Intelligent evacuation management systems: A review

Crowd and evacuation management have been active areas of research and study in the recent past. Various developments continue to take place in the process of efficient evacuation of crowds in mass gatherings. This article is intended to provide a review of intelligent evacuation management systems covering the aspects of crowd monitoring, crowd disaster prediction, evacuation modelling, and evacuation path guidelines. Soft computing approaches play a vital role in the design and deployment of intelligent evacuation applications pertaining to crowd control management. While the review deals with video and nonvideo based aspects of crowd monitoring and crowd disaster prediction, evacuation techniques are reviewed via the theme of soft computing, along with a brief review on the evacuation navigation path. We believe that this review will assist researchers in developing reliable automated evacuation systems that will help in ensuring the safety of the evacuees especially during emergency evacuation scenarios

Wind Energy Forecasting at Different Time Horizons with Individual and Global Models

This paper has been presented at: 14th IFIP International Conference on Artificial Intelligence Applications and InnovationsIn this work two different machine learning approaches have been studied to predict wind power for different time horizons: individual and global models. The individual approach constructs a model for each horizon while the global approach obtains a single model that can be used for all horizons. Both approaches have advantages and disadvantages. Each individual model is trained with data pertaining to a single horizon, thus it can be specific for that horizon, but can use fewer data for training than the global model, which is constructed with data belonging to all horizons. Support Vector Machines have been used for constructing the individual and global models. This study has been tested on energy production data obtained from the Sotavento wind farm and meteorological data from the European Centre for Medium-Range Weather Forecasts, for a 5 × 5 grid around Sotavento. Also, given the large amount of variables involved, a feature selection algorithm (Sequential Forward Selection) has been used in order to improve the performance of the models. Experimental results show that the global model is more accurate than the individual ones, specially when feature selection is used.The authors acknowledge financial support granted by the Spanish Ministry of Science under contract ENE2014-56126-C2-2-R

Artificial intelligence for photovoltaic systems

Photovoltaic systems have gained an extraordinary popularity in the energy generation industry. Despite the benefits, photovoltaic systems still suffer from four main drawbacks, which include low conversion efficiency, intermittent power supply, high fabrication costs and the nonlinearity of the PV system output power. To overcome these issues, various optimization and control techniques have been proposed. However, many authors relied on classical techniques, which were based on intuitive, numerical or analytical methods. More efficient optimization strategies would enhance the performance of the PV systems and decrease the cost of the energy generated. In this chapter, we provide an overview of how Artificial Intelligence (AI) techniques can provide value to photovoltaic systems. Particular attention is devoted to three main areas: (1) Forecasting and modelling of meteorological data, (2) Basic modelling of solar cells and (3) Sizing of photovoltaic systems. This chapter will aim to provide a comparison between conventional techniques and the added benefits of using machine learning methods

Implementation and evaluation of a harm-reduction model for clinical care of substance using pregnant women

<p>Abstract</p> <p>Background</p> <p>Methamphetamine (MA) use during pregnancy is associated with many pregnancy complications, including preterm birth, small for gestational age, preeclampsia, and abruption. Hawaii has lead the nation in MA use for many years, yet prior to 2007, did not have a comprehensive plan to care for pregnant substance-using women. In 2006, the Hawaii State Legislature funded a pilot perinatal addiction clinic. The Perinatal Addiction Treatment Clinic of Hawaii was built on a harm-reduction model, encompassing perinatal care, transportation, child-care, social services, family planning, motivational incentives, and addiction medicine. We present the implementation model and results from our first one hundred three infants (103) seen over 3 years of operation of the program.</p> <p>Methods</p> <p>Referrals came from community health centers, hospitals, addiction treatment facilities, private physician offices, homeless outreach services and self-referral through word-of-mouth and bus ads. Data to describe sample characteristics and outcome was obtained prospectively and retrospectively from chart abstraction and delivery data. Drug use data was obtained from the women's self-report and random urine toxicology during the pregnancy, as well as urine toxicology at the time of birth on mothers, and urine and meconium toxicology on the infants. Post-partum depression was measured in mothers with the Edinburgh Post-Partum depression scale. Data from Path clinic patients were compared with a representative cohort of women delivering at Kapiolani Medical Center for Women and Children during the same time frame, who were enrolled in another study of pregnancy outcomes. Ethical approval for this study was obtained through the University of Hawaii Committee for Human Studies.</p> <p>Results</p> <p>Between April 2007 and August 2010, 213 women with a past or present history of addiction were seen, 132 were pregnant and 97 delivered during that time. 103 live-born infants were delivered. There were 3 first-trimester Spontaneous Abortions, two 28-week intrauterine fetal deaths, and two sets of twins and 4 repeat pregnancies. Over 50% of the women had lost custody of previous children due to substance use. The majority of women who delivered used methamphetamine (86%), either in the year before pregnancy or during pregnancy. Other drugs include marijuana (59.8%), cocaine (33%), opiates (9.6%), and alcohol (15.2%). Of the women served, 85% smoked cigarettes upon enrollment. Of the 97 women delivered during this period, all but 4 (96%) had negative urine toxicology at the time of delivery. Of the 103 infants, 13 (12.6%) were born preterm, equal to the state and national average, despite having many risk factors for prematurity, including poverty, poor diet, smoking and polysubstance use. Overwhelmingly, the women are parenting their children, > 90% retained custody at 8 weeks. Long-term follow-up showed that women who maintained custody chose long-acting contraceptive methods; while those who lost custody had a very high (> 50%) repeat pregnancy rate at 9 months post delivery.</p> <p>Conclusion</p> <p>Methamphetamine use during pregnancy doesn't exist is isolation. It is often combined with a multitude of other adverse circumstances, including poverty, interpersonal violence, psychiatric comorbidity, polysubstance use, nutritional deficiencies, inadequate health care and stressful life experiences. A comprehensive harm reduction model of perinatal care, which aims to ameliorate some of these difficulties for substance-using women without mandating abstinence, provides exceptional birth outcomes and can be implemented with limited resources.</p

Smoke-free legislation and child health

In this paper, we aim to present an overview of the scientific literature on the link between smoke-free legislation and early-life health outcomes. Exposure to second-hand smoke is responsible for an estimated 166 ,000 child deaths each year worldwide. To protect people from tobacco smoke, the World Health Organization recommends the implementation of comprehensive smoke-free legislation that prohibits smoking in all public indoor spaces, including workplaces, bars and restaurants. The implementation of such legislation has been found to reduce tobacco smoke exposure, encourage people to quit smoking and improve adult health outcomes. There is an increasing body of evidence that shows that children also experience health benefits after implementation of smoke-free legislation. In addition to protecting children from tobacco smoke in public, the link between smoke-free legislation and improved child health is likely to be mediated via a decline in smoking during pregnancy and reduced exposure in the home environment. Recent studies have found that the implementation of smoke-free legislation is associated with a substantial decrease in the number of perinatal deaths, preterm births and hospital attendance for respiratory tract infections and asthma in children, although such benefits are not found in each study. With over 80% of the world’s population currently unprotected by comprehensive smoke-free laws, protecting (unborn) children from the adverse impact of tobacco smoking and SHS exposure holds great potential to benefit public health and should therefore be a key priority for policymakers and health workers alike

Tobacco control policies and perinatal health:A national quasi-experimental study

We investigated whether changes in perinatal outcomes occurred following introduction of key tobacco control policies in the Netherlands: smoke-free legislation in workplaces plus a tobacco tax increase and mass media campaign (January-February 2004); and extension of the smoke-free law to the hospitality industry, accompanied by another tax increase and mass media campaign (July 2008). This was a national quasi-experimental study using Netherlands Perinatal Registry data (2000-2011; registration: ClinicalTrials.gov NCT02189265). Primary outcome measures were: perinatal mortality, preterm birth, and being small-for-gestational age (SGA). The association with timing of the tobacco control policies was investigated using interrupted time series logistic regression analyses with adjustment for confounders. Among 2,069,695 singleton births, there were 13,027 (0.6%) perinatal deaths, 116,043 (5.6%) preterm live-births and 187,966 (9.1%) SGA live-births. The 2004 policies were not associated with significant changes in the odds of developing any of the primary outcomes. After the 2008 policy change, a -4.4% (95% CI -2.4; -6.4, p < 0.001) decrease in odds of being SGA was observed. A reduction in SGA births, but not preterm birth or perinatal mortality, was observed in the Netherlands after extension of the smoke-free workplace law to bars and restaurants in conjunction with a tax increase and mass media campaign

Impact of smoke-free legislation on perinatal and infant mortality:a national quasi-experimental study

Smoke-free legislation is associated with improved early-life outcomes; however its impact on perinatal survival is unclear. We linked individual-level data with death certificates for all registered singletons births in England (1995-2011). We used interrupted time series logistic regression analysis to study changes in key adverse perinatal events following the July 2007 national, comprehensive smoke-free legislation. We studied 52,163 stillbirths and 10,238,950 live-births. Smoke-free legislation was associated with an immediate 7.8% (95%CI 3.5-11.8; p < 0.001) reduction in stillbirth, a 3.9% (95%CI 2.6-5.1; p < 0.001) reduction in low birth weight, and a 7.6% (95%CI 3.4-11.7; p = 0.001) reduction in neonatal mortality. No significant impact on SIDS was observed. Using a counterfactual scenario, we estimated that in the first four years following smoke-free legislation, 991 stillbirths, 5,470 cases of low birth weight, and 430 neonatal deaths were prevented. In conclusion, smoke-free legislation in England was associated with clinically important reductions in severe adverse perinatal outcomes