Learning informative features for indoor traversability

This paper presents a method for automatic terrain classification, using a cheap monocular camera in conjunction with a robot’s stall sensor. A first step is to have the robot generate a training set of labelled images. Several techniques are then evaluated for preprocessing the images, reducing their dimensionality, and building a classifier. Finally, the classifier is implemented and used online by an indoor robot. Results are presented, demonstrating an increased level of autonomy.

The association between objectively measured neighborhood features and walking in middle-aged adults

Purpose: To explore the role of the neighborhood environment in supporting walking Design: Cross sectional study of 10,286 residents of 200 neighborhoods. Participants were selected using a stratified two-stage cluster design. Data were collected by mail survey (68.5% response rate). Setting: The Brisbane City Local Government Area, Australia, 2007. Subjects: Brisbane residents aged 40 to 65 years. Measures Environmental: street connectivity, residential density, hilliness, tree coverage, bikeways, and street lights within a one kilometer circular buffer from each resident’s home; and network distance to nearest river or coast, public transport, shop, and park. Walking: minutes in the previous week categorized as < 30 minutes, ≥ 30 < 90 minutes, ≥ 90 < 150 minutes, ≥ 150 < 300 minutes, and ≥ 300 minutes. Analysis: The association between each neighborhood characteristic and walking was examined using multilevel multinomial logistic regression and the model parameters were estimated using Markov chain Monte Carlo simulation. Results: After adjustment for individual factors, the likelihood of walking for more than 300 minutes (relative to <30 minutes) was highest in areas with the most connectivity (OR=1.93, 99% CI 1.32-2.80), the greatest residential density (OR=1.47, 99% CI 1.02-2.12), the least tree coverage (OR=1.69, 99% CI 1.13-2.51), the most bikeways (OR=1.60, 99% CI 1.16-2.21), and the most street lights (OR=1.50, 99% CI 1.07-2.11). The likelihood of walking for more than 300 minutes was also higher among those who lived closest to a river or the coast (OR=2.06, 99% CI 1.41-3.02). Conclusion: The likelihood of meeting (and exceeding) physical activity recommendations on the basis of walking was higher in neighborhoods with greater street connectivity and residential density, more street lights and bikeways, closer proximity to waterways, and less tree coverage. Interventions targeting these neighborhood characteristics may lead to improved environmental quality as well as lower rates of overweight and obesity and associated chromic disease.

Collaboration features in current BPM tools

In cross-organizational, distributed environments, Business Process Management requires collaborative technologies to facilitate the process of discovering, modeling, and improving business processes across geographical and organizational boundaries. This paper provides a comprehensive understanding of collaborative business process modeling that is based on a review of literature and a case study of three selected modelling tools. The application of the framework reveals that current process modeling tools consider different perspectives on collaboration, and that the included features are orthogonal. This paper informs practitioners about the state of the art in tool support for collaborative process modelling. It also informs vendors about opportunities to enhance the technology support. For research, our paper paper informs social aspects of BPM technology through its explicit focus on the collaboration of BPM stakeholders in the process of distributed modeling.

The'dream'of multi-agency crime prevention : pitfalls in policy and practice

During the 1980s, terms such as interagency or multi-agency cooperation, collaboration, coordination, and interaction have became permanent features of both crime prevention rhetoric and government crime policy. The concept of having the government, local authorities, and the community working in partnership has characterized both left and right politics for over a decade. The U.S. National Advisory Commission on Criminal Justice Standards and Goals in the U.S.. Circulars 8/84 and 44/90 released by the U.K. Home Office, and the British Morgan Report-coupled with the launch of government strategies in France, the Netherlands, England and Wales, Australia, and, more recently, in Belgium, New Zealand, and Canada-have all emphasized the importance of agencies working together to prevent or reduce crime. This paper draws upon recent Australian research and critically analyzes multi-agency crime prevention. It suggests that agency conflicts and power struggles may be exacerbated by neo-liberal economic theory, by the politics of crime prevention management, and by policies that aim to combine situational and social prevention endeavors. Furthermore, it concludes that indigenous peoples are excluded by crime prevention strategies that fail to define and interpret crime and its prevention in culturally appropriate ways.

