon, with
a lower bound of $213 million surpassing previous estimates. We observe that
the majority of detected MEV on L2s consists of arbitrage opportunities, as
liquidations are rare. These results emphasize the need for continuous
monitoring and analysis of MEV on L2s, promoting informed decision-making for
network selection and highlighting the associated risks
Road safety for fleets of vehicles
Road safety for fleets of vehicles has been neglected in the insurance literature, mainly because appropriate data and methodology were not available. This article makes a threefold contribution: 1) Produce statistics on current fleets’ road safety offences and accidents using a panel of 20 years of data on truck fleets; 2) relate fleets’ offences to accidents; and 3) identify and classify the riskiest fleets for insurance ratemaking based on past experience in managing road safety. Our main technical innovation to the insurance literature is in the estimation of fleets’ distributions of accidents. For each fleet size (or group of sizes), we estimate the parameters of the negative binomial (NB) distribution of the annual number of accidents according to the characteristics of the fleets, the years, and the number of driver (DRV) and carrier (CAR) road safety violations accumulated in the previous year. When the NB model does not accurately predict the mathematical expectation of the number of accidents of larger fleets, we proceed in two steps. First, we estimate the probability of having zero accidents in a year, and then estimate the negative binomial distribution using the estimated probability of having zero accidents, to weight the zeros of each fleet. To achieve our third objective, we construct risk classes for the vehicle fleets using the predicted accident probabilities obtained from the estimated models. Our results show a substantial heterogeneity between fleets in terms of road safety. This information should be very useful for optimal insurance pricing and better incentives for road safety
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