Continuous-time correlated random walk model for animal telemetry data

We propose a continuous-time version of the correlated random walk model for animal telemetry data. The continuous-time formulation allows data that have been nonuniformly collected over time to be modeled without subsampling, interpolation, or aggregation to obtain a set of locations uniformly spaced in time. The model is derived from a continuous-time Ornstein-Uhlenbeck velocity process that is integrated to form a location process. The continuous-time model was placed into a state-space framework to allow parameter estimation and location predictions from observed animal locations. Two previously unpublished marine mammal telemetry data sets were analyzed to illustrate use of the model, by-products available from the analysis, and different modifications which are possible. A harbor seal data set was analyzed with a model that incorporates the proportion of each hour spent on land. Also, a northern fur seal pup data set was analyzed with a random drift component to account for directed travel and ocean currents.     

Using the land transformation model to forecast vacant land

Growing or shrinking cities can experience increases in vacant land. As urban populations and boundaries fluctuate, holes can open in once tight urban areas. Many cities chase growth-oriented approaches to dealing with vacancies. It is critical to understand land-use alteration to accurately predict transformations of physical change in order to make better informed decisions about this phenomenon. This research utilizes the land transformation model (LTM), an artificial neural networking mechanism in Geographic Information Systems, to forecast vacant land. Variable influence on vacant land prediction and accuracy of the LTM is assessed by comparing input factors and patterns, using time-series data from 1990 to 2010 in Fort Worth, Texas, USA. Results indicate that the LTM can be useful in simulating vacant land-use changes but more precise mechanisms are necessary to increase accuracy. This will allow for more proactive decisions to better regulate the process of urban decline and regeneration.     

World diamond industry: 1970–2000

The diamond cartel has remained effective in controlling diamond supplies and prices for a longer period than any other major minerals cartel in the twentieth century. This paper examines the diamond pipeline from mine to the jewellery market. Particular attention is given to the characteristics of diamonds and of the industry structure that make the long-term stability of the cartel possible. The strategies of De Beers Consolidated Diamond Mines in controlling rough gem supplies and prices are examined, and projections are made to 2000. The paper shows that in spite of a projected decrease in the share of total diamond production sold through the De Beers' cartel in the 1990s, the cartel is expected to continue effectively to control supplies and prices.     

Case study: Browning-ferris industries' computerized system for managing audit and environment performance

While some companies have established scoring systems within their audit programs, few utilize the full potential for measurement of the information gathered and subsequently produced from audits. In this article, the use of a computerized tracking system developed and used by Browning-Ferris Industries is discussed, along with a data report that details the completion of audit items and helps assure that action plans resulting from environmental audits are completed. This and other summary reports from the computer tracking system have provided meaningful measures of individual facilities' and overall company performance.     

COMPARISON OF PROCESS‐BASED AND ARTIFICIAL NEURAL NETWORK APPROACHES FOR STREAMFLOW MODELING IN AN AGRICULTURAL WATERSHED1

ABSTRACT: The performance of the Soil and Water Assessment Tool (SWAT) and artificial neural network (ANN) models in simulating hydrologic response was assessed in an agricultural watershed in southeastern Pennsylvania. All of the performance evaluation measures including Nash‐Sutcliffe coefficient of efficiency (E) and coefficient of determination (R²) suggest that the ANN monthly predictions were closer to the observed flows than the monthly predictions from the SWAT model. More specifically, monthly streamflow E and R² were 0.54 and 0.57, respectively, for the SWAT model calibration period, and 0.71 and 0.75, respectively, for the ANN model training period. For the validation period, these values were ?0.17 and 0.34 for the SWAT and 0.43 and 0.45 for the ANN model. SWAT model performance was affected by snowmelt events during winter months and by the model's inability to adequately simulate base flows. Even though this and other studies using ANN models suggest that these models provide a viable alternative approach for hydrologic and water quality modeling, ANN models in their current form are not spatially distributed watershed modeling systems. However, considering the promising performance of the simple ANN model, this study suggests that the ANN approach warrants further development to explicitly address the spatial distribution of hydrologic/water quality processes within watersheds.     

Software tools to support incident reporting in safety-critical systems

Incident reporting systems are playing an increasingly important role in the development and maintenance of safety-critical applications. The perceived success of the FAA's Aviation Safety Reporting System (ASRS) and the FDA's MedWatch has led to the establishment of similar national and international schemes. These enable individuals and groups to report their safety concerns in a confidential or anonymous manner. Unfortunately, many of these systems are becoming victims of their own success. The ASRS and MedWatch have both now received over 500,000 submissions. In consequence, the administrators of incident reporting systems increasingly rely upon software tools to support the administration of their systems. In the past, these systems have relied upon ad hoc applications of conventional database technology. However, there are several reasons why this technology is inadequate for many large-scale reporting schemes. In particular, the problems of query formation often result in poor precision and recall. This, in turn, has profound implications for safety-critical applications. Users may fail to identify similar incidents within national or international collections. These ad hoc approaches also neglect the opportunities provided by recent developments in computer assisted interviewing and in the monitoring of retrieval activities to build models of user behavior. These techniques offer a number of potential benefits. For instance, it is possible to automatically detect potential biases in the way that investigators analyze particular incidents.     

Visualizing reductive dechlorination in support of intrinsic bioremediation using multivariate plots and GIS

Demonstrating intrinsic bioremediation requires not only that the right types of evidence be gathered, but also that those data be analyzed at an appropriate level of detail and presented in a manner that clearly illustrates the key trends to the target audience. The goal of this study was to develop one type of multivariate pattern diagram, the pie diagram, for clearly and efficiently presenting data demonstrating the occurrence of reductive dechlorination at sites contaminated by chlorinated ethenes. The pie diagrams were created using normalized ethenes molar concentrations to estimate and illustrate the changes in the concentrations of contaminants and metabolic intermediates that could be attributed to biodegradative processes. Spatial pie‐diagram maps illustrating the normalized chlorinated‐ethenes data were produced using geographic information system (GIS) software. Application of this visualization tool is demonstrated using an example data set and is compared with a conventional x‐y graph of the data. The trends elucidated on the basis of the pie diagrams, coupled with additional site evidence of natural attenuation (e.g., electron donor and acceptor data), are shown to provide a consistent interpretation of the site data. © 2002 Wiley Periodicals, Inc.