On dual power assignment optimization for biconnectivity

Topology control is an important technology of wireless ad hoc networks to achieve energy efficiency and fault tolerance. In this paper, we study the dual power assignment problem for 2-edge connectivity and 2-vertex connectivity in the symmetric graphical model which is a combinatorial optimization problem from topology control technology.The problem is arisen from the following origin. In a wireless ad hoc network where each node can switch its transmission power between high-level and low-level, how can we establish a fault-tolerantly connected network topology in the most energy-efficient way? Specifically, the objective is to minimize the number of nodes assigned with high power and yet achieve 2-edge connectivity or 2-vertex connectivity.We addressed these optimization problems (2-edge connectivity and 2-vertex connectivity version) under the general graph model in (Wang et al. in Theor. Comput. Sci., 2008). In this paper, we propose a novel approximation algorithm, called Candidate Set Filtering algorithm, to compute nearly-optimal solutions. Specifically, our algorithm can achieve 3.67-approximation ratio for both 2-edge connectivity and 2-vertex connectivity, which improves the existing 4-approximation algorithms for these two cases.     

A place to heal: a qualitative focus group study of respite care preferences among individuals experiencing homelessness*

Homeless patients have longer hospital stays than housed persons due, in part, to a lack of safe discharge locations. Respite care for homeless individuals decreases hospital length of stay and readmissions rates. This study aimed to develop client-centered recommendations for medical respite care. We conducted four focus group interviews (n?=?25 participants) between August 2010 and February 2013 of homeless adult residents in Minnesota. Four domains of respite care were identified from content analysis of interviews: physical, relational, facilitation, and amenities. Novel recommendations include (a) a facility equipped to address mental health and substance dependence needs, (b) a standardized training protocol for respite staff, (c) the creation of a patient advocate, and (d) the creation of a respite case manager to facilitate post-discharge instructions and connection to primary care and social services. These new and actionable recommendations could help inform policies and the development of future medical respite care facilities.     

Inference on high-dimensional implicit dynamic models using a guided intermediate resampling filter

Statistics and Computing - We propose a method for inference on moderately high-dimensional, nonlinear, non-Gaussian, partially observed Markov process models for which the transition density is...     

On Fisher’s dispersion test for integer-valued autoregressive Poisson models with applications

The integer-valued autoregressive (INAR) model has been widely used in diverse fields. Since the task of identifying the underlying distribution of time-series models is a crucial step for further inferences, we consider the goodness-of-fit test for the Poisson assumption on first-order INAR models. For a test, we employ Fisher’s dispersion test due to its simplicity and then derive its null limiting distribution. As an illustration, a simulation study and real data analysis are conducted for the counts of coal mining disasters, the monthly crime data set from New South Wales, and the annual numbers of worldwide earthquakes.     

On the cores of games arising from integer edge covering functions of graphs

In this paper, we study cooperative games arising from integer edge covering problems on graphs. We introduce two games, a rigid k-edge covering game and its relaxed game, as generalizations of a rigid edge covering game and its relaxed game studied by Liu and Fang (2007). Then we give a characterization of the cores of both games, find relationships between them, and give necessary and sufficient conditions for the balancedness of a rigid k-edge covering game and its relaxed game.     

New employee orientation: cases of Korean corporations

Despite its effectiveness in socialization and development, new employee orientation (NEO) as a stand-alone training intervention has rarely been a topic of interest in the academic world. The purpose of this study was to examine the NEO programmes for university graduates in Korean corporations. Through an extensive review of NEO-related materials in 10 large Korean corporations, the designs and contents of Korean NEOs were analysed. As a result, all investigated corporations were found to use most of the institutionalized socialization tactics: formal, collective, fixed, sequential, and serial. The contents of the NEOs mainly focused on the synergism and integration roles. The embedded national culture and organizational contexts in Korean corporations were explored to explain the practices of the NEOs. Implications for HRD practice and research were suggested.     

LOCAL POLYNOMIAL QUASI-LIKELIHOOD REGRESSION ON RANDOM FIELDS

In this paper, local quasi‐likelihood regression is considered for stationary random fields of dependent variables. In the case of independent data, local polynomial quasi‐likelihood regression is known to have several appealing features such as minimax efficiency, design adaptivity and good boundary behaviour. These properties are shown to carry over to the case of random fields. The asymptotic normality of the regression estimator is established and explicit formulae for its asymptotic bias and variance are derived for strongly mixing stationary random fields. The extension to multi‐dimensional covariates is also provided in full generality. Moreover, evaluation of the finite sample performance is made through a simulation study.     

原产国效应与原产地效应的实证研究--中韩比较

本研究在国际营销研究领域里比较广泛探讨的原产国效应(Country of Origin Effect)的基础上,分析了中国消费者在评价国内外品牌时所产生的原产地效应(Region of Origin Effect)问题.根据韩国/中国和上海/沈阳的原产国和原产地效应的实证分析,发现中国消费者评价韩国或中国产品时不受原产国效应的影响,但却受到原产地效应影响,这是本研究的重要发现,也对企业管理实践具有重要意义.     

Bayesian methods for contingency tables using Gibbs sampling

Cell counts in contingency tables can be smoothed using loglinear models. Recently, sampling-based methods such as Markov chain Monte Carlo (MCMC) have been introduced, making it possible to sample from posterior distributions. The novelty of the approach presented here is that all conditional distributions can be specified directly, so that straight-forward Gibbs sampling is possible. Thus, the model is constructed in a way that makes burn-in and checking convergence a relatively minor issue. The emphasis of this paper is on smoothing cell counts in contingency tables, and not so much on estimation of regression parameters. Therefore, the prior distribution consists of two stages. We rely on a normal nonconjugate prior at the first stage, and a vague prior for hyperparameters at the second stage. The smoothed counts tend to compromise between the observed data and a log-linear model. The methods are demonstrated with a sparse data table taken from a multi-center clinical trial. The research for the first author was supported by Brain Pool program of the Korean Federation of Science and Technology Societies. The research for the second author was partially supported by KOSEF through Statistical Research Center for Complex Systems at Seoul National University.