A Survey on Graphical Methods for Classification Predictive Performance Evaluation

Predictive performance evaluation is a fundamental issue in design, development, and deployment of classification systems. As predictive performance evaluation is a multidimensional problem, single scalar summaries such as error rate, although quite convenient due to its simplicity, can seldom evaluate all the aspects that a complete and reliable evaluation must consider. Due to this, various graphical performance evaluation methods are increasingly drawing the attention of machine learning, data mining, and pattern recognition communities. The main advantage of these types of methods resides in their ability to depict the trade-offs between evaluation aspects in a multidimensional space rather than reducing these aspects to an arbitrarily chosen (and often biased) single scalar measure. Furthermore, to appropriately select a suitable graphical method for a given task, it is crucial to identify its strengths and weaknesses. This paper surveys various graphical methods often used for predictive performance evaluation. By presenting these methods in the same framework, we hope this paper may shed some light on deciding which methods are more suitable to use in different situations.

Observations on the feeding habits of Lutzomyia longipalpis (Lutz & Neiva, 1912) (Diptera: Psychodidae: Phlebotominae) in Campo Grande, an endemic area of visceral leishmaniasis in Mato Grosso do Sul, Brazil

Sand flies were captured weekly with CDC light traps from December 2003 to November 2005 in three areas of Campo Grande, in the Brazilian state of Mato Grosso do Sul. These areas incorporated two patches of remnant forest and five houses. The blood meals of engorged female sand flies were identified using the avidin-biotin system of immunoenzymatic ELISA capture. Most (327/355) of the females analysed were Lutzomyia longipalpis, of which 66.4% reacted with human blood, 64.8% with that of birds and 8.9% with that of dogs. Females that had taken human blood predominated in the residential areas and two forest patches. The following combinations of blood were also detected for L. longipalpis in some of the samples analysed: bird + human (43.4%), bird + human + dog (6.1%). The combination bird + human + dog + pig was also found for Nyssomyia whitmani. Dogs and pigs appear to have little attractiveness for L. longipalpis. The results obtained demonstrate the eclecticism and high anthropophily of L. longipalpis and raise new questions with regard to the importance of dogs in VL epidemiology and the possible role of man as a source of infection for sand flies. (C) 2008 Elsevier B.V. All rights reserved.

Chemical Communication in the Gregarious Psocid Cerastipsocus sivorii (Psocoptera: Psocidae)

The objectives of this study were: (1) to test the existence of an aggregation pheromone in the gregarious psocid Cerastipsocus sivorii; (2) to compare the attractiveness of odors from different aggregations; (3) to test whether nymphs are able to chemically recognize damage-released alarm signals. In a choice experiment conducted in the laboratory, we showed that psocids are able to detect chemical cues from groups of conspecifics. Laboratory experiments also showed that nymphs are capable of chemically recognizing the aggregations where they came from. Finally, in a field experiment, most aggregations dispersed when exposed to the body fluids of a crushed conspecific, but no aggregations dispersed upon exposure to a crushed termite. The implications of these results for the evolution of sociality in psocopterans are discussed.

Scalable model-based configuration management of security services in complex enterprise networks

Security administrators face the challenge of designing, deploying and maintaining a variety of configuration files related to security systems, especially in large-scale networks. These files have heterogeneous syntaxes and follow differing semantic concepts. Nevertheless, they are interdependent due to security services having to cooperate and their configuration to be consistent with each other, so that global security policies are completely and correctly enforced. To tackle this problem, our approach supports a comfortable definition of an abstract high-level security policy and provides an automated derivation of the desired configuration files. It is an extension of policy-based management and policy hierarchies, combining model-based management (MBM) with system modularization. MBM employs an object-oriented model of the managed system to obtain the details needed for automated policy refinement. The modularization into abstract subsystems (ASs) segment the system-and the model-into units which more closely encapsulate related system components and provide focused abstract views. As a result, scalability is achieved and even comprehensive IT systems can be modelled in a unified manner. The associated tool MoBaSeC (Model-Based-Service-Configuration) supports interactive graphical modelling, automated model analysis and policy refinement with the derivation of configuration files. We describe the MBM and AS approaches, outline the tool functions and exemplify their applications and results obtained. Copyright (C) 2010 John Wiley & Sons, Ltd.