Project management governance : a situational approach

The purpose of this paper is to show how project management governance is addressed through the use of a specific meta-method. Governance is defined here on two criteria: accountability and performance. Accountability is promoted through transparency and performance is promoted by responsive and responsible decision-making. According to a systemic perspective, transparency and decision-making involve having information, tacit or explicit knowledge, as well as understanding of the context, the different parameters and variables, their interaction and conditions of change. Although this method of methods was built according a heuristic process involving 25 years of various researches and consulting activities, it seems appropriate to draw its foundations. I clarify first my epistemological position and the notion of project and project management, as Art and Science. This lead me to define a "Be" / "Have" posture to this regards. Then, the main theoretical roots of MAP Method are exposed: Boisot' s Social Learning Cycle, Praxeology and Theory of Convention. Then we introduced the main characteristics of the method and the 17 methods and tools constituting MAP "tool box", thus with regard to the project management governance perspective. Finally, I discuss the integration of two managerial modes (operational and project modes) and the consequence in term of governance in a specific socio-techno-economic project/context ecosystem.

Hessian-based affine adaptation of salient local image features

Affine covariant local image features are a powerful tool for many applications, including matching and calibrating wide baseline images. Local feature extractors that use a saliency map to locate features require adaptation processes in order to extract affine covariant features. The most effective extractors make use of the second moment matrix (SMM) to iteratively estimate the affine shape of local image regions. This paper shows that the Hessian matrix can be used to estimate local affine shape in a similar fashion to the SMM. The Hessian matrix requires significantly less computation effort than the SMM, allowing more efficient affine adaptation. Experimental results indicate that using the Hessian matrix in conjunction with a feature extractor that selects features in regions with high second order gradients delivers equivalent quality correspondences in less than 17% of the processing time, compared to the same extractor using the SMM.

Discovering relevant features for effective query formulation

The quality of discovered features in relevance feedback (RF) is the key issue for effective search query. Most existing feedback methods do not carefully address the issue of selecting features for noise reduction. As a result, extracted noisy features can easily contribute to undesirable effectiveness. In this paper, we propose a novel feature extraction method for query formulation. This method first extract term association patterns in RF as knowledge for feature extraction. Negative RF is then used to improve the quality of the discovered knowledge. A novel information filtering (IF) model is developed to evaluate the proposed method. The experimental results conducted on Reuters Corpus Volume 1 and TREC topics confirm that the proposed model achieved encouraging performance compared to state-of-the-art IF models.

In the pursuit of effective affective computing : the relationship between features and registration

For facial expression recognition systems to be applicable in the real world, they need to be able to detect and track a previously unseen person's face and its facial movements accurately in realistic environments. A highly plausible solution involves performing a "dense" form of alignment, where 60-70 fiducial facial points are tracked with high accuracy. The problem is that, in practice, this type of dense alignment had so far been impossible to achieve in a generic sense, mainly due to poor reliability and robustness. Instead, many expression detection methods have opted for a "coarse" form of face alignment, followed by an application of a biologically inspired appearance descriptor such as the histogram of oriented gradients or Gabor magnitudes. Encouragingly, recent advances to a number of dense alignment algorithms have demonstrated both high reliability and accuracy for unseen subjects [e.g., constrained local models (CLMs)]. This begs the question: Aside from countering against illumination variation, what do these appearance descriptors do that standard pixel representations do not? In this paper, we show that, when close to perfect alignment is obtained, there is no real benefit in employing these different appearance-based representations (under consistent illumination conditions). In fact, when misalignment does occur, we show that these appearance descriptors do work well by encoding robustness to alignment error. For this work, we compared two popular methods for dense alignment-subject-dependent active appearance models versus subject-independent CLMs-on the task of action-unit detection. These comparisons were conducted through a battery of experiments across various publicly available data sets (i.e., CK+, Pain, M3, and GEMEP-FERA). We also report our performance in the recent 2011 Facial Expression Recognition and Analysis Challenge for the subject-independent task.

FGFR2 point mutations in 466 Endometrioid Endometrial Tumors : relationship with MSI, KRAS, PIK3CA, CTNNB1 mutations and Clinicopathological features

