Human falls are a global public health issue resulting in over 37.3 million severe injuries and 646,000 deaths yearly. Falls result direct financial cost to systems indirectly society productivity. Unsurprisingly, human fall detection prevention major focus of research. In this article, we consider deep learning for an IoT fog computing environment. We propose Convolutional Neural Network composed three convolutional layers, two maxpool, fully-connected layers as our model. evaluate its...

In a cloud computing environment, dynamic resource allocation and reallocation are keys for accommodating unpredictable demands and, ultimately, contribute to investment return. This article discusses this process in the context of distributed clouds, which seen as systems where application developers can selectively lease geographically resources. highlights categorizes main challenges inherent particular offering stepwise view that covers initial modeling phase through optimization phase.

The fourth industrial revolution heralds a paradigm shift in how people, processes, things, data and networks communicate connect with each other. Conventional computing infrastructures are struggling to satisfy dramatic growth demand from deluge of connected heterogeneous end points located at the edge while, same time, meeting quality service levels. complexity makes it increasingly difficult for infrastructure providers plan provision resources meet this demand. While simulation...

Cloud Computing has been used by different types of clients because it many advantages, including the minimization infrastructure resources costs, and its elasticity property, which allows services to be scaled up or down according current demand. From provider point-of-view, there are challenges overcome in order deliver that meet all requirements defined Service Level Agreements (SLAs). High availability one biggest for providers, can improve a service, such as checkpointing, load...

The Internet of Things has the potential transforming health systems through collection and analysis patient physiological data via wearable devices sensor networks. Such can offer assisted living services in real-time a range multimedia-based services. However, service downtime, particularly case emergencies, lead to adverse outcomes worst case, death. In this paper, we propose an e-health monitoring architecture based on sensors that relies cloud fog infrastructures handle store data....

The world population's life expectancy has gradually increased. According to the World Health Organization (WHO), expectation will reach 90 years by 2030, and this quality of is one most important aging aspects. academic business communities are devoting many efforts develop new applications that promote for portion population; services, such as vital signs monitoring, fall detection systems, heart attacks, among others, increasingly in evidence. Most these e-health systems focused on...

Over 2.8 million people die each year from being overweight or obese, a largely preventable disease. Social media has fundamentally changed the way we communicate, collaborate, consume, and create content. The ease with which content can be shared resulted in rapid increase number of individuals organisations that seek to influence opinion volume they generate. nutrition diet domain is not immune this phenomenon. Unfortunately, public health perspective, many these ‘influencers’ may poorly...

Abstract One of the main categories Neglected Tropical Diseases (NTDs) are arboviruses, which Dengue and Chikungunya most common. Arboviruses mainly affect tropical countries. Brazil has largest absolute number cases in Latin America. This work presents a unified data set with clinical, sociodemographic, laboratorial on confirmed patients Chikungunya, as well ruled out infection from these diseases. The is based case notification submitted to Brazilian Information System for Notifiable...

Commercial buildings are a significant consumer of energy worldwide. Logistics facilities, and specifically warehouses, common building type which remain under-researched in the demand-side forecasting literature. Warehouses have an idiosyncratic profile when compared to other commercial industrial with reliance on small number systems. As such, warehouse owners operators increasingly entering performance contracts service companies (ESCOs) minimise environmental impact, reduce costs,...

Low birth weight (LBW) is a health condition that affects over 20 million gestational outcomes worldwide. The current literature indicates machine learning models have the potential to assist healthcare professionals in predicting LBW and giving them opportunity intervene earlier pregnancy, which might include adjusting medical treatments or suggesting changes diet. This study proposes evaluation of predict pregnant women are at risk neonatal with LBW. methodology involves six phases,...

Premature birth can be defined as before 37 weeks of gestation, which is a significant global health issue, being the main cause for neonatal deaths. In this work, we evaluate machine learning models predicting premature using Brazilian sociodemographic and obstetric data, focusing on challenge data imbalance, common problem that lead to biased predictions. We five balancing techniques: Undersampling, Oversampling, three Hybridsampling configurations where minority class was increased by...

With the popularization of cloud computing, several enterprises and open-source communities have developed their own solutions. A number factors weigh on user selection, as each one has peculiar characteristics may target different usage scenarios. Considering such challenge, this paper focuses giving reader an understanding some major existing open computing solutions – XCP, Eucalyptus Open Nebula. Hopefully, a deep comparison can leverage research area providing good starting point to...

In recent years, there has been significant advancement in resource management mechanisms for cloud computing infrastructure performance terms of cost, quality service (QoS) and energy consumption. The emergence the Internet Things led to development that extends beyond centralised data centers from edge, so-called cloud-to-thing continuum (C2T). This is characterised by extreme heterogeneity, geographic distribution, complexity, where key indicators (KPIs) traditional model may no longer...

COVID-19 is a pandemic characterized by uncertainty not only in transmission and pathogenicity, but also disease-specific control options. Despite many governmental measures, the disease spreading countries, public health system close to be collapsed. Alternative techniques should taken order minimize negative impacts on society. This work presents preliminary results of deep learning models classify positive based X-ray images. We provide binary classification (COVID-19 vs healhty,...

Distributed Clouds, or just D-Clouds, can be seen as a paradigm that is able to exploit the potential of sharing resources across geographic boundaries and provide latency-bound allocation third-party developers. The representation D-Cloud challenge involves careful choice characteristics drive mapping requests on substrate resources. Regarding these problems, this paper introduces Cloud Modeling Language (CloudML), vendor-neutral XML-based language intended integrate description different...

Guaranteeing high levels of availability is a huge challenge for cloud providers. The authors look at the causes failures and recommend ways to prevent them minimize their effects when they occur.