Upgrading a TCABR data analysis and acquisition system for remote participation using Java, XML, RCP and modern client/server communication/authentication

The TCABR data analysis and acquisition system has been upgraded to support a joint research programme using remote participation technologies. The architecture of the new system uses Java language as programming environment. Since application parameters and hardware in a joint experiment are complex with a large variability of components, requirements and specification solutions need to be flexible and modular, independent from operating system and computer architecture. To describe and organize the information on all the components and the connections among them, systems are developed using the extensible Markup Language (XML) technology. The communication between clients and servers uses remote procedure call (RPC) based on the XML (RPC-XML technology). The integration among Java language, XML and RPC-XML technologies allows to develop easily a standard data and communication access layer between users and laboratories using common software libraries and Web application. The libraries allow data retrieval using the same methods for all user laboratories in the joint collaboration, and the Web application allows a simple graphical user interface (GUI) access. The TCABR tokamak team in collaboration with the IPFN (Instituto de Plasmas e Fusao Nuclear, Instituto Superior Tecnico, Universidade Tecnica de Lisboa) is implementing this remote participation technologies. The first version was tested at the Joint Experiment on TCABR (TCABRJE), a Host Laboratory Experiment, organized in cooperation with the IAEA (International Atomic Energy Agency) in the framework of the IAEA Coordinated Research Project (CRP) on ""Joint Research Using Small Tokamaks"". (C) 2010 Elsevier B.V. All rights reserved.

The decline of the world`s energy intensity

Energy intensity of the total primary energy supply (TPES), total final energy consumption (TFC) and LOSSES in the conversion from TPES to TFC were analyzed for the World, OECD and Rest of the World (ROW) countries. LOSSES increased significantly for all groups of countries due to the increase of electricity production from coal in the period studied (1971-2008). Electricity share final consumption almost doubled, increasing from 8.8% to 17.2% in the period studied. However the energy intensity of LOSSES remained practically constant, which reflects the fact that the efficiency of electricity generation from coal (the main source of electricity) remained practically constant in that period. Despite the attractiveness of end-use devices running on electricity such as computers, which is typical of modern societies, the CO(2) emissions are bound to increase unless coal is replaced by less carbon emitting sources such as natural gas, renewables and nuclear energy. (C) 2011 Elsevier Ltd. All rights reserved.

A multi-GPU algorithm for large-scale neuronal networks

Large-scale simulations of parts of the brain using detailed neuronal models to improve our understanding of brain functions are becoming a reality with the usage of supercomputers and large clusters. However, the high acquisition and maintenance cost of these computers, including the physical space, air conditioning, and electrical power, limits the number of simulations of this kind that scientists can perform. Modern commodity graphical cards, based on the CUDA platform, contain graphical processing units (GPUs) composed of hundreds of processors that can simultaneously execute thousands of threads and thus constitute a low-cost solution for many high-performance computing applications. In this work, we present a CUDA algorithm that enables the execution, on multiple GPUs, of simulations of large-scale networks composed of biologically realistic Hodgkin-Huxley neurons. The algorithm represents each neuron as a CUDA thread, which solves the set of coupled differential equations that model each neuron. Communication among neurons located in different GPUs is coordinated by the CPU. We obtained speedups of 40 for the simulation of 200k neurons that received random external input and speedups of 9 for a network with 200k neurons and 20M neuronal connections, in a single computer with two graphic boards with two GPUs each, when compared with a modern quad-core CPU. Copyright (C) 2010 John Wiley & Sons, Ltd.

Hypothesis testing in an errors-in-variables model with heteroscedastic measurement errors

In many epidemiological studies it is common to resort to regression models relating incidence of a disease and its risk factors. The main goal of this paper is to consider inference on such models with error-prone observations and variances of the measurement errors changing across observations. We suppose that the observations follow a bivariate normal distribution and the measurement errors are normally distributed. Aggregate data allow the estimation of the error variances. Maximum likelihood estimates are computed numerically via the EM algorithm. Consistent estimation of the asymptotic variance of the maximum likelihood estimators is also discussed. Test statistics are proposed for testing hypotheses of interest. Further, we implement a simple graphical device that enables an assessment of the model`s goodness of fit. Results of simulations concerning the properties of the test statistics are reported. The approach is illustrated with data from the WHO MONICA Project on cardiovascular disease. Copyright (C) 2008 John Wiley & Sons, Ltd.