Small Telescope Exoplanet Transit Surveys: XO

The XO project aims at detecting transiting exoplanets around bright stars from the ground using small telescopes. The original configuration of XO (McCullough et al. 2005) has been changed and extended as described here. The instrumental setup consists of three identical units located at different sites, each composed of two lenses equipped with CCD cameras mounted on the same mount. We observed two strips of the sky covering an area of 520 deg$^2$ for twice nine months. We build lightcurves for ~20,000 stars up to magnitude R~12.5 using a custom-made photometric data reduction pipeline. The photometric precision is around 1-2% for most stars, and the large quantity of data allows us to reach a millimagnitude precision when folding the lightcurves on timescales that are relevant to exoplanetary transits. We search for periodic signals and identify several hundreds of variable stars and a few tens of transiting planet candidates. Follow-up observations are underway to confirm or reject these candidates. We found two close-in gas giant planets so far, in line with the expected yield.Comment: Invited review, 25 pages, 16 figure

Beat Em or Join Em: Export Subsidies versus International Research Joint Ventures in Oligopolistic Markets

This paper compares adversarial with cooperative industrial and trade policies in a dynamic oligopoly game in which a home and foreign firm compete in R&D and output and, because of spillovers, each firm benefits from the other's R&D. When the government can commit to an export subsidy, such a policy raises welfare relative to cooperation, except when R&D is highly effective and spillovers are near-complete. Without commitment, however, subsidisation may yield welfare levels much lower than cooperation and lower even than free trade, though qualifications to the dangers from no commitment are noted.

A Congeries of Absorption Cross Sections for Wavelengths Less Than 3000 degrees Angstrom

The absorption of ultraviolet solar radiation is of prime importance for the study of planetary atmospheres.The absorption coefficients of most of the atmospheric gases have been measured by a number of investigators, but the results are scattered throughout the literature. This report contains a detailed collection of absorption cross sections of the gases listed in Table 1 for wavelengths less than 3000 degrees angstroms. The data on each gas are given together with a historical sketch of the study of the gas and a list of the pertinent references. Also included is a study of the absorption and photoionization coefficients of the major atmospheric gases at intense solar emission lines

Exploring the relationship between task, teacher actions, and student learning

We are examining actions that teachers take to convert tasks into learning opportunities. In this paper, we contrast ways that three teachers convert the same task into lessons, and the way that their lessons reflect their intent. We found that the teachers did what they intended to do, that this was connected to their appreciation of the mathematics involved, and directly influenced the learning opportunities of the students. To the extent that the potential of the task was reduced, this seemed due to the lack of mathematical confidence in the case of two of the teachers

Why Campaigns for Local Transportation Initiatives Succeed or Fail: An Analysis of Four Communities and National Data, MTI Report 00-01

As funding from state and national sources has dwindled and demands for relief from traffic and congestion have grown, local governments and transportation agencies are increasingly left to develop their own sources of enhanced revenues. Frequently the bid to increase available revenues comprises a local ballot measure, enabling the citizens served by these governments and agencies to express their preferences for or against increased taxation in support of an improved transportation system. What determines the success of campaigns in support of such ballot measures? To answer this question, this report includes the use of two different approaches and data sources. 1) A statistical analysis of community-level characteristics. Data from localities across the nation, as well those within the state of California, that have conducted elections for transportation tax increase are analyzed to determine what factors seem to affect the outcome of such elections. 2) Case studies of four communities that recently conducted elections for transportation tax increases (Santa Clara and Sonoma Counties in California, and the Denver and Seattle metropolitan areas). The case studies allow for in-depth, qualitative understanding of what election strategies and other campaign elements comprise successful or unsuccessful efforts to raise local revenues. Among the most significant findings from the statistical analysis of local elections were the following: Efforts to fund transportation with taxes where the proportion of elderly is greater than 9 percent are more likely to succeed In communities where the percentage of elderly is greater than 9 percent, the analysis indicates that voters may be more willing to accept local transportation taxes. However, in communities where the percentage of elderly is less than 9 percent, transportation measures may require significantly more determined marketing to enhance the probability of passage. Efforts to increase sales taxes for transportation programs will be less successful in communities with higher sales taxes. A relatively strong and negative relationship between sales tax and support for transportation tax initiatives was identified in the national election data. This suggests that communities with relatively higher sales taxes will be hard pressed to convince citizens to support additional increases

Alien Registration- Sullivan, Dennis O. (Rumford, Oxford County)

https://digitalmaine.com/alien_docs/14094/thumbnail.jp

Comparing the Effectiveness of Support Vector Machines and Convolutional Neural Networks for Determining User Intent in Conversational Agents

Over the last fifty years, conversational agent systems have evolved in their ability to understand natural language input. In recent years Natural Language Processing (NLP) and Machine Learning (ML) have allowed computer systems to make great strides in the area of natural language understanding. However, little research has been carried out in these areas within the context of conversational systems. This paper identifies Convolutional Neural Network (CNN) and Support Vector Machine (SVM) as the two ML algorithms with the best record of performance in ex isting NLP literature, with CNN indicated as generating the better results of the two. A comprehensive experiment is defined where the results of SVM models utilising sev eral kernels are compared to the results of a selection of CNN models. To contextualise the experiment to conversational agents a dataset based on conversational interactions is used. A state of the art NLP pipeline is also created to work with both algorithms in the context of the agent dataset. By conducting a detailed statistical analysis of the results, this paper proposes to provide an extensive indicator as to which algo rithm offers better performance for agent-based systems. Ultimately the experimental results indicate that CNN models do not necessarily generate better results than SVM models. In fact, the SVM model utilising a Radial Basis Function kernel generates statistically better results than all other models considered under these experimental conditions

Alien Registration- Sullivan, John O. (Rumford, Oxford County)

https://digitalmaine.com/alien_docs/14095/thumbnail.jp