Interim report on the progress of an inventory of artesian wells in Florida: leading to the enforcement of sections 370.051 - 370.54, Florida statues

One of the causes of lower artesian pressure, water waste and aquifer contamination is the misuse and insufficient care of artesian wells. In 1953, Senate Bill No. 57, entitled "An Act to Protect and Control the Artesian Waters of the State" (see Appendix) became a law. This law was passed through the efforts exerted by leading members of the Senate and the House of Representatives, who understood the need for a wise and controlled expenditure of our most valuable natural resource. The State Geologist and his authorized representatives were designated by this law to enforce this conservation measure; however, no financial provision was included for the 1953-55 biennium. The proposed program of the Florida Geological Survey for this biennium did not include the funds nor provide any full-time personnel for the enforcement of this statute. As a result, little actual work was accomplished during these two years, although much time was given to planning and discussion of the problem. Realizing that this program could provide additional basic data needed in the analysis of the water-supply problem, the State Geologist sought and was granted by the 1955 Legislature adequate funds with which to activate the first phase of the enforcement of Florida Statute No. 370.051-054. Enumerated below is a summary of the progress made on this investigation as outlined previously: 1. Data have been collected on 967 wildly flowing wells in 22 counties. 2. Chloride determinations have been run on 850 of the 967 wells. 3. Of the 967 wells, 554 have chlorides in excess of the 250 ppm, the upper limit assigned by the State Board of Health for public consumption. 4. Water escapes at the rate of 37, 762 gallons per minute from these 967 wells. This amounts to 54, 377, 280 gallons per day. The investigation is incomplete at this time; therefore, no final conclusions can be reached. However, from data already collected, the following recommendations are proposed: 1. That the present inventory of wildly flowing wells be completed for the entire State. 2. That the current inventory of wildly flowing wells be expanded at the conclusion of the present inventory to include all flowing wells. 3. That a complete statewide inventory program be established and conducted in cooperation with the Ground Water Branchof the U.S. Geological Survey. 4. That the enforcement functions as set down in Sections 370.051/.054, Florida Statutes, be separated from the program to collect water-resource data and that these functions be given to the Water Resources Department, if such is created (to be recommended by the Water Resources Study Commission in a water policy law presented to the 1957 Legislature). 5. That the research phase (well inventory) of the program remain under the direction of the Florida Geological Survey. (PDF contains 204 pages.)

The Relationship between Decision Trees and the Scale of Train Data Set

Decision Trees need train samples in the train data set to get classification rules. If the number of train data was too small, the important information might be missed and thus the model could not explain the classification rules of data. While it is not affirmative that large scale of train data set can get well model. This Paper analysis the relationship between decision trees and the train data scale. We use nine decision tree algorithms to experiment the accuracy, complexity and robustness of decision tree algorithms. Some results are demonstrated.

Basic equations for ferroelectrics

A set of new formula of energy functions for ferroelectrics was proposed, and then the new basic equations were derived in this paper. The finite element formulation based on the new basic equations was improved to avoid the equivalent nodal load produced by remnant polarization. With regard to the fundamentals of mathematics and physics, the new energy functions and basic equations are reasonable for the material element of ferroelectrics in finite element analysis.

User’s Guide to ADMB2R: A Set of AD Model Builder Output Routines Compatible with the R Statistics Language

ADMB2R is a collection of AD Model Builder routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 ADMB2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the ADMB2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer ADMB2R to others in the hope that they will find it useful. (PDF contains 30 pages)

User’s Guide to C2R: A Set of C Language Output Routines Compatible with the R Statistics Language

C2R is a collection of C routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 C2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the C2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer C2R to others in the hope that they will find it useful. (PDF contains 27 pages)

Influence of Training Set Selection in Artificial Neural Network-Based Propagation Path Loss Predictions

This paper analyzes the use of artificial neural networks (ANNs) for predicting the received power/path loss in both outdoor and indoor links. The approach followed has been a combined use of ANNs and ray-tracing, the latter allowing the identification and parameterization of the so-called dominant path. A complete description of the process for creating and training an ANN-based model is presented with special emphasis on the training process. More specifically, we will be discussing various techniques to arrive at valid predictions focusing on an optimum selection of the training set. A quantitative analysis based on results from two narrowband measurement campaigns, one outdoors and the other indoors, is also presented.

Scientific Data Application Profile Scoping Study

This study was undertaken by UKOLN on behalf of the Joint Information Systems Committee (JISC) in the period April to September 2008. Application profiles are metadata schemata which consist of data elements drawn from one or more namespaces, optimized for a particular local application. They offer a way for particular communities to base the interoperability specifications they create and use for their digital material on established open standards. This offers the potential for digital materials to be accessed, used and curated effectively both within and beyond the communities in which they were created. The JISC recognized the need to undertake a scoping study to investigate metadata application profile requirements for scientific data in relation to digital repositories, and specifically concerning descriptive metadata to support resource discovery and other functions such as preservation. This followed on from the development of the Scholarly Works Application Profile (SWAP) undertaken within the JISC Digital Repositories Programme and led by Andy Powell (Eduserv Foundation) and Julie Allinson (RRT UKOLN) on behalf of the JISC. Aims and Objectives 1.To assess whether a single metadata AP for research data, or a small number thereof, would improve resource discovery or discovery-to-delivery in any useful or significant way. 2.If so, then to:a.assess whether the development of such AP(s) is practical and if so, how much effort it would take; b.scope a community uptake strategy that is likely to be successful, identifying the main barriers and key stakeholders. 3.Otherwise, to investigate how best to improve cross-discipline, cross-community discovery-to-delivery for research data, and make recommendations to the JISC and others as appropriate. Approach The Study used a broad conception of what constitutes scientific data, namely data gathered, collated, structured and analysed using a recognizably scientific method, with a bias towards quantitative methods. The approach taken was to map out the landscape of existing data centres, repositories and associated projects, and conduct a survey of the discovery-to-delivery metadata they use or have defined, alongside any insights they have gained from working with this metadata. This was followed up by a series of unstructured interviews, discussing use cases for a Scientific Data Application Profile, and how widely a single profile might be applied. On the latter point, matters of granularity, the experimental/measurement contrast, the quantitative/qualitative contrast, the raw/derived data contrast, and the homogeneous/heterogeneous data collection contrast were discussed. The Study report was loosely structured according to the Singapore Framework for Dublin Core Application Profiles, and in turn considered: the possible use cases for a Scientific Data Application Profile; existing domain models that could either be used or adapted for use within such a profile; and a comparison existing metadata profiles and standards to identify candidate elements for inclusion in the description set profile for scientific data. The report also considered how the application profile might be implemented, its relationship to other application profiles, the alternatives to constructing a Scientific Data Application Profile, the development effort required, and what could be done to encourage uptake in the community. The conclusions of the Study were validated through a reference group of stakeholders.

Viewpoints cards - full set

Viewpoints cards for developing successful student-staff partnerships.