BirdVis: visualizing and understanding bird populations

Birds are unrivaled windows into biotic processes at all levels and are proven indicators of ecological well-being. Understanding the determinants of species distributions and their dynamics is an important aspect of ecology and is critical for conservation and management. Through crowdsourcing, since 2002, the eBird project has been collecting bird observation records. These observations, together with local-scale environmental covariates such as climate, habitat, and vegetation phenology have been a valuable resource for a global community of educators, land managers, ornithologists, and conservation biologists. By associating environmental inputs with observed patterns of bird occurrence, predictive models have been developed that provide a statistical framework to harness available data for predicting species distributions and making inferences about species-habitat associations. Understanding these models, however, is challenging because they require scientists to quantify and compare multiscale spatialtemporal patterns. A large series of coordinated or sequential plots must be generated, individually programmed, and manually composed for analysis. This hampers the exploration and is a barrier to making the cross-species comparisons that are essential for coordinating conservation and extracting important ecological information. To address these limitations, as part of a collaboration among computer scientists, statisticians, biologists and ornithologists, we have developed BirdVis, an interactive visualization system that supports the analysis of spatio-temporal bird distribution models. BirdVis leverages visualization techniques and uses them in a novel way to better assist users in the exploration of interdependencies among model parameters. Furthermore, the system allows for comparative visualization through coordinated views, providing an intuitive interface to identify relevant correlations and patterns. We justify our design decisions and present case studies that show how BirdVis has helped scientists obtain new evidence for existing hypotheses, as well as formulate new hypotheses in their domain.     

Evolutionary mechanism design: a review

The advent of large-scale distributed systems poses unique engineering challenges. In open systems such as the internet it is not possible to prescribe the behaviour of all of the components of the system in advance. Rather, we attempt to design infrastructure, such as network protocols, in such a way that the overall system is robust despite the fact that numerous arbitrary, non-certified, third-party components can connect to our system. Economists have long understood this issue, since it is analogous to the design of the rules governing auctions and other marketplaces, in which we attempt to achieve socially-desirable outcomes despite the impossibility of prescribing the exact behaviour of the market participants, who may attempt to subvert the market for their own personal gain. This field is known as “mechanism design”: the science of designing rules of a game to achieve a specific outcome, even though each participant may be self-interested. Although it originated in economics, mechanism design has become an important foundation of multi-agent systems (MAS) research. In a traditional mechanism design problem, analytical methods are used to prove that agents’ game-theoretically optimal strategies lead to socially desirable outcomes. In many scenarios, traditional mechanism design and auction theory yield clear-cut results; however, there are many situations in which the underlying assumptions of the theory are violated due to the messiness of the real-world. In this paper we review alternative approaches to mechanism design which treat it as an engineering problem and bring to bear engineering design principles, viz.: iterative step-wise refinement of solutions, and satisficing instead of optimization in the face of intractable complexity. We categorize these approaches under the banner of evolutionary mechanism design.     

Cartoons beyond clipart: A computer tool for storyboarding and storywriting

This paper describes the motivation, proposal, and early prototype testing of a computer tool for story visualisation. An analysis of current software for making various types of visual story is made; this identifies a gap between software which emphasises preset banks of artwork, and software which emphasises low-level construction and/or drawing. A proposal is made to fill this gap, and a prototype implementation of the proposal is described in the context of a school-based study with England and Wales’s Year 5, covering ages 9–10 years. Results from this prototype study both validate the novel proposal made and demonstrate that children are capable of manipulating characters and notional camera angles in a more complex way than most current software permits.     

Modelling computational requirements of mobile robotic systems using zones and processing windows

Mobile robotic systems must sense constraints imposed by a dynamically changing environment and predictably react to those changes in real-time. Complexity arises in mobile robotic systems because the computing platform travels through the environment with which the system is interacting. These systems have spatio-temporal requirements in the sense that correct behavior is defined in terms of both space and time. The focus of this paper is mobile robotic platforms that must sense their environment and avoid obstacles as they navigate from one point to another. We present a design and analysis methodology for these platforms that integrates spatio-temporal attributes with fixed priority real-time scheduling through the use of zone and processing window abstractions.     

On the classification performance of TAN and general Bayesian networks

Over a decade ago, Friedman et al. introduced the Tree Augmented Naïve Bayes (TAN) classifier, with experiments indicating that it significantly outperformed Naïve Bayes (NB) in terms of classification accuracy, whereas general Bayesian network (GBN) classifiers performed no better than NB. This paper challenges those claims, using a careful experimental analysis to show that GBN classifiers significantly outperform NB on datasets analyzed, and are comparable to TAN performance. It is found that the poor performance reported by Friedman et al. are not attributable to the GBN per se, but rather to their use of simple empirical frequencies to estimate GBN parameters, whereas basic parameter smoothing (used in their TAN analyses but not their GBN analyses) improves GBN performance significantly. It is concluded that, while GBN classifiers may have some limitations, they deserve greater attention, particularly in domains where insight into classification decisions, as well as good accuracy, is required.     

DynaMICs: Comprehensive Support for Run-Time Monitoring

Software engineering strives to enable the economic construction of software systems that behave reliably, predictably, and safely. In other engineering disciplines, safety is assured in part by detailed monitoring of processes. In software, we may achieve some level of confidence in the operation of programs by monitoring their execution. DynaMICs is a software tool that facilitates the collection and use of constraints for software systems. In addition, it supports traceability by mapping constraints to system artifacts. Constraint specifications are stored separately from code; constraint-monitoring code is automatically generated from the specifications and inserted into the program at appropriate places; and constraints are verified at execution time. These constraint checks are triggered by changes made to variable values. We describe the architecture of DynaMICs, discuss alternative verification techniques, and outline research directions for the DynaMICs project.     

The Impact of Information Technology Investment on Enterprise Performance: A Case Study

Investment in information technology is steadily increasing, but many organizations find it difficult to formally assess the value of IT investments because the latter are often incorporated into broad management initiatives. the authors believe that the results of the research study reported on here can help firms to develop a better understanding of the dynamic relationship between IT investment and performance at both the firm and industry levels of analysis. This study clearly demonstrates the importance of adopting an organizational change perspective when assessing the impact of IT investment on firm performance.     

Molecular modeling optimization of anticoagulant pyridine derivatives

Intravascular clotting remains a major health problem in the United States, the most prominent being deep vein thrombosis, pulmonary embolism and thromboembolic stroke. Previous reports on the use of pyridine derivatives in cardiovascular drug development encourage us to pursue new types of compounds based on a pyridine scaffold. Eleven pyridine derivatives (oximes, semicarbazones, N-oxides) previously synthesized in our laboratories were tested as anticoagulants on pooled normal plasma using the prothrombin time (PT) protocol. The best anticoagulant within the oxime series was compound AF4, within the oxime N-oxide series was compound AF4-N-oxide, and within the semicarbazone series, compound MD1-30Y. We also used a molecular modeling approach to guide our efforts, and found that there was good correlation between coagulation data and computational energy scores. Molecular docking was performed to target the active site of thrombin with the DOCK v5.2 package. The results of molecular modeling indicate that improvement in anticoagulant activities can be expected by functionalization at the three-position of the pyridine ring and by N-oxide formation. Results reported here prove the suitability of DOCK in the lead optimization process.