Interaction-aware Kalman Neural Networks for Trajectory Prediction

Forecasting the motion of surrounding obstacles (vehicles, bicycles, pedestrians and etc.) benefits the on-road motion planning for intelligent and autonomous vehicles. Complex scenes always yield great challenges in modeling the patterns of surrounding traffic. For example, one main challenge comes from the intractable interaction effects in a complex traffic system. In this paper, we propose a multi-layer architecture Interaction-aware Kalman Neural Networks (IaKNN) which involves an interaction layer for resolving high-dimensional traffic environmental observations as interaction-aware accelerations, a motion layer for transforming the accelerations to interaction aware trajectories, and a filter layer for estimating future trajectories with a Kalman filter network. Attributed to the multiple traffic data sources, our end-to-end trainable approach technically fuses dynamic and interaction-aware trajectories boosting the prediction performance. Experiments on the NGSIM dataset demonstrate that IaKNN outperforms the state-of-the-art methods in terms of effectiveness for traffic trajectory prediction.Comment: 8 pages, 4 figures, Accepted for IEEE Intelligent Vehicles Symposium (IV) 202

Tensor Regression

Regression analysis is a key area of interest in the field of data analysis and machine learning which is devoted to exploring the dependencies between variables, often using vectors. The emergence of high dimensional data in technologies such as neuroimaging, computer vision, climatology and social networks, has brought challenges to traditional data representation methods. Tensors, as high dimensional extensions of vectors, are considered as natural representations of high dimensional data. In this book, the authors provide a systematic study and analysis of tensor-based regression models and their applications in recent years. It groups and illustrates the existing tensor-based regression methods and covers the basics, core ideas, and theoretical characteristics of most tensor-based regression methods. In addition, readers can learn how to use existing tensor-based regression methods to solve specific regression tasks with multiway data, what datasets can be selected, and what software packages are available to start related work as soon as possible. Tensor Regression is the first thorough overview of the fundamentals, motivations, popular algorithms, strategies for efficient implementation, related applications, available datasets, and software resources for tensor-based regression analysis. It is essential reading for all students, researchers and practitioners of working on high dimensional data.Comment: 187 pages, 32 figures, 10 table

A qualitative analysis of offenders' modus operandi in sexually exploitative interactions with children online

Transcripts of chat logs of naturally-occurring, sexually exploitative interactions between offenders and victims that took place via Internet communication platforms were analyzed. The aim of the study was to examine the modus operandi of offenders in such interactions, with particular focus on the specific strategies they use to engage victims, including discursive tactics. We also aimed to ascertain offenders’ underlying motivation and function of engagement in online interactions with children. Five cases, comprising 29 transcripts, were analyzed using qualitative thematic analysis with a discursive focus. In addition to this, police reports were reviewed for descriptive and case-specific information. Offenders were men aged between 27 and 52 years (M = 33.6, SD = 5.6), and the number of children they communicated with ranged from one to twelve (M = 4.6, SD = 4.5). Victims were aged between 11 and 15 (M = 13.00, SD = 1.2), and were both female and male. Three offenders committed online sexual offenses, and two offenders committed contact sexual offenses in addition to online sexual offenses. The analysis of transcripts revealed that interactions between offenders and victims were of a highly sexual nature, and that offenders employed a range of manipulative strategies to engage victims and achieve their compliance. It appeared that offenders engaged in such interactions for the purpose of sexual arousal and gratification, as well as fantasy fulfillment