Visually Perceived Distance Judgments: Tablet-Based Augmented Reality Versus the Real World

Does visually perceived distance differ when objects are viewed in augmented reality (AR), as opposed to the real world? What are the differences? These questions are theoretically interesting, and the answers are important for the development of many tablet- and phone-based AR applications, including mobile AR navigation systems. This article presents a thorough literature review of distance judgment experimental protocols, and results from several areas of perceptual psychology. In addition to distance judgments of real and virtual objects, this section also discusses previous work in measuring the geometry of virtual picture space and considers how this work might be relevant to tablet AR. Then, the article presents the results of two experiments. In each experiment, observers bisected egocentric distances of 15 and 30 m in tablet-based AR and in the real world, in both indoor corridor and outdoor field environments. In AR, observers bisected the distances to virtual humans, while in the real world, they bisected the distances to real humans. This is the first reported research that directly compares distance judgments of real and virtual objects in a tablet AR system. Four key findings were: (1) In AR, observers expanded midpoint intervals at 15 m, but compressed midpoints at 30 m. (2) Observers were accurate in the real world. (3) The environmental setting—corridor or open field—had no effect. (4) The picture perception literature is important in understanding how distances are likely judged in tablet-based AR. Taken together, these findings suggest the depth distortions that AR application developers should expect with mobile and especially tablet-based AR.     

A population-based iterated greedy algorithm for the minimum weight vertex cover problem

Given an undirected, vertex-weighted graph, the goal of the minimum weight vertex cover problem is to find a subset of the vertices of the graph such that the subset is a vertex cover and the sum of the weights of its vertices is minimal. This problem is known to be NP-hard and no efficient algorithm is known to solve it to optimality. Therefore, most existing techniques are based on heuristics for providing approximate solutions in a reasonable computation time.Population-based search approaches have shown to be effective for solving a multitude of combinatorial optimization problems. Their advantage can be identified as their ability to find areas of the space containing high quality solutions. This paper proposes a simple and efficient population-based iterated greedy algorithm for tackling the minimum weight vertex cover problem. At each iteration, a population of solutions is established and refined using a fast randomized iterated greedy heuristic based on successive phases of destruction and reconstruction. An extensive experimental evaluation on a commonly used set of benchmark instances shows that our algorithm outperforms current state-of-the-art approaches.     

Efficient algorithms for singleton arc consistency

In this paper, we propose two original and efficient approaches for enforcing singleton arc consistency. In the first one, the data structures used to enforce arc consistency are shared between all subproblems where a domain is reduced to a singleton. This new algorithm is not optimal but it requires far less space and is often more efficient in practice than the optimal algorithm SAC-Opt. In the second approach, we perform several runs of a greedy search (where at each step, arc consistency is maintained), possibly detecting the singleton arc consistency of several values in one run. It is an original illustration of applying inference (i.e., establishing singleton arc consistency) by search. Using a greedy search allows benefiting from the incrementality of arc consistency, learning relevant information from conflicts and, potentially finding solution(s) during the inference process. We present extensive experiments that show the benefit of our two approaches.     

Five-year experience with setup and implementation of an integrated database system for clinical documentation and research

In radiation oncology, where treatment concepts are elaborated in interdisciplinary collaborations, handling distributed, large heterogeneous amounts of data efficiently is very important, yet challenging, for an optimal treatment of the patient as well as for research itself. This becomes a strong focus, as we step into the era of modern personalized medicine, relying on various quantitative data information, thus involving the active contribution of multiple medical specialties. Hence, combining patient data from all involved information systems is inevitable for analyses. Therefore, we introduced a documentation and data management system integrated in the clinical environment for electronic data capture. We discuss our concept and five-year experience of a precise electronic documentation system, with special focus on the challenges we encountered. We specify how such a system can be designed and implemented to plan, tailor and conduct (multicenter) clinical trials, ultimately reaching the best clinical performance, and enhancing interdisciplinary and clinical research.     

Quantitative evaluation of three calibration methods for 3-D freehand ultrasound

In this paper, three different calibration methods for three-dimensional (3-D) freehand ultrasound (US) are evaluated. Calibration is the process of estimating the rigid transformation from US image coordinates to the coordinate system of the tracking sensor mounted onto the probe. Calibration accuracy has an important impact on quantitative studies. Geometrical precision can also be crucial in many interventions and surgery. The proposed evaluation framework relies on a single point phantom and a 3-D US phantom which mimics the US characteristics of human liver. Four quality measures are used: 3-D point localization criterion, distance and volume measurements, and shape based criterion. Results show that during the acquisition procedure, volumetric measurements and shapes of the reconstructed object depend on probe motion used, particularly fan motions for which errors are larger. It is also shown that accurate calibration is essential to obtain reliable quantitative information.     

3-D deformable image registration: a topology preservation scheme based on hierarchical deformation models and interval analysis optimization.

This paper deals with topology preservation in three-dimensional (3-D) deformable image registration. This work is a nontrivial extension of, which addresses the case of two-dimensional (2-D) topology preserving mappings. In both cases, the deformation map is modeled as a hierarchical displacement field, decomposed on a multiresolution B-spline basis. Topology preservation is enforced by controlling the Jacobian of the transformation. Finding the optimal displacement parameters amounts to solving a constrained optimization problem: The residual energy between the target image and the deformed source image is minimized under constraints on the Jacobian. Unlike the 2-D case, in which simple linear constraints are derived, the 3-D B-spline-based deformable mapping yields a difficult (until now, unsolved) optimization problem. In this paper, we tackle the problem by resorting to interval analysis optimization techniques. Care is taken to keep the computational burden as low as possible. Results on multipatient 3-D MRI registration illustrate the ability of the method to preserve topology on the continuous image domain.     

Genetic studies on several bean traits of Coffea canephora coffee in Cameroon

The genetic parameters of several bean traits of coffee from the species Coffea canephora were estimated using two mating designs: a triangular diallel with 6 parents and a partial diallel with 18 parents. The traits studied were: normal bean weight, the percentage of peaberries, the length, width and thickness of the beans. These characteristics were studied along with yield. The yield data came from harvests obtained over 14 years divided into an initial cycle of 6 years, a second cycle of 5 years after cutting back and a third cycle of 3 years after topping. The general combining abilities (GCA) were the principal sources of significant variation for the traits studied. Transmission of these traits was therefore mostly additive. Yield over 14 years was the most heritable trait. The rank correlations between the GCA of the bean traits and those of yield were not significant. The genetic correlations estimated in the partial diallel did not reveal any link between bean traits and yield. Only one genetic correlation between the peaberry rate and yield was significant. The peaberry rate was linked to fertility, which thus appeared to be a genetic component of yield. Index‐based selection combining an increase in yield with improved bean traits could therefore be carried out without any particular difficulty. Copyright © 2005 Society of Chemical Industry     

Climate policies for road transport revisited (II): Closing the policy gap with cap-and-trade

Current policies in the road transport sector fail to deliver consistent and efficient incentives for greenhouse gas abatement (see companion article by Creutzig et al., in press). Market-based instruments such as cap-and-trade systems close this policy gap and complement traditional policies that are required where specific market failures arise. Even in presence of strong existing non-market policies, cap-and-trade delivers additional abatement and efficiency by incentivizing demand side abatement options. This paper analyzes generic design options and economic impacts of including the European road transport sector into the EU ETS. Suitable points of regulation are up- and midstream in the fuel chain to ensure effectiveness (cover all emissions and avoid double-counting), efficiency (incentivize all abatement options) and low transaction costs. Based on year 2020 marginal abatement cost curves from different models and current EU climate policy objectives we show that in contrast to conventional wisdom, road transport inclusion would not change the EU ETS allowance price. Hence, industrial carbon leakage induced by adding road transport to the EU ETS may be less important than previously estimated.     

Detecting zero-day attacks using context-aware anomaly detection at the application-layer

Anomaly detection allows for the identification of unknown and novel attacks in network traffic. However, current approaches for anomaly detection of network packet payloads are limited to the analysis of plain byte sequences. Experiments have shown that application-layer attacks become difficult to detect in the presence of attack obfuscation using payload customization. The ability to incorporate syntactic context into anomaly detection provides valuable information and increases detection accuracy. In this contribution, we address the issue of incorporating protocol context into payload-based anomaly detection. We present a new data representation, called \({c}_n\)-grams, that allows to integrate syntactic and sequential features of payloads in an unified feature space and provides the basis for context-aware detection of network intrusions. We conduct experiments on both text-based and binary application-layer protocols which demonstrate superior accuracy on the detection of various types of attacks over regular anomaly detection methods. Furthermore, we show how \({c}_n\)-grams can be used to interpret detected anomalies and thus, provide explainable decisions in practice.