Augmenting RatSLAM using FAB-MAP-based visual data association

This paper investigates the use of the FAB-MAP appearance-only SLAM algorithm as a method for performing visual data association for RatSLAM, a semi-metric full SLAM system. While both systems have shown the ability to map large (60-70km) outdoor locations of approximately the same scale, for either larger areas or across longer time periods both algorithms encounter difficulties with false positive matches. By combining these algorithms using a mapping between appearance and pose space, both false positives and false negatives generated by FAB-MAP are significantly reduced during outdoor mapping using a forward-facing camera. The hybrid FAB-MAP-RatSLAM system developed demonstrates the potential for successful SLAM over large periods of time.

Spatial mapping and map exploitation : a bio-inspired engineering perspective

Probabilistic robot mapping techniques can produce high resolution, accurate maps of large indoor and outdoor environments. However, much less progress has been made towards robots using these maps to perform useful functions such as efficient navigation. This paper describes a pragmatic approach to mapping system development that considers not only the map but also the navigation functionality that the map must provide. We pursue this approach within a bio-inspired mapping context, and use esults from robot experiments in indoor and outdoor environments to demonstrate its validity. The research attempts to stimulate new research directions in the field of robot mapping with a proposal for a new approach that has the potential to lead to more complete mapping and navigation systems.

Modeling crash outcome probabilities at rural intersections: Application of hierarchical binomial logistic models

It is important to examine the nature of the relationships between roadway, environmental, and traffic factors and motor vehicle crashes, with the aim to improve the collective understanding of causal mechanisms involved in crashes and to better predict their occurrence. Statistical models of motor vehicle crashes are one path of inquiry often used to gain these initial insights. Recent efforts have focused on the estimation of negative binomial and Poisson regression models (and related deviants) due to their relatively good fit to crash data. Of course analysts constantly seek methods that offer greater consistency with the data generating mechanism (motor vehicle crashes in this case), provide better statistical fit, and provide insight into data structure that was previously unavailable. One such opportunity exists with some types of crash data, in particular crash-level data that are collected across roadway segments, intersections, etc. It is argued in this paper that some crash data possess hierarchical structure that has not routinely been exploited. This paper describes the application of binomial multilevel models of crash types using 548 motor vehicle crashes collected from 91 two-lane rural intersections in the state of Georgia. Crash prediction models are estimated for angle, rear-end, and sideswipe (both same direction and opposite direction) crashes. The contributions of the paper are the realization of hierarchical data structure and the application of a theoretically appealing and suitable analysis approach for multilevel data, yielding insights into intersection-related crashes by crash type.

Does the p38 MAP kinase inhibitor pamapimod have potential for the treatment of rheumatoid arthritis?

Background: Methotrexate alone or in combination with other agents is the standard treatment for moderate-to-severe rheumatoid arthritis. As the biological agents are expensive, they are not usually used until methotrexate has failed to give a good response. Thus, there is scope for the development of cheaper drugs that can be used instead of methotrexate or in addition to methotrexate. Objectives/methods: Pamapimod is a p38α inhibitor being developed for use in the treatment of rheumatoid arthritis. The objective was to evaluate the recent clinical trials of pamapimod in subjects with rheumatoid arthritis. Results: There is no clear cut evidence that pamapimod alone or in the presence of methotrexate is efficacious in subjects with rheumatoid arthritis, but it does cause adverse effects. Conclusion: It is unlikely that pamapimod will be useful in the treatment of rheumatoid arthritis.

Primary students' performance on map tasks : the role of context

This study investigated the longitudinal performance of 583 students on six map items that were represented in various graphic forms. Specifically, this study compared the performance of 7-9-year-olds (across Grades 2 and 3) from metropolitan and non-metropolitan locations. The results of the study revealed significant performance differences in favour of metropolitan students on two of six map tasks. Implications include the need for teachers in non-metropolitan locations to ensure that their students do not overly fixate on landmarks represented on maps but rather consider the arrangement of all elements encompassed within the graphic.

Topological map induction using neighbourhood information of places

In topological mapping, perceptual aliasing can cause different places to appear indistinguishable to the robot. In case of severely corrupted or non-available odometry information, topological mapping is difficult as the robot is challenged with the loop-closing problem; that is to determine whether it has visited a particular place before. In this article we propose to use neighbourhood information to disambiguate otherwise indistinguishable places. Using neighbourhood information for place disambiguation is an approach that neither depends on a specific choice of sensors nor requires geometric information such as odometry. Local neighbourhood information is extracted from a sequence of observations of visited places. In experiments using either sonar or visual observations from an indoor environment the benefits of using neighbourhood clues for the disambiguation of otherwise identical vertices are demonstrated. Over 90% of the maps we obtain are isomorphic with the ground truth. The choice of the robot’s sensors does not impact the results of the experiments much.

A semi-local method for iterative depth-map refinement

We present an iterative hierarchical algorithm for multi-view stereo. The algorithm attempts to utilise as much contextual information as is available to compute highly accurate and robust depth maps. There are three novel aspects to the approach: 1) firstly we incrementally improve the depth fidelity as the algorithm progresses through the image pyramid; 2) secondly we show how to incorporate visual hull information (when available) to constrain depth searches; and 3) we show how to simultaneously enforce the consistency of the depth-map by continual comparison with neighbouring depth-maps. We show that this approach produces highly accurate depth-maps and, since it is essentially a local method, is both extremely fast and simple to implement.

Learning and acting in project situations through a meta-method (MAP) a case study : contextual and situational approach for project management governance in management education

The paper introduces the underlying principles and the general features of a meta-method (MAP method) developed as part of and used in various research, education and professional development programmes at ESC Lille. This method aims at providing effective and efficient structure and process for acting and learning in various complex, uncertain and ambiguous managerial situations (projects, programmes, portfolios). The paper is developed around three main parts. First, I suggest revisiting the dominant vision of the project management knowledge field, based on the assumptions they are not addressing adequately current business and management contexts and situations, and that competencies in management of entrepreneurial activities are the sources of creation of value for organisations. Then, grounded on the former developments, I introduce the underlying concepts supporting MAP method seen as a ‘convention generator’ and how this meta method inextricably links learning and practice in addressing managerial situations. Finally, I briefly describe an example of application, illustrating with a case study how the method integrates Project Management Governance, and give few examples of use in Management Education and Professional Development.

Learning and acting in project situations through a meta-method (MAP) : a case study : contextual and situational approach for project management governance in management education

The paper introduces the underlying principles and the general features of a meta-method (MAP method – Management & Analysis of Projects) developed as part of and used in various research, education and professional development programmes at ESC Lille. This method aims at providing effective and efficient structure and process for acting and learning in various complex, uncertain and ambiguous managerial situations (projects, programmes, portfolios). The paper is organized in three parts. In a first part, I propose to revisit the dominant vision of the project management knowledge field, based on the assumptions they are not addressing adequately current business and management contexts and situations, and that competencies in management of entrepreneurial activities are the sources of creation of value for organisations. Then, grounded on the new suggested perspective, the second part presents the underlying concepts supporting MAP method seen as a ‘convention generator' and how this meta-method inextricably links learning and practice in addressing managerial situations. The third part describes example of application, illustrating with a brief case study how the method integrates Project Management Governance, and gives few examples of use in Management Education and Professional Development.

Adaptive bilateral filtering using saliency map for deblocking low bit rate videos

This paper proposes a novel approach to video deblocking which performs perceptually adaptive bilateral filtering by considering color, intensity, and motion features in a holistic manner. The method is based on bilateral filter which is an effective smoothing filter that preserves edges. The bilateral filter parameters are adaptive and avoid over-blurring of texture regions and at the same time eliminate blocking artefacts in the smooth region and areas of slow motion content. This is achieved by using a saliency map to control the strength of the filter for each individual point in the image based on its perceptual importance. The experimental results demonstrate that the proposed algorithm is effective in deblocking highly compressed video sequences and to avoid over-blurring of edges and textures in salient regions of image.