Monitoring Payments for Watershed Services Schemes in Developing Countries

Payments for watershed services (PWS) are schemes that use funds from water users (including governments) as an incentive for landholders to improve their land management practices. They are increasingly seen as a viable policy alternative to watershed management issues, and a means of addressing chronic problems such as declining water flows, deteriorating water quality and flooding. In some places, local governments, donor agencies and NGOs are actively trying to upscale and replicate PWS schemes across the area. While their apparent success and progress in launching new initiatives is encouraging, there is still much to be learned from formative experiences in this field, especially with regard to monitoring and evaluation.In this paper we discuss the monitoring and evaluation criteria behind compliance or transactional monitoring, which ensures that contracts are followed, and effectiveness conditionality, which looks at how schemes manage to achieve their environmental objectives regardless of the degree of compliance. Although the two are usually linked, a high degree of compliance does not necessarily ensure that a scheme is effective. This is because a poorly designed scheme may target the wrong land managers and land that is at least risk, meaning that payments do not generate the desired hydro-ecological or conservation benefits. As the levering capacity to demand payments for better watershed management increases, so does the need to understand the dynamics of such activities and demonstrate their impacts. While the growing interest in such schemes shows that participants believe in the principle of land management, evidence of their impact is needed to determine which initiatives genuinely add value and are worth pursuing

Analysis and Forecasting of Trending Topics in Online Media Streams

Among the vast information available on the web, social media streams capture what people currently pay attention to and how they feel about certain topics. Awareness of such trending topics plays a crucial role in multimedia systems such as trend aware recommendation and automatic vocabulary selection for video concept detection systems. Correctly utilizing trending topics requires a better understanding of their various characteristics in different social media streams. To this end, we present the first comprehensive study across three major online and social media streams, Twitter, Google, and Wikipedia, covering thousands of trending topics during an observation period of an entire year. Our results indicate that depending on one's requirements one does not necessarily have to turn to Twitter for information about current events and that some media streams strongly emphasize content of specific categories. As our second key contribution, we further present a novel approach for the challenging task of forecasting the life cycle of trending topics in the very moment they emerge. Our fully automated approach is based on a nearest neighbor forecasting technique exploiting our assumption that semantically similar topics exhibit similar behavior. We demonstrate on a large-scale dataset of Wikipedia page view statistics that forecasts by the proposed approach are about 9-48k views closer to the actual viewing statistics compared to baseline methods and achieve a mean average percentage error of 45-19% for time periods of up to 14 days.Comment: ACM Multimedia 201

Alien Registration- Wilcox, Dengel (Presque Isle, Aroostook County)

https://digitalmaine.com/alien_docs/33688/thumbnail.jp

A step towards understanding paper documents

This report focuses on analysis steps necessary for a paper document processing. It is divided in three major parts: a document image preprocessing, a knowledge-based geometric classification of the image, and a expectation-driven text recognition. It first illustrates the several low level image processing procedures providing the physical document structure of a scanned document image. Furthermore, it describes a knowledge-based approach, developed for the identification of logical objects (e.g., sender or the footnote of a letter) in a document image. The logical identifiers provide a context-restricted consideration of the containing text. While using specific logical dictionaries, a expectation-driven text recognition is possible to identify text parts of specific interest. The system has been implemented for the analysis of single-sided business letters in Common Lisp on a SUN 3/60 Workstation. It is running for a large population of different letters. The report also illustrates and discusses examples of typical results obtained by the system