The state of capacity development evaluation in biodiversity conservation and natural resource management

Capacity development is critical to long-term conservation success, yet we lack a robust and rigorous understanding of how well its effects are being evaluated. A comprehensive summary of who is monitoring and evaluating capacity development interventions, what is being evaluated and how, would help in the development of evidence-based guidance to inform design and implementation decisions for future capacity development interventions and evaluations of their effectiveness. We built an evidence map by reviewing peer-reviewed and grey literature published since 2000, to identify case studies evaluating capacity development interventions in biodiversity conservation and natural resource management. We used inductive and deductive approaches to develop a coding strategy for studies that met our criteria, extracting data on the type of capacity development intervention, evaluation methods, data and analysis types, categories of outputs and outcomes assessed, and whether the study had a clear causal model and/or used a systems approach. We found that almost all studies assessed multiple outcome types: most frequent was change in knowledge, followed by behaviour, then attitude. Few studies evaluated conservation outcomes. Less than half included an explicit causal model linking interventions to expected outcomes. Half of the studies considered external factors that could influence the efficacy of the capacity development intervention, and few used an explicit systems approach. We used framework synthesis to situate our evidence map within the broader literature on capacity development evaluation. Our evidence map (including a visual heat map) highlights areas of low and high representation in investment in research on the evaluation of capacity development

RGB-D Odometry and SLAM

The emergence of modern RGB-D sensors had a significant impact in many application fields, including robotics, augmented reality (AR) and 3D scanning. They are low-cost, low-power and low-size alternatives to traditional range sensors such as LiDAR. Moreover, unlike RGB cameras, RGB-D sensors provide the additional depth information that removes the need of frame-by-frame triangulation for 3D scene reconstruction. These merits have made them very popular in mobile robotics and AR, where it is of great interest to estimate ego-motion and 3D scene structure. Such spatial understanding can enable robots to navigate autonomously without collisions and allow users to insert virtual entities consistent with the image stream. In this chapter, we review common formulations of odometry and Simultaneous Localization and Mapping (known by its acronym SLAM) using RGB-D stream input. The two topics are closely related, as the former aims to track the incremental camera motion with respect to a local map of the scene, and the latter to jointly estimate the camera trajectory and the global map with consistency. In both cases, the standard approaches minimize a cost function using nonlinear optimization techniques. This chapter consists of three main parts: In the first part, we introduce the basic concept of odometry and SLAM and motivate the use of RGB-D sensors. We also give mathematical preliminaries relevant to most odometry and SLAM algorithms. In the second part, we detail the three main components of SLAM systems: camera pose tracking, scene mapping and loop closing. For each component, we describe different approaches proposed in the literature. In the final part, we provide a brief discussion on advanced research topics with the references to the state-of-the-art.Comment: This is the pre-submission version of the manuscript that was later edited and published as a chapter in RGB-D Image Analysis and Processin

Discourse and religion in educational practice

Despite the existence of long-held binaries between secular and sacred, private and public spaces, school and religious literacies in many contemporary societies, the significance of religion and its relationship to education and society more broadly has become increasingly topical. Yet, it is only recently that the investigation of the nexus of discourse and religion in educational practice has started to receive some scholarly attention. In this chapter, religion is understood as a cultural practice, historically situated and embedded in specific local and global contexts. This view of religion stresses the social alongside the subjective or experiential dimensions. It explores how through active participation and apprenticeship in culturally appropriate practices and behaviors often mediated intergenerationally and the mobilisation of linguistic and other semiotic resources but also affective, social and material resources, membership in religious communities is constructed and affirmed. The chapter reviews research strands that have explored different aspects of discourse and religion in educational practice as a growing interdisciplinary field. Research strands have examined the place and purpose of religion in general and evangelical Christianity in particular in English Language Teaching (ELT) programmes and the interplay of religion and teaching and learning in a wide range of religious and increasingly secular educational contexts. They provide useful insights for scholars of discourse studies to issues of identity, socialisation, pedagogy and language policy

Avoiding to face the challenges of visual place recognition

Through this paper, bottlenecks of conventional place recognition techniques are studied, and a replacement strategy is proposed for each item. Conventional place recognition algorithms are extensions of object recognition techniques applied to larger scale targets known as the place landmarks. The discussion presented in this paper aims to address the challenges of detection and recognition of the places, which make this topic distinctive from detection and recognition of the objects and landmarks. The challenges are listed under related categories. The table of challenges, reasons, and the recommendations to avoid these situations is presented as the guideline for selection of proper tools for place recognition purpose.Accepted versio