Mutations in multiple oncogenes including KRAS, CTNNB1, PIK3CA and FGFR2 have been identified in endometrial cancer. The aim of this study was to provide insight into the clinicopathological features associated with patterns of mutation in these genes, a necessary step in planning targeted therapies for endometrial cancer. 466 endometrioid endometrial tumors were tested for mutations in FGFR2, KRAS, CTNNB1, and PIK3CA. The relationships between mutation status, tumor microsatellite instability (MSI) and clinicopathological features including overall survival (OS) and disease-free survival (DFS) were evaluated using Kaplan-Meier survival analysis and Cox proportional hazard models. Mutations were identified in FGFR2 (48/466); KRAS (87/464); CTNNB1 (88/454) and PIK3CA (104/464). KRAS and FGFR2 mutations were significantly more common, and CTNNB1 mutations less common, in MSI positive tumors. KRAS and FGFR2 occurred in a near mutually exclusive pattern (p = 0.05) and, surprisingly, mutations in KRAS and CTNNB1 also occurred in a near mutually exclusive pattern (p = 0.0002). Multivariate analysis revealed that mutation in KRAS and FGFR2 showed a trend (p = 0.06) towards longer and shorter DFS, respectively. In the 386 patients with early stage disease (stage I and II), FGFR2 mutation was significantly associated with shorter DFS (HR = 3.24; 95% confidence interval, CI, 1.35-7.77; p = 0.008) and OS (HR = 2.00; 95% CI 1.09-3.65; p = 0.025) and KRAS was associated with longer DFS (HR = 0.23; 95% CI 0.05-0.97; p = 0.045). In conclusion, although KRAS and FGFR2 mutations share similar activation of the MAPK pathway, our data suggest very different roles in tumor biology. This has implications for the implementation of anti-FGFR or anti-MEK biologic therapies.

Identifying engaging features of schooling : assessing the psychometric soundness of student generated research

In this article we report on data analysed from a student project about attitudes to school and student perception of engagement and disengagement. The data were collected by students in an Australian study that employed the Young People as Researchers Model. Middle years students devised and administered a questionnaire to students in grade eight, nine and ten at a secondary school in Australia. A total of 239 students completed the questionnaire. The students completed the initial analysis which was followed by a more detailed analysis by the authors of this paper. The findings support the work of American, British and Australian researchers about the factors that influence engagement and disengagement from schooling. The reported outcomes from the student work and the secondary analysis indicate that students do have the capacity to undertake valid and meaningful research and can make informed contributions to school improvement and student engagement.

The pedagogical, linguistic and content features of popular English language learning websites in China : a framework for analysis and design

As increasing numbers of Chinese language learners choose to learn English online (CNNIC, 2012), there is a need to investigate popular websites and their language learning designs. This paper reports on the first stage of a study that analysed the pedagogical, linguistic and content features of 25 Chinese English Language Learning (ELL) websites ranked according to their value and importance to users. The website ranking was undertaken using a system known as PageRank. The aim of the study was to identify the features characterising popular sites as opposed to those of less popular sites for the purpose of producing a framework for ELL website design in the Chinese context. The study found that a pedagogical focus with developmental instructional materials accommodating diverse proficiency levels was a major contributor to website popularity. Chinese language use for translations and teaching directives and intermediate level English for learning materials were also significant features. Content topics included Anglophone/Western and non-Anglophone/Eastern contexts. Overall, popular websites were distinguished by their mediation of access to and scaffolded support for ELL.

Rotorcraft collision avoidance using spherical image-based visual servoing and single point features

This paper presents a reactive collision avoidance method for small unmanned rotorcraft using spherical image-based visual servoing. Only a single point feature is used to guide the aircraft in a safe spiral like trajectory around the target, whilst a spherical camera model ensures the target always remains visible. A decision strategy to stop the avoidance control is derived based on the properties of spiral like motion, and the effect of accurate range measurements on the control scheme is discussed. We show that using a poor range estimate does not significantly degrade the collision avoidance performance, thus relaxing the need for accurate range measurements. We present simulated and experimental results using a small quad rotor to validate the approach.

JFA based Speaker Recognition using Delta-Phase and MFCC features

This paper investigates the use of mel-frequency deltaphase (MFDP) features in comparison to, and in fusion with, traditional mel-frequency cepstral coefficient (MFCC) features within joint factor analysis (JFA) speaker verification. MFCC features, commonly used in speaker recognition systems, are derived purely from the magnitude spectrum, with the phase spectrum completely discarded. In this paper, we investigate if features derived from the phase spectrum can provide additional speaker discriminant information to the traditional MFCC approach in a JFA based speaker verification system. Results are presented which provide a comparison of MFCC-only, MFDPonly and score fusion of the two approaches within a JFA speaker verification approach. Based upon the results presented using the NIST 2008 Speaker Recognition Evaluation (SRE) dataset, we believe that, while MFDP features alone cannot compete with MFCC features, MFDP can provide complementary information that result in improved speaker verification performance when both approaches are combined in score fusion, particularly in the case of shorter utterances.