Want Amid Plenty: Developing and Testing a Cross-National Measure of Anomie

One of the biggest challenges facing researchers trying to empirically test structural or institutional anomie theories is the operationalization of the key concept of anomie. This challenge is heightened by the data constraints involved in cross-national research. As a result, researchers have been forced to rely on surrogate or proxy measures of anomie and indirect tests of the theories. The purpose of this study is to examine an innovative and more theoretically sound measure of anomie and to test its ability to make cross-national predictions of serious crime. Our results are supportive of the efficacy of this construct to explain cross-national variations in crime rates. Nations with the highest rates of structural anomie also have the highest predicted rates of homicide.

Is VHB-JOURQUAL2 a Good Measure of Scientific Quality? Assessing the Validity of the Major Business Journal Ranking in German-Speaking Countries

This study examines the question of whether the journal ranking VHB-JOURQUAL 2 can be considered as a good measure for the construct “scientific quality”. Various rankings in business research provide the database for the analysis. The correlations between theses rankings are used to assess the validity of VHB-JOURQUAL 2 along various validity criteria. The correlations with rankings that measure the same construct based on different methods show that VHB-JOURQUAL 2 has acceptable, but moderate convergent validity. The validity varies considerably across disciplines, showing that the heterogeneity of business administration is not sufficiently represented by this overall ranking. The variability is related to the variation in members per discipline represented by the German Association for Business Research. Furthermore, the measure shows a weak correlation with acceptance rates as an indicator of nomological validity in some disciplines.

Application of Time-Delay Estimation to Mixed Reality Multisensor Tracking

Spatial tracking is one of the most challenging and important parts of Mixed Reality environments. Many applications, especially in the domain of Augmented Reality, rely on the fusion of several tracking systems in order to optimize the overall performance. While the topic of spatial tracking sensor fusion has already seen considerable interest, most results only deal with the integration of carefully arranged setups as opposed to dynamic sensor fusion setups. A crucial prerequisite for correct sensor fusion is the temporal alignment of the tracking data from several sensors. Tracking sensors are typically encountered in Mixed Reality applications, are generally not synchronized. We present a general method to calibrate the temporal offset between different sensors by the Time Delay Estimation method which can be used to perform on-line temporal calibration. By applying Time Delay Estimation on the tracking data, we show that the temporal offset between generic Mixed Reality spatial tracking sensors can be calibrated. To show the correctness and the feasibility of this approach, we have examined different variations of our method and evaluated various combinations of tracking sensors. We furthermore integrated this time synchronization method into our UBITRACK Mixed Reality tracking framework to provide facilities for calibration and real-time data alignment.