A Graph Theoretic Approach for Object Shape Representation in Compositional Hierarchies Using a Hybrid Generative-Descriptive Model

A graph theoretic approach is proposed for object shape representation in a hierarchical compositional architecture called Compositional Hierarchy of Parts (CHOP). In the proposed approach, vocabulary learning is performed using a hybrid generative-descriptive model. First, statistical relationships between parts are learned using a Minimum Conditional Entropy Clustering algorithm. Then, selection of descriptive parts is defined as a frequent subgraph discovery problem, and solved using a Minimum Description Length (MDL) principle. Finally, part compositions are constructed by compressing the internal data representation with discovered substructures. Shape representation and computational complexity properties of the proposed approach and algorithms are examined using six benchmark two-dimensional shape image datasets. Experiments show that CHOP can employ part shareability and indexing mechanisms for fast inference of part compositions using learned shape vocabularies. Additionally, CHOP provides better shape retrieval performance than the state-of-the-art shape retrieval methods.Comment: Paper : 17 pages. 13th European Conference on Computer Vision (ECCV 2014), Zurich, Switzerland, September 6-12, 2014, Proceedings, Part III, pp 566-581. Supplementary material can be downloaded from http://link.springer.com/content/esm/chp:10.1007/978-3-319-10578-9_37/file/MediaObjects/978-3-319-10578-9_37_MOESM1_ESM.pd

Nature-based solutions can help reduce the impact of natural hazards: A global analysis of NBS case studies

The knowledge derived from successful case studies can act as a driver for the implementation and upscaling of nature-based solutions (NBS). This work reviewed 547 case studies to gain an overview of NBS practices and their role in reducing the adverse impact of natural hazards and climate change. The majority (60 %) of case studies are situated in Europe compared with the rest of the world where they are poorly represented. Of 547 case studies, 33 % were green solutions followed by hybrid (31 %), mixed (27 %), and blue (10 %) approaches. Approximately half (48 %) of these NBS interventions were implemented in urban (24 %), and river and lake (24 %) ecosystems. Regarding the scale of intervention, 92 % of the case studies were operationalised at local (50 %) and watershed (46 %) scales while very few (4 %) were implemented at the landscape scale. The results also showed that 63 % of NBS have been used to deal with natural hazards, climate change, and loss of biodiversity, while the remaining 37 % address socio-economic challenges (e.g., economic development, social justice, inequality, and cohesion). Around 88 % of NBS implementations were supported by policies at the national level and the rest 12 % at local and regional levels. Most of the analysed cases contributed to Sustainable Development Goals 15, 13, and 6, and biodiversity strategic goals B and D. Case studies also highlighted the co-benefits of NBS: 64 % of them were environmental co-benefits (e.g., improving biodiversity, air and water qualities, and carbon storage) while 36 % were social (27 %) and economic (9 %) co-benefits. This synthesis of case studies helps to bridge the knowledge gap between scientists, policymakers, and practitioners, which can allow adopting and upscaling of NBS for disaster risk reduction and climate change adaptation and enhance their preference in decision-making processes

'Thinking like a fish': adaptive strategies for coping with vulnerability and variability emerging from a relational engagement with kob

Based on ethnographic fieldwork amongst a group of commercial handline fishers in the town of Stilbaai in South Africa's southern Cape region, this paper presents a range of flexible, adaptive and evolving strategies through which fishers negotiate constantly shifting variability in weather patterns, fish stocks, fisheries policies, and economic conditions. These variabilities constitute a diverse set of vulnerabilities to which fishers must respond in order to sustain their livelihoods. In this context, the act of 'thinking like a fish' on the part of the fishers provides them with an effective means of adapting to variability and uncertainty. Findings of ethnographic research in 2010-11 suggest that a number of the fishers who participated in the research actively work towards achieving a balance between profit and sustainability. 'Thinking like a fish' is an embodied, interactive way of knowing that emerges from interactions between fishers and fish, offering an ethical and ecological outlook which is a valuable resource for fisheries and conservation management in the region. We suggest that the deeply embodied interactional component of 'thinking like a fish' results from a desire to understand the life world of fish and to think from their perspective in order to more effectively target them while sustaining the species and ecosystem

Shallow waters: social science research in South Africa's marine environment

This paper provides an overview of social science research in the marine environment of South Africa for the period 1994–2012. A bibliography based on a review of relevant literature and social science projects funded under the SEAChange programme of the South African Network for Coastal and Oceanic Research (SANCOR) was used to identify nine main themes that capture the knowledge generated in the marine social science field. Within these themes, a wide diversity of topics has been explored, covering a wide geographic area. The review suggests that there has been a steady increase in social science research activities and outputs over the past 18 years, with a marked increase in postgraduate dissertations in this field. The SEAChange programme has contributed to enhancing understanding of certain issues and social interactions in the marine environment but this work is limited. Furthermore, there has been limited dissemination of these research results amongst the broader marine science community and incorporation of this information into policy and management decisions has also been limited. However, marine scientists are increasingly recognising the importance of taking a more holistic and integrated approach to management, and are encouraging further social science research, as well as interdisciplinary research across the natural and social sciences. Possible reasons for the lack of communication and coordination amongst natural and social scientists, as well as the limited uptake of research results in policy and management decisions, are discussed and recommendations are proposed.Web of Scienc

Localized practices and globalized futures: challenges for Alaska coastal community youth

An article from Maritime Studies (2015) 14:

Challenges for Implementing an Ecosystem Approach to Fisheries Management

The ecosystem approach is being promoted as the foundation of solutions to the unsustainability of fisheries. However, because the ecosystem approach is broadly inclusive, the science for its implementation is often considered to be overly complex and difficult. When the science needed for an ecosystem approach to fisheries is perceived this way, science products cannot keep pace with fisheries critics, thus encouraging partisan political interference in fisheries management and proliferation of “faith-based solutions. In this paper we argue that one way to effectively counter politicization of fisheries decision-making is to ensure that new ecosystem-based approaches in fisheries are viewed only as an emergent property of innovation in science and policy. We organize our essay using three major themes to focus the discussion: empirical, jurisdictional, and societal challenges. We undertake at least partial answers to the following questions: (1) has conventional fisheries management really failed?; (2) can short-comings in conventional fisheries management be augmented with new tools, such as allocation of rights?; (3) is the Ecosystem Approach to Fisheries (EAF) equivalent to Ecosystem-Based Management?; and (4) is restoration of degraded ecosystems a necessary component of an EAF

Toward Self-Referential Autonomous Learning of Object and Situation Models

Most current approaches to scene understanding lack the capability to adapt object and situation models to behavioral needs not anticipated by the human system designer. Here, we give a detailed description of a system architecture for self-referential autonomous learning which enables the refinement of object and situation models during operation in order to optimize behavior. This includes structural learning of hierarchical models for situations and behaviors that is triggered by a mismatch between expected and actual action outcome. Besides proposing architectural concepts, we also describe a first implementation of our system within a simulated traffic scenario to demonstrate the feasibility of our approach