The Linked Data Benchmark Council (LDBC) is now two years underway and has gathered strong industrial participation for its mission to establish benchmarks, and benchmarking practices for evaluating graph data management systems. The LDBC introduced a new choke-point driven methodology for developing benchmark workloads, which combines user input with input from expert systems architects, which we outline. This paper describes the LDBC Social Network Benchmark (SNB), and presents database benchmarking innovation in terms of graph query functionality tested, correlated graph generation techniques, as well as a scalable benchmark driver on a workload with complex graph dependencies. SNB has three query workloads under development: Interactive, Business Intelligence, and Graph Algorithms. We describe the SNB Interactive Workload in detail and illustrate the workload with some early results, as well as the goals for the two other workloads.

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Patient monitoring of vital signals such as breathing rhythm and heart beat rate can be done remotely by the use of a radar system. This approach is advantageous since it does not require any contact with the patient. Obviously contactless monitoring results in a more comfortable situation for the patient, and in occasions it is almost mandatory as in the case of heavy burnt or newborn patients. Moreover, additional information such movement patterns are also available. A 120 GHz FMCW radar is described with special focus on the design, construction and testing of a specific reflector antenna for the system. The system is based on a commercial radar chipset that includes its own antennas. The challenge has been to design the optimum reflector and to build it and test it in a cost effective way. The reflector has been 3D printed and a near-field testing technique has been implemented to assess its performance. The results show that the system is able to measure the vital signs at distances beyond one meter.