PARTICIPATORY MODELLING TO SUPPORT DECISION MAKING IN WATER MANAGEMENT. A CASE STUDY IN THE MIDDLE GUADIANA BASIN, SPAIN.

Resource /Energy Economics and Policy,

Exploiting Cognitive Structure for Adaptive Learning

Adaptive learning, also known as adaptive teaching, relies on learning path recommendation, which sequentially recommends personalized learning items (e.g., lectures, exercises) to satisfy the unique needs of each learner. Although it is well known that modeling the cognitive structure including knowledge level of learners and knowledge structure (e.g., the prerequisite relations) of learning items is important for learning path recommendation, existing methods for adaptive learning often separately focus on either knowledge levels of learners or knowledge structure of learning items. To fully exploit the multifaceted cognitive structure for learning path recommendation, we propose a Cognitive Structure Enhanced framework for Adaptive Learning, named CSEAL. By viewing path recommendation as a Markov Decision Process and applying an actor-critic algorithm, CSEAL can sequentially identify the right learning items to different learners. Specifically, we first utilize a recurrent neural network to trace the evolving knowledge levels of learners at each learning step. Then, we design a navigation algorithm on the knowledge structure to ensure the logicality of learning paths, which reduces the search space in the decision process. Finally, the actor-critic algorithm is used to determine what to learn next and whose parameters are dynamically updated along the learning path. Extensive experiments on real-world data demonstrate the effectiveness and robustness of CSEAL.Comment: Accepted by KDD 2019 Research Track. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD'19

Grid-enabling Satellite Image Archive Prototype for UA Space Grid Testbed

* The work is partially supported by the grant of National Academy of Science of Ukraine for the support of scientific researches by young scientists No 24-7/05, " Розробка Desktop Grid-системи і оптимізація її продуктивності ”.The paper describes practical approach to implementation of satellite data archive using Globus Toolkit 4 components. The solutions consists in converting a hierarchy of remote data files available via FTP into Grid- enabled archive. All etries of such archive will be indexed using arbitrary but pre-defined XML schema. The information will be exposed via MDS4 Index service and the actual data will be exposed via GridFTP. The schema used in our solution is simple enough for understanding but in a real life applications we should use metadata standards such as ISO 19139 and ISO 19115 in particular. A working prototype of the archive described in this paper is deployed on the Grid testbed of Space Research Institute of National Academy of Science and National Space Agency of Ukraine (SRI-NASU-NSAU). The SRI-NASU-NSAU testbed is briefly described in this paper as well

Exploratory Climate Data Visualization and Analysis Using DV3D and UVCDAT

Earth system scientists are being inundated by an explosion of data generated by ever-increasing resolution in both global models and remote sensors. Advanced tools for accessing, analyzing, and visualizing very large and complex climate data are required to maintain rapid progress in Earth system research. To meet this need, NASA, in collaboration with the Ultra-scale Visualization Climate Data Analysis Tools (UVCOAT) consortium, is developing exploratory climate data analysis and visualization tools which provide data analysis capabilities for the Earth System Grid (ESG). This paper describes DV3D, a UV-COAT package that enables exploratory analysis of climate simulation and observation datasets. OV3D provides user-friendly interfaces for visualization and analysis of climate data at a level appropriate for scientists. It features workflow inte rfaces, interactive 40 data exploration, hyperwall and stereo visualization, automated provenance generation, and parallel task execution. DV30's integration with CDAT's climate data management system (COMS) and other climate data analysis tools provides a wide range of high performance climate data analysis operations. DV3D expands the scientists' toolbox by incorporating a suite of rich new exploratory visualization and analysis methods for addressing the complexity of climate datasets

Participatory modelling to support decision making in water management. A case study in the middle Guadiana basin, Spain.

The objective of this research was the implementation of a participatory process for the development of a tool to support decision making in water management. The process carried out aims at attaining an improved understanding of the water system and an encouragement of the exchange of knowledge and views between stakeholders to build a shared vision of the system. In addition, the process intends to identify impacts of possible solutions to given problems, which will help to take decisions

GDP Data Revisions and Forward-Looking Monetary Policy in Switzerland

This paper analyzes forward-looking rules for Swiss monetary policy in a small structural VAR model consisting of four variables taking into account data revisions for GDP. First, the paper develops an analytical method to analyze the effect of data revision errors in GDP on the ex ante or conditional inflation-output-growth volatility trade-off and applies it to Swiss data. Second, the effects of different targets in a forward-looking monetary policy on ex post or unconditional volatility of inflation and output growth is explored by a simulation exercise. In general, the results obtained suggest that focusing monetary policy on GDP growth instead on inflation may lead to an inefficient policy with both increased medium term inflation and GDP growth volatility in the presence of GDP data revisions.Structural VAR, forward-looking monetary policy, efficiency frontier, GDP data revisions

Wright State University College of Engineering and Computer Science Bits and PCs newsletter, Volume 13, Number 4, April 1997

A ten page newsletter created by the Wright State University College of Engineering and Computer Science that addresses the current affairs of the college.https://corescholar.libraries.wright.edu/bits_pcs/1074/thumbnail.jp