Marieke M. J. W. van Rooij

Bio: Marieke M. J. W. van Rooij is an academic researcher from Radboud University Nijmegen. The author has contributed to research in topics: Anxiety & Biofeedback. The author has an hindex of 11, co-authored 19 publications receiving 747 citations. Previous affiliations of Marieke M. J. W. van Rooij include University of Cincinnati & University of Amsterdam.

A fractal approach to dynamic inference and distribution analysis.

Abstract: Event-distributions inform scientists about the variability and dispersion of repeated measurements. This dispersion can be understood from a complex systems perspective, and quantified in terms of fractal geometry. The key premise is that a distribution’s shape reveals information about the governing dynamics of the system that gave rise to the distribution. Two categories of characteristic dynamics are distinguished: additive systems governed by component-dominant dynamics and multiplicative or interdependent systems governed by interaction-dominant dynamics. A logic by which systems governed by interaction-dominant dynamics are expected to yield mixtures of lognormal and inverse power-law samples is discussed. These mixtures are described by a so-called cocktail model of response times derived from human cognitive performances. The overarching goals of this article are twofold: First, to offer readers an introduction to this theoretical perspective and second, to offer an overview of the related statistical methods.

SPENCER: A Socially Aware Service Robot for Passenger Guidance and Help in Busy Airports

Abstract: We present an ample description of a socially compliant mobile robotic platform, which is developed in the EU-funded project SPENCER. The purpose of this robot is to assist, inform and guide passengers in large and busy airports. One particular aim is to bring travellers of connecting flights conveniently and efficiently from their arrival gate to the passport control. The uniqueness of the project stems from the strong demand of service robots for this application with a large potential impact for the aviation industry on one side, and on the other side from the scientific advancements in social robotics, brought forward and achieved in SPENCER. The main contributions of SPENCER are novel methods to perceive, learn, and model human social behavior and to use this knowledge to plan appropriate actions in real-time for mobile platforms. In this paper, we describe how the project advances the fields of detection and tracking of individuals and groups, recognition of human social relations and activities, normative human behavior learning, socially-aware task and motion planning, learning socially annotated maps, and conducting empirical experiments to assess socio-psychological effects of normative robot behaviors.

DEEP: A Biofeedback Virtual Reality Game for Children At-risk for Anxiety

Abstract: Anxiety disorders are among the most frequently diagnosed mental health problems in children, leading to potentially devastating outcomes on a personal level and high costs for society. Although evidence-based interventions are readily available, their outcomes are often disappointing and variable. In particular, existing interventions are not effective long-term nor tailored to differences in individual responsiveness. We therefore need a new approach to the prevention and treatment of anxiety in children and a commensurate scientific methodology to uncover individual profiles of change. We argue that applied games have a great deal of potential for both. The current paper presents results from a recent pilot study using a biofeedback virtual reality game (DEEP). DEEP integrates established therapeutic principles with an embodied and intuitive learning process towards improved anxiety regulation skills.

Critical Fluctuations as an Early-Warning Signal for Sudden Gains and Losses in Patients Receiving Psychotherapy for Mood Disorders:

Abstract: Whereas sudden gains and losses (large shifts in symptom severity) in patients receiving psychotherapy appear abrupt and hence may seem unexpected, hypotheses from complex-systems theory suggest th...

Connected text reading and differences in text reading fluency in adult readers.

Abstract: The process of connected text reading has received very little attention in contemporary cognitive psychology. This lack of attention is in parts due to a research tradition that emphasizes the role of basic lexical constituents, which can be studied in isolated words or sentences. However, this lack of attention is in parts also due to the lack of statistical analysis techniques, which accommodate interdependent time series. In this study, we investigate text reading performance with traditional and nonlinear analysis techniques and show how outcomes from multiple analyses can used to create a more detailed picture of the process of text reading. Specifically, we investigate reading performance of groups of literate adult readers that differ in reading fluency during a self-paced text reading task. Our results indicate that classical metrics of reading (such as word frequency) do not capture text reading very well, and that classical measures of reading fluency (such as average reading time) distinguish relatively poorly between participant groups. Nonlinear analyses of distribution tails and reading time fluctuations provide more fine-grained information about the reading process and reading fluency.

In Defense of the Triplet Loss for Person Re-Identification

Abstract: In the past few years, the field of computer vision has gone through a revolution fueled mainly by the advent of large datasets and the adoption of deep convolutional neural networks for end-to-end learning. The person re-identification subfield is no exception to this. Unfortunately, a prevailing belief in the community seems to be that the triplet loss is inferior to using surrogate losses (classification, verification) followed by a separate metric learning step. We show that, for models trained from scratch as well as pretrained ones, using a variant of the triplet loss to perform end-to-end deep metric learning outperforms most other published methods by a large margin.

The Long Tail: Why the Future of Business is Selling Less of More

Abstract: The Long Tail: How Technology is turning mass markets into millions of niches. (p. 15). This passage from The Long Tail, pretty much sums it all up. The Long Tail by Chris Anderson is a good and worthwhile read for information scientists, computer scientists, ecommerce researchers, and others interested in all areas of Web research. The central premise of the book is that the combination of (1) the Pareto or Zipf distribution (i.e., power law probability distribution) that is characteristic of Web traffic and (2) the direct access to consumers via Web technology has opened up new business opportunities in the ''long tail''. Producers and advertisers no longer have to target ''the big hits'' at the head of the distribution. Instead, they can target the small, niche communities or even individuals in the tail of the distribution. The long tail is has been studied by Web researchers and has been noted in term usage on search engines, access times to servers, and popularity of Web sites. Andersen points out that the long tail also applies to products sold on the Web. He recounts that a sizeable percentage of Amazon sales come from books that only sell a few copies, a large number of songs from Rhapsody get downloaded only once in a month, and a significant number of movies from Netflix only get ordered occasionally. However, since the storage is in digital form for the songs and music (and Amazon out sources the storage of books) there is little additional inventory cost of these items. This phenomenon across all Web companies has led to a broadening of participation by both producers and consumers that would not have happened without the Web. The idea of the long tail is well known, of course. What Anderson has done is present it in an interesting manner and in a Web ecommerce setting. He applies it to Web businesses and then relates the multitude of other factors ongoing that permit the actual implementation of the long tail effect. Anderson also expands on prior work on the long tail by introducing an element of time, given the distribution a three dimensional effect. All in all, it is a nifty idea. The book is comprised of 14 chapters, plus an Introduction. Chapter 1 presents an overview of what the long tail is. Chapter 2 discusses the ''head'', which is the top of the tail where the …

Understanding and Misunderstanding Randomized Controlled Trials

Abstract: RCTs are valuable tools whose use is spreading in economics and in other social sciences. They are seen as desirable aids in scientific discovery and for generating evidence for policy. Yet some of the enthusiasm for RCTs appears to be based on misunderstandings: that randomization provides a fair test by equalizing everything but the treatment and so allows a precise estimate of the treatment alone; that randomization is required to solve selection problems; that lack of blinding does little to compromise inference; and that statistical inference in RCTs is straightforward, because it requires only the comparison of two means. None of these statements is true. RCTs do indeed require minimal assumptions and can operate with little prior knowledge, an advantage when persuading distrustful audiences, but a crucial disadvantage for cumulative scientific progress, where randomization adds noise and undermines precision. The lack of connection between RCTs and other scientific knowledge makes it hard to use them outside of the exact context in which they are conducted. Yet, once they are seen as part of a cumulative program, they can play a role in building general knowledge and useful predictions, provided they are combined with other methods, including conceptual and theoretical development, to discover not "what works," but why things work. Unless we are prepared to make assumptions, and to stand on what we know, making statements that will be incredible to some, all the credibility of RCTs is for naught.