Vocational training can bring significant benefits for people with disabilities (PwD), particularly in terms of self-esteem and autonomy. Nevertheless, only a small fraction of Brazilians with disabilities actually work, due to lack of... more
Vocational training can bring significant benefits for people with disabilities (PwD), particularly in terms of self-esteem and autonomy. Nevertheless, only a small fraction of Brazilians with disabilities actually work, due to lack of job qualifications. In this paper, we report on the early progress of an ongoing research agenda that investigates new educational and social engagement technologies to facilitate the qualification and inclusion of PwD in the Brazilian labor market. Based on our experiences working with multiple disability populations in a series of exploratory studies, we discuss relevant aspects to be considered in the design and implementation of a vocational training platform targeted at PwD.
Research Interests:
ABSTRACT The growth in the adoption of cloud computing is driven by distinct and clear benefits for both cloud customers and cloud providers. However, the increase in the number of cloud providers as well as in the variety of offerings... more
ABSTRACT The growth in the adoption of cloud computing is driven by distinct and clear benefits for both cloud customers and cloud providers. However, the increase in the number of cloud providers as well as in the variety of offerings from each provider has made it harder for customers to choose. At the same time, the number of options to build a cloud infrastructure, from cloud management platforms to different interconnection and storage technologies, also poses a challenge for cloud providers. In this context, cloud experiments are as necessary as they are labor intensive. Cloud Bench [1] is an open-source framework that automates cloud-scale evaluation and benchmarking through the running of controlled experiments, where complex applications are automatically deployed. Experiments are described through experiment plans, containing directives with enough descriptive power to make the experiment descriptions brief while allowing for customizable multi-parameter variation. Experiments can be executed in multiple clouds using a single interface. Cloud Bench is capable of managing experiments spread across multiple regions and for long periods of time. The modular approach adopted allows it to be easily extended to accommodate new cloud infrastructure APIs and benchmark applications, directly by external users. A built-in data collection system collects, aggregates and stores metrics for cloud management activities (such as VM provisioning and VM image capture) and application runtime information. Experiments can be conducted in a highly controllable fashion, in order to assess the stability, scalability and reliability of multiple cloud configurations. We demonstrate Cloud Bench's main characteristics through the evaluation of an Open Stack installation, including experiments with approximately 1200 simultaneous VMs at an arrival rate of up to 400 VMs/hour.