Coordinating visualizations of polysemous action: Values added for grounding proportion

We contribute to research on visualization as an epistemic learning tool by inquiring into the didactical potential of having students visualize one phenomenon in accord with two different partial meanings of the same concept. 22 Grade 4-6 students participated in a design study that investigated the emergence of proportional-equivalence notions from mediated perceptuomotor schemas. Working as individuals or pairs in tutorial clinical interviews, students solved non-symbolic interaction problems that utilized remote-sensing technology. Next, they used symbolic artifacts interpolated into the problem space as semiotic means to objectify in mathematical register a variety of both additive and multiplicative solution strategies. Finally, they reflected on tensions between these competing visualizations of the space. Micro-ethnographic analyses of episodes from three paradigmatic case studies suggest that students reconciled semiotic conflicts by generating heuristic logico-mathematical inferences that integrated competing meanings into cohesive conceptual networks. These inferences hinged on revisualizing additive elements multiplicatively. Implications are drawn for rethinking didactical design for proportions. © 2013 FIZ Karlsruhe

Non-invasive imaging of subsurface paint layers with optical coherence tomography

Optical coherence tomography (OCT) systems are fast scanning infrared Michelson interferometers designed for the non-invasive examination of the interiors of the eye and subsurface structures of biological tissues. OCT has recently been applied to the non-invasive examinations of the stratigraphy of paintings and museum artefacts. So far this is the only technique capable of imaging non-invasively the subsurface structure of paintings and painted objects. Unlike the traditional method of paint cross-section examination where sampling is required, the non-invasive and non-contact nature of the technique enables the examination of the paint cross-section anywhere on a painting, as there is no longer an issue with conservation ethics regarding the taking of samples from historical artefacts. A range of applications of the technique including the imaging of stratigraphy of paintings and painted artefacts, the imaging of underdrawings to the analysis of the optical properties of paint and varnish layers is presented. Future projects on the application of OCT to art conservation are discussed

Pengembangan Lks IPA Berbasis Project Based Learning untuk Meningkatkan Keterampilan Kerja Ilmiah Kelas IV

This study aims to develop a student worksheets project based learning in science teaching is done by improving the skills of scientific work of students. This research was conducted as many as six sessions using two different worksheet, the worksheet early and worksheets project based learning. The results of the initial work sheet obtained average students scientific work skills at 10.05 and the results of the Project based learning worksheets obtained average students scientific work skills at 14.88. An assessment of student worksheets project-based learning of expert learning device of 93.33, from the responses of teacher is at 100, from student responses at 89.96, the results of the worksheets based learning project categorized as feasible to use

Terms of trade instability and balance of payments adjustment in Nigeria: A simultaneous equation modelling

This paper employs simultaneous equation modeling to test the  hypothesis that impact of terms of trade instability has no significant  impact on Nigeria.s balance of payments position. Empirical evidence  reveals that BOP has negative relationship with terms of trade. This implies that for any 1percent instability (shock) in terms of trade, balance of  payment will be adversely affected by about 1.8 percent. Hence it becomes pertinent for policy makers to pursue policies that will stabilize terms of  trade. The study also invalidates the Marshal-learner condition. Hence,  caution should not be thrown to the wind in adopting the policy of  deliberately depreciating the naira especially because of the peculiarity of the country.s exports and imports. Indeed, evidence thus abound that it is not enough to increase exports rather the export basket should be  diversified. The negative association between inflation and BOP should be a source of worry to policy makers. It is therefore imperative for economy to address exchange control problems to the effect that the naira does not depreciate beneath a managed floor value.Key Words: Terms of trade instability, Balance of payments adjustment, Nigeri

Characterizing normal crossing hypersurfaces

The objective of this article is to give an effective algebraic characterization of normal crossing hypersurfaces in complex manifolds. It is shown that a hypersurface has normal crossings if and only if it is a free divisor, has a radical Jacobian ideal and a smooth normalization. Using K. Saito's theory of free divisors, also a characterization in terms of logarithmic differential forms and vector fields is found and and finally another one in terms of the logarithmic residue using recent results of M. Granger and M. Schulze.Comment: v2: typos fixed, final version to appear in Math. Ann.; 24 pages, 2 figure

Batch process optimization via run-to-run constraints adaptation

© 2007 EUCA.In the batch process industry, the available models carry a large amount of uncertainty and can seldom be used to directly optimize real processes. Several measurement-based optimization methods have been proposed to deal with model mismatch and process disturbances. Constraints often play a dominant role in the dynamic optimization of batch processes. In their presence, the optimal input profiles are characterized by a set of arcs, switching times and active path and terminal constraints. This paper presents a novel method tailored to those problems where the potential of optimization arises mainly from the correct set of path and terminal constraints being active. The input profiles are computed between successive runs by dynamic optimization of a fixed nominal model, and the constraints in the optimization problem are adapted using measured information from previous batches. Note that, unlike many existing optimization schemes, the measurements are not used to update the process model. Moreover, the proposed approach has the potential to uncover the optimal input structure. This is demonstrated on a simple semi-batch reactor example

Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics

Value-based reinforcement-learning algorithms provide state-of-the-art results in model-free discrete-action settings, and tend to outperform actor-critic algorithms. We argue that actor-critic algorithms are limited by their need for an on-policy critic. We propose Bootstrapped Dual Policy Iteration (BDPI), a novel model-free reinforcement-learning algorithm for continuous states and discrete actions, with an actor and several off-policy critics. Off-policy critics are compatible with experience replay, ensuring high sample-efficiency, without the need for off-policy corrections. The actor, by slowly imitating the average greedy policy of the critics, leads to high-quality and state-specific exploration, which we compare to Thompson sampling. Because the actor and critics are fully decoupled, BDPI is remarkably stable, and unusually robust to its hyper-parameters. BDPI is significantly more sample-efficient than Bootstrapped DQN, PPO, and ACKTR, on discrete, continuous and pixel-based tasks. Source code: https://github.com/vub-ai-lab/bdpi.Comment: Accepted at the European Conference on Machine Learning 2019 (ECML

Opinion Mining on Non-English Short Text

As the type and the number of such venues increase, automated analysis of sentiment on textual resources has become an essential data mining task. In this paper, we investigate the problem of mining opinions on the collection of informal short texts. Both positive and negative sentiment strength of texts are detected. We focus on a non-English language that has few resources for text mining. This approach would help enhance the sentiment analysis in languages where a list of opinionated words does not exist. We propose a new method projects the text into dense and low dimensional feature vectors according to the sentiment strength of the words. We detect the mixture of positive and negative sentiments on a multi-variant scale. Empirical evaluation of the proposed framework on Turkish tweets shows that our approach gets good results for opinion mining