Constraint-based Sequential Pattern Mining with Decision Diagrams

Constrained sequential pattern mining aims at identifying frequent patterns on a sequential database of items while observing constraints defined over the item attributes. We introduce novel techniques for constraint-based sequential pattern mining that rely on a multi-valued decision diagram representation of the database. Specifically, our representation can accommodate multiple item attributes and various constraint types, including a number of non-monotone constraints. To evaluate the applicability of our approach, we develop an MDD-based prefix-projection algorithm and compare its performance against a typical generate-and-check variant, as well as a state-of-the-art constraint-based sequential pattern mining algorithm. Results show that our approach is competitive with or superior to these other methods in terms of scalability and efficiency.Comment: AAAI201

Learning in planning with temporally extended goals and uncontrollable events

Recent contributions to advancing planning from the classical model to more realistic problems include using temporal logic such as LTL to express desired properties of a solution plan. This paper introduces a planning model that combines temporally extended goals and uncontrollable events. The planning task is to reach a state such that all event sequences generated from that state satisfy the problem's temporally extended goal. A real-life application that motivates this work is to use planning to configure a system in such a way that its subsequent, non-deterministic internal evolution (nominal behavior) is guaranteed to satisfy a condition expressed in temporal logic. A solving architecture is presented that combines planning, model checking and learning. An online learning process incrementally discovers information about the problem instance at hand. The learned information is useful both to guide the search in planning and to safely avoid unnecessary calls to the model checking module. A detailed experimental analysis of the approach presented in this paper is included. The new method for online learning is shown to greatly improve the system performance.NICTA is funded by the Australian Government’s Department of Communications, Information Technology, and the Arts and the Australian Research Council through Backing Australia’s Ability and the ICT Research Centre of Excellence program

Funiculars anomalies during childbirth: about 562 cases collected in Pikine National Hospital

Background: Establish an epidemiological description of the different types of umbilical cord anomalies in our reference structure and to assess their impact on the prognosis of childbirth.Methods: We conducted a descriptive study, cross over a period of one year in Obstetrics and Gynecology Service Level III of Pikine Hospital. We included all women in labor have reached the term less than 28 weeks gestation and delivering a newborn with umbilical cord abnormality diagnosed during labor or during the expulsion.Results: During this period, we compiled 562 anomalies of the umbilical cord, which gave a frequency of 23.8%. Length discrepancies were far the most frequent (67.4%). Only the prolapsed cord was an independent risk factor for cesarean section (p = 0.036). The rate of episiotomy and tear was significantly higher in case of brevity (primitive or induced) cord (p = 0.042). Apgar score ≤7 was significantly related to the presence of brevity (p = 0.000), excessive length (p = 0.048) or cord prolapse (p = 0.037).Conclusions: This study has allowed us to see that the funicular abnormalities impede the smooth running of childbirth. Their occurrence is facilitated by the excess amniotic fluid, prematurity and low birth weight. Their research during prenatal ultrasounds should be systematic

Time series analysis of dengue incidence in Guadeloupe, French West Indies: Forecasting models using climate variables as predictors

BACKGROUND: During the last decades, dengue viruses have spread throughout the Americas region, with an increase in the number of severe forms of dengue. The surveillance system in Guadeloupe (French West Indies) is currently operational for the detection of early outbreaks of dengue. The goal of the study was to improve this surveillance system by assessing a modelling tool to predict the occurrence of dengue epidemics few months ahead and thus to help an efficient dengue control. METHODS: The Box-Jenkins approach allowed us to fit a Seasonal Autoregressive Integrated Moving Average (SARIMA) model of dengue incidence from 2000 to 2006 using clinical suspected cases. Then, this model was used for calculating dengue incidence for the year 2007 compared with observed data, using three different approaches: 1 year-ahead, 3 months-ahead and 1 month-ahead. Finally, we assessed the impact of meteorological variables (rainfall, temperature and relative humidity) on the prediction of dengue incidence and outbreaks, incorporating them in the model fitting the best. RESULTS: The 3 months-ahead approach was the most appropriate for an effective and operational public health response, and the most accurate (Root Mean Square Error, RMSE = 0.85). Relative humidity at lag-7 weeks, minimum temperature at lag-5 weeks and average temperature at lag-11 weeks were variables the most positively correlated to dengue incidence in Guadeloupe, meanwhile rainfall was not. The predictive power of SARIMA models was enhanced by the inclusion of climatic variables as external regressors to forecast the year 2007. Temperature significantly affected the model for better dengue incidence forecasting (p-value = 0.03 for minimum temperature lag-5, p-value = 0.02 for average temperature lag-11) but not humidity. Minimum temperature at lag-5 weeks was the best climatic variable for predicting dengue outbreaks (RMSE = 0.72). CONCLUSION: Temperature improves dengue outbreaks forecasts better than humidity and rainfall. SARIMA models using climatic data as independent variables could be easily incorporated into an early (3 months-ahead) and reliably monitoring system of dengue outbreaks. This approach which is practicable for a surveillance system has public health implications in helping the prediction of dengue epidemic and therefore the timely appropriate and efficient implementation of prevention activities

Pyrethroid Resistance Reduces the Efficacy of Space Sprays for Dengue Control on the Island of Martinique (Caribbean)

The mosquito Aedes aegypti is the major vector of the Dengue virus in human populations and is responsible of serious outbreaks worldwide. In most countries, vector control is implemented by the use of insecticides to reduce mosquito populations. During epidemics, insecticides of the pyrethroid family (blocking the voltage gated sodium channel protein in the nerve sheath) are used by space spraying with vehicle mounted thermal foggers to kill adult mosquitoes. Unfortunately some populations of Ae. aegypti have become resistant to these insecticides, leading to operational challenges for public health services. In Martinique (French West Indies), resistance to pyrethroids was detected in the 1990s. The present study assessed the impact of this resistance on the efficacy of vector control operations in 9 localities of Martinique. Here we showed that the resistance strongly reduces the efficacy of pyrethroid-based treatments, thus emphasizing the urgent need for alternative insecticides or tools to reduce dengue transmission

BDD-based heuristics for binary optimization

In this paper we introduce a new method for generating heuristic solutions to binary optimization problems. We develop a technique based on binary decision diagrams. We use these structures to provide an under-approximation to the set of feasible solutions. We show that the proposed algorithm delivers comparable solutions to a state-of-the-art general-purpose optimization solver on randomly generated set covering and set packing problems

Overview of the Alliance for Cellular Signaling

The Alliance for Cellular Signaling is a large-scale collaboration designed to answer global questions about signalling networks. Pathways will be studied intensively in two cells-B lymphocytes (the cells of the immune system) and cardiac myocytes-to facilitate quantitative modelling. One goal is to catalyse complementary research in individual laboratories; to facilitate this, all alliance data are freely available for use by the entire research community.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62977/1/nature01304.pd