Carleton University

About: Carleton University is a education organization based out in Ottawa, Ontario, Canada. It is known for research contribution in the topics: Population & Context (language use). The organization has 15852 authors who have published 39650 publications receiving 1106610 citations.

Computation Offloading and Content Caching in Wireless Blockchain Networks With Mobile Edge Computing

Abstract: Blockchain technology has been applied in a variety of fields due to its capability of establishing trust in a decentralized fashion. However, the application of blockchain in wireless mobile networks is hindered by a major challenge brought by the proof-of-work puzzle during the mining process, which sets a high demand for the computational capability and storage availability in mobile devices. To address this problem, we propose a novel mobile edge computing (MEC) enabled wireless blockchain framework where the computation-intensive mining tasks can be offloaded to nearby edge computing nodes and the cryptographic hashes of blocks can be cached in the MEC server. Particularly, two offloading modes are considered, i.e., offloaded to the nearby access point or a group of nearby users. First, we conduct the performance analysis of each mode with stochastic geometry methods. Then, the joint offloading decision and caching strategy is formulated as an optimization problem. Furthermore, an alternating direction method of multipliers based algorithm is utilized to solve the problem in a distributed manner. Finally, simulation results demonstrate the effectiveness of our proposed scheme.

High volatility, thick tails and extreme value theory in value-at-risk estimation

Abstract: In this paper, the performance of the extreme value theory in value-at-risk calculations is compared to the performances of other well-known modeling techniques, such as GARCH, variance–covariance (Var–Cov) method and historical simulation in a volatile stock market. The models studied can be classified into two groups. The first group consists of GARCH(1, 1) and GARCH(1, 1)-t models which yield highly volatile quantile forecasts. The other group, consisting of historical simulation, Var–Cov approach, adaptive generalized Pareto distribution (GPD) and nonadaptive GPD models, leads to more stable quantile forecasts. The quantile forecasts of GARCH(1, 1) models are excessively volatile relative to the GPD quantile forecasts. This makes the GPD model be a robust quantile forecasting tool which is practical to implement and regulate for VaR measurements.

Search for new phenomena in final states with large jet multiplicities and missing transverse momentum at √s = 8 TeV proton-proton collisions using the ATLAS experiment

Abstract: A search is presented for new particles decaying to large numbers (7 or more) of jets, with missing transverse momentum and no isolated electrons or muons. This analysis uses 20.3 fb−1 of pp collision data at s√=8 TeV collected by the ATLAS experiment at the Large Hadron Collider. The sensitivity of the search is enhanced by considering the number of b-tagged jets and the scalar sum of masses of large-radius jets in an event. No evidence is found for physics beyond the Standard Model. The results are interpreted in the context of various simplified supersymmetry-inspired models where gluinos are pair produced, as well as an mSUGRA/CMSSM model.

Are Simple Gain Scores Obsolete

Abstract: It is widely believed that measures of gain, growth, or change, expressed as simple differences between pretest and posttest scores, are inherently unreliable It is also believed that gain scores lack predictive validity with respect to other criteria However, these conclu sions are based on misleading assumptions about the values of parameters in familiar equations in classical test theory The present paper examines modified equa tions for the validity and reliability of difference scores that describe applied testing situations more realisti cally and reveal that simple gain scores can be more useful in research than commonly believed