Do flood risk perceptions provide useful insights for flood risk management? Findings from central Vietnam

Following the renewed attention for non-structural flood risk reduction measures implemented at the household level, there has been an increased interest in individual flood risk perceptions. The reason for this is the commonly-made assumption that flood risk perceptions drive the motivation of individuals to undertake flood risk mitigation measures, as well as the public's demand for flood protection, and therefore provide useful insights for flood risk management. This study empirically examines these assumptions by presenting data from a survey conducted among 300 households in central Vietnam. The main implications for flood risk communication and the stimulation of precautionary behaviour are that the current predominant focus on flood risk perceptions in the academic literature, and risk communication policy is not supported. Hence, the study provides an important contribution to the existing literature that mainly studies flood risk perceptions in developed countries. © 2012 Blackwell Publishing Ltd and The Chartered Institution of Water and Environmental Management (CIWEM)

SSDL: Self-Supervised Domain Learning for Improved Face Recognition

Face recognition in unconstrained environments is challenging due to variations in illumination, quality of sensing, motion blur and etc. An individual’s face appearance can vary drastically under different conditions creating a gap between train (source) and varying test (target) data. The domain gap could cause decreased performance levels in direct knowledge transfer from source to target. Despite fine-tuning with domain specific data could be an effective solution, collecting and annotating data for all domains is extremely expensive. To this end, we propose a self-supervised domain learning (SSDL) scheme that trains on triplets mined from unlabelled data. A key factor in effective discriminative learning, is selecting informative triplets. Building on most confident predictions, we follow an “easy-to-hard” scheme of alternate triplet mining and self-learning. Comprehensive experiments on four different benchmarks show that SSDL generalizes well on different domains

ClusterFace: Joint Clustering and Classification for Set-Based Face Recognition

Deep learning technology has enabled successful modeling of complex facial features when high quality images are available. Nonetheless, accurate modeling and recognition of human faces in real world scenarios `on the wild' or under adverse conditions remains an open problem. When unconstrained faces are mapped into deep features, variations such as illumination, pose, occlusion, etc., can create inconsistencies in the resultant feature space. Hence, deriving conclusions based on direct associations could lead to degraded performance. This rises the requirement for a basic feature space analysis prior to face recognition. This paper devises a joint clustering and classification scheme which learns deep face associations in an easy-to-hard way. Our method is based on hierarchical clustering where the early iterations tend to preserve high reliability. The rationale of our method is that a reliable clustering result can provide insights on the distribution of the feature space, that can guide the classification that follows. Experimental evaluations on three tasks, face verification, face identification and rank-order search, demonstrates better or competitive performance compared to the state-of-the-art, on all three experiments

Working with female offenders in restorative justice frameworks: Effective and ethical practice

Despite a recent increase in restorative justice practice in the criminal justice system, to date there has been no in-depth consideration of the impact of gender in these settings. This paper presents findings from a unique qualitative study on female offenders’ experiences of restorative conferencing in England and Wales, drawing on interviews with practitioners who have worked with female cases, as well as with women who have gone through a restorative justice conference in a perpetrator capacity. Gender specific factors, suggested to be especially valuable for practitioners to consider when delivering effective and ethical restorative conferences with female offenders, are outlined

A Review of Risk Perceptions and Other Factors that Influence Flood Mitigation Behavior

In flood risk management, a shift can be observed toward more integrated approaches that increasingly address the role of private households in implementing flood damage mitigation measures. This has resulted in a growing number of studies into the supposed positive relationship between individual flood risk perceptions and mitigation behavior. Our literature review shows, however, that, actually, this relationship is hardly observed in empirical studies. Two arguments are provided as an explanation. First, on the basis of protection motivation theory, a theoretical framework is discussed suggesting that individuals’ high-risk perceptions need to be accompanied by coping appraisal to result in a protective response. Second, it is pointed out that possible feedback from already-adopted mitigation measures on risk perceptions has hardly been considered by current studies. In addition, we also provide a review of factors that drive precautionary behavior other than risk perceptions. It is found that factors such as coping appraisal are consistently related to mitigation behavior. We conclude, therefore, that the current focus on risk perceptions as a means to explain and promote private flood mitigation behavior is not supported on either theoretical or empirical grounds