Participants Kai Niu, MS, Madison, WI (Presenter) Nothing to Disclose Pengfei Yang, Shanghai, China (Abstract Co-Author) Nothing to Disclose Beverly A. Kienitz, MD, DDS, Madison, WI (Abstract Co-Author) Nothing to Disclose Ke Li, PhD, Madison, WI (Abstract Co-Author) Nothing to Disclose Sebastian Schafer, Madison, WI (Abstract Co-Author) Consultant, Siemens AG Kevin Royalty, PhD,MBA, Hoffman Es...

Department of Biochemistry, University of Wisconsin–Madison, Madison, WI 53706, USA 6 Morgridge Institute for Research, Madison, WI 53715, USA 7 Genome Center of Wisconsin, