993 resultados para Forest protection


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This book presents a comprehensive assessment of regional responses to the crisis in the asylum/refugee system and critically examines how different regions tackle the problem. The chapters consider the fundamental challenges which undermine an effective asylum process as well as regional difficulties with the various circumstances surrounding asylum seekers. With contributions on Africa, Europe, Latin America, South Asia and the Middle East, and the Pacific, the collection strives to appreciate what informs each region’s approach to the asylum process and asks if there are issues common to every region and if regions can learn from one another. The book seeks an understanding of the existing legal regime for the protection of asylum seekers and how regional institutions such as human rights commissions and regional courts enforce and adjudicate the law.

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Artificial neural network (ANN) methods are used to predict forest characteristics. The data source is the Southeast Alaska (SEAK) Grid Inventory, a ground survey compiled by the USDA Forest Service at several thousand sites. The main objective of this article is to predict characteristics at unsurveyed locations between grid sites. A secondary objective is to evaluate the relative performance of different ANNs. Data from the grid sites are used to train six ANNs: multilayer perceptron, fuzzy ARTMAP, probabilistic, generalized regression, radial basis function, and learning vector quantization. A classification and regression tree method is used for comparison. Topographic variables are used to construct models: latitude and longitude coordinates, elevation, slope, and aspect. The models classify three forest characteristics: crown closure, species land cover, and tree size/structure. Models are constructed using n-fold cross-validation. Predictive accuracy is calculated using a method that accounts for the influence of misclassification as well as measuring correct classifications. The probabilistic and generalized regression networks are found to be the most accurate. The predictions of the ANN models are compared with a classification of the Tongass national forest in southeast Alaska based on the interpretation of satellite imagery and are found to be of similar accuracy.

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While video surveillance systems have become ubiquitous in our daily lives, they have introduced concerns over privacy invasion. Recent research to address these privacy issues includes a focus on privacy region protection, whereby existing video scrambling techniques are applied to specific regions of interest (ROI) in a video while the background is left unchanged. Most previous work in this area has only focussed on encrypting the sign bits of nonzero coefficients in the privacy region, which produces a relatively weak scrambling effect. In this paper, to enhance the scrambling effect for privacy protection, it is proposed to encrypt the intra prediction modes (IPM) in addition to the sign bits of nonzero coefficients (SNC) within the privacy region. A major issue with utilising encryption of IPM is that drift error is introduced outside the region of interest. Therefore, a re-encoding method, which is integrated with the encryption of IPM, is also proposed to remove drift error. Compared with a previous technique that uses encryption of IPM, the proposed re-encoding method offers savings in the bitrate overhead while completely removing the drift error. Experimental results and analysis based on H.264/AVC were carried out to verify the effectiveness of the proposed methods. In addition, a spiral binary mask mechanism is proposed that can reduce the bitrate overhead incurred by flagging the position of the privacy region. A definition of the syntax structure for the spiral binary mask is given. As a result of the proposed techniques, the privacy regions in a video sequence can be effectively protected by the enhanced scrambling effect with no drift error and a lower bitrate overhead.

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There are a range of theoretical approaches which may inform the interface between child protection and adult mental health services. These theoretical perspectives tend to be focused on either child protection or mental health with no agreed integrating framework. The interface continues to be identified, in research, case management reviews and inquiry reports, as complex and problematic. This paper proposes that more positive, integrated approaches to service user engagement, risk assessment and management may lead to better outcomes in working with families experiencing parental mental health problems and child protection concerns. It is proposed that the recovery approach, increasingly used in mental health services, can inform the processes of engagement, assessment and intervention at the mental health and child protection interface. The article provides a critical overview of the recovery approach and compares it with approaches typifying interventions in child protection work to date. Relevant research and inquiries are also examined as a context for how to more effectively respond to cases where there are issues around parental mental health problems and child protection. The article concludes with case material to illustrate the potential application of the recovery approach to the interface between mental health and child protection services.

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This article analyses the relevance of the ECJ ruling in Junk for German labour law.

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This study investigates the potential of the prohibition of indirect race discrimination to be used for law reform, and to uncover discriminatory practices. It reflects on the history and contents of the concept, and focuses in particular on its application in the Republic of South Africa