University of Wisconsin–Milwaukee

About: University of Wisconsin–Milwaukee is a education organization based out in Milwaukee, Wisconsin, United States. It is known for research contribution in the topics: Population & Gravitational wave. The organization has 11839 authors who have published 28034 publications receiving 936438 citations. The organization is also known as: UWM & University of Wisconsin-Milwaukee.

A Cultural Models Approach to Service Recovery

Abstract: Service recovery research remains conflicted in its understanding of consumers' recovery expectations and of why similar goods or service failures may lead to different recovery expectations. The authors argue that this conflict results from the assumption that consumer recovery expectations are monolithic and largely homogeneous, driven mainly by behavioral, relational, or contextual stimuli. Instead, recovery scenarios involving high-involvement (i.e., self-relevant) goods and service failures may activate closely held, identity-related cultural models that, though ultimately applied to regain balance (a foundational schema), differ according to their sociocultural heritage and create a range of unique consumer recovery preferences. The authors empirically identify three embodied cultural models—relational, oppositional, and utilitarian—that consumers apply to goods or service failures. Furthermore, the authors discuss implications for service recovery research and services marketing practice a...

A preliminary study of one year of pedometer self-monitoring.

Abstract: Background: Long-term pedometer monitoring has not been attempted.Purpose: The purpose of this project was to collect 365 days of continuous self-monitored pedometer data to explore the natural variability of physical activity.Methods: Twenty-three participants (7 men, 16 women; M age = 38 ± 9.9 years; M body mass index = 27.7± 6.2 kg/m2) were recruited by word of mouth at two southern U.S. universities. Participants were asked to wear pedometers at their waist during waking hours and record steps per day and daily behaviors (e.g., sport/exercise, work or not) on a simple calendar. In total, participants wore pedometers and recorded 8,197 person-days of data (of a possible 8,395 person-days, or 98%) for a mean of 10,090± 3,389 steps/day. Missing values were estimated using the Missing Values Analysis EM function in SPSS, Version 11.0.1.Results: A mean of 10,082± 3,319 steps/day was computed. Using the corrected data, differences in steps/day were significant for season (summer > winter, F = 7.57, p = .001), day of the week (weekday > weekend, F = 3.97, p = .011), type of day (workday vs. nonworkday, F = 9.467, p = .008), and participation in sport/exercise (day with sport/exercise > day without sport/exercise, F = 102.5, p < .0001).Conclusions: These data suggest that surveillance should be conducted in the spring/fall or that an appropriate correction factor should be considered if the intent is to capture values resembling the year-round average.

On Recovery of Sparse Signals Via $\ell _{1}$ Minimization

Abstract: This paper considers constrained lscr1 minimization methods in a unified framework for the recovery of high-dimensional sparse signals in three settings: noiseless, bounded error, and Gaussian noise. Both lscr1 minimization with an lscrinfin constraint (Dantzig selector) and lscr1 minimization under an llscr2 constraint are considered. The results of this paper improve the existing results in the literature by weakening the conditions and tightening the error bounds. The improvement on the conditions shows that signals with larger support can be recovered accurately. In particular, our results illustrate the relationship between lscr1 minimization with an llscr2 constraint and lscr1 minimization with an lscrinfin constraint. This paper also establishes connections between restricted isometry property and the mutual incoherence property. Some results of Candes, Romberg, and Tao (2006), Candes and Tao (2007), and Donoho, Elad, and Temlyakov (2006) are extended.