Empowering students to become socially responsible professionals is a desirable result of computing education. Humanitarian Free and Open Source Software (HFOSS) projects provide an opportunity for computing educators to inspire their students to tackle global humanitarian challenges while also learning about software engineering.
Deep learning can enable Internet of Things (IoT) devices to interpret unstructured multimedia data and intelligently react to both user and environmental events but has demanding performance and power requirements. The authors explore two ways to successfully integrate deep learning with low-power IoT products.
A hybrid learning framework uses a collective anomaly to analyze patterns in denial-of-service attacks along with data clustering to distinguish an attack from normal network traffic. In two evaluation datasets, the framework achieved higher hit rates relative to existing anomaly-detection techniques. Mohiuddin Ahmed, "Thwarting DoS Attacks: A Framework for Detection based on Collective Anomalies and Clustering", Computer, vol.
To maintain Moore's law, the semiconductor industry decided a decade ago that a new transistor was imperative. That silver bullet has yet to materialize, but computer design innovations are now maintaining or even exceeding expected scaling progress. This theme issue gives a cross-sectional view of these new scaling drivers.
Recent advances in deep learning for image recognition have spawned numerous challenge-based learning competitions in which participants can use a low-cost GPU graphics card to accomplish goals that required expensive resources in the recent past. Students are encouraged to explore this exciting new field of research by entering these competitions. Scooter Willis, "Stand on the Shoulders of Giants", Computer, vol.