Equivalent Neutral Wind

The definition of equivalent neutral wind and the rationale for using it as the geophysical product of a spaceborne scatterometer are reviewed. The differences between equivalent neutral wind and actual wind, which are caused by atmospheric density stratification, are demonstrated with measurements at selected locations. A method of computing this parameter from ship and buoy measurements is described and some common fallacies in accounting for the effects of atmospheric stratification on wind shear are discussed. The computer code for the model to derive equivalent neutral wind is provided

Testing for homogeneity of gametic disequilibrium across strata

Copyright © 2007 Yin et al. Background: Assessing the non-random associations of alleles at different loci, or gametic disequilibrium, can provide clues about aspects of population histories and mating behavior and can be useful in locating disease genes. For gametic data which are available from several strata with different allele probabilities, it is necessary to verify that the strata are homogeneous in terms of gametic disequilibrium. Results: Using the likelihood score theory generalized to nuisance parameters we derive a score test for homogeneity of gametic disequilibrium across several independent populations. Simulation results demonstrate that the empirical type I error rates of our score homogeneity test perform satisfactorily in the sense that they are close to the pre-chosen 0.05 nominal level. The associated power and sample size formulae are derived. We illustrate our test with a data set from a study of the cystic fibrosis transmembrane conductance regulator gene. Conclusion: We propose a large-sample homogeneity test on gametic disequilibrium across several independent populations based on the likelihood score theory generalized to nuisance parameters. Our simulation results show that our test is more reliable than the traditional test based on the Fisher's test of homogeneity among correlation coefficients. © 2007 Yin et al; licensee BioMed Central Ltd.This research was supported by the National Natural Science Foundation of China (Grant Numbers 10431010 and 10701022), National 973 Key Project of China (2007CB311002), NCET-04-0310, EYTP, the Jilin Distinguished Young Scholars Program (Grant Number 20030113) and the Program Innovative Research Team (PCSIRT) in University (#IRT0519). The work of ML Tang was fully supported by a grant from the Research Grant Council of the Hong Kong Special Administration (Project no. HKBU261007)

Statistical model of OFDMA cellular networks uplink interference using lognormal distribution

In this letter, we propose an analytical approach to model uplink intercell interference (ICI) in hexagonal grid based orthogonal frequency division multiple access (OFMDA) cellular networks. The key idea is that the uplink ICI from individual cells is approximated with a lognormal distribution with statistical parameters being determined analytically. Accordingly, the aggregated uplink ICI is approximated with another lognormal distribution and its statistical parameters can be determined from those of individual cells using Fenton-Wilkson method. Analytic expressions of uplink ICI are derived with two traditional frequency reuse schemes, namely integer frequency reuse schemes with factor 1 (IFR-1) and factor 3 (IFR-3). Uplink fractional power control and lognormal shadowing are modeled. System performances in terms of signal to interference plus noise ratio (SINR) and spectrum efficiency are also derived. The proposed model has been validated by simulations

Framework of mobile-based learning (M-Learning): An exploratory study on the use of mobile devices for university students’ academic learning

This paper reports the results of 15 in-depth interviews with university students in the Greater Boston area regarding their mobile learning experiences, including the kinds of learning activities performed, and the advantages and challenges of m-learning. Mobile devices were used mainly for initial exploratory learning or a way for quick access and interacting with classmates. Participants avoided using mobile devices for complicated tasks or deep learning. The limited usability of mobile devices in supporting advanced learning is alarming. A conceptual framework of m-learning containing dimensions of mobility and ubiquity, convenience, interaction and collaboration, and usability was presented

QuikSCAT Satellite Comparisons with Nearshore Buoy Wind Data off the U.S. West Coast

To determine the accuracy of nearshore winds from the QuikSCAT satellite, winds from three satellite datasets (scientifically processed swath, gridded near-real-time, and gridded science datasets) were compared to those from 12 nearshore and 3 offshore U.S. West Coast buoys. Satellite observations from August 1999 to December 2000 that were within 25 km and 30 min of each buoy were used. Comparisons showed that satellite–buoy wind differences near shore were larger than those offshore. Editing the satellite data by discarding observations recorded in rain and those recorded in light winds improved the accuracy of all three datasets. After removing rain-flagged data and wind speeds less than 3 m s21, root-mean-squared differences (satellite minus buoy) for swath data, the best of the three datasets, were 1.4 m s21 and 378 based on 5741 nearshore comparisons. By removing winds less than 6 m s21, these differences were reduced to 1.3 m s21 and 268. At the three offshore buoys, the root-mean-squared differences for the swath data, with both rain and winds less than 6 m s21 removed, were 1.0 m s21 and 158 based on 1920 comparisons. Although the satellite’s scientifically processed swath data near shore do not match buoy observations as closely as those offshore, they are sufficiently accurate for many coastal studies

Analytical evaluation of higher order sectorization, frequency reuse, and user classification methods in OFDMA networks

Higher order sectorization (HOS), which splits macrocells into a larger number of smaller sectors, are receiving significant interest as a cost-effective means of improving network capacity. Potentially, the capacity gain with HOS is proportionally linear to the number of sectors per cell due to spatial reuse, but factors such as non-ideal antenna radiation patterns together with inter-cell interference can significantly reduce this capacity gain. We develop a statistical model to theoretically characterize the performance of HOS deployments in wireless networks using orthogonal frequency division multiple access. Moreover, a fractional frequency reuse scheme is considered, which aids to mitigate inter-cell interference. The model provides a fast and effective tool for studying network performance in terms of user signal quality, site throughput, and outage probability, and it can be used to speed up network planning and optimization. In addition, we consider the impact of user classification methods in the analysis, and propose a new spectrum efficiency-based user classification method that improves resource utilization and allocation fairness. Performance results indicate that the proposed model is accurate, and shows a diminishing performance gain of HOS deployments with the number of sectors. The proposed user classification method improves network performances with respect to the state-of-the-art approaches

Capacity Constrained Influence Maximization in Social Networks

Influence maximization (IM) aims to identify a small number of influential individuals to maximize the information spread and finds applications in various fields. It was first introduced in the context of viral marketing, where a company pays a few influencers to promote the product. However, apart from the cost factor, the capacity of individuals to consume content poses challenges for implementing IM in real-world scenarios. For example, players on online gaming platforms can only interact with a limited number of friends. In addition, we observe that in these scenarios, (i) the initial adopters of promotion are likely to be the friends of influencers rather than the influencers themselves, and (ii) existing IM solutions produce sub-par results with high computational demands. Motivated by these observations, we propose a new IM variant called capacity constrained influence maximization (CIM), which aims to select a limited number of influential friends for each initial adopter such that the promotion can reach more users. To solve CIM effectively, we design two greedy algorithms, MG-Greedy and RR-Greedy, ensuring the $1/2$-approximation ratio. To improve the efficiency, we devise the scalable implementation named RR-OPIM+ with $(1/2-\epsilon)$-approximation and near-linear running time. We extensively evaluate the performance of 9 approaches on 6 real-world networks, and our solutions outperform all competitors in terms of result quality and running time. Additionally, we deploy RR-OPIM+ to online game scenarios, which improves the baseline considerably.Comment: The technical report of the paper entitled 'Capacity Constrained Influence Maximization in Social Networks' in SIGKDD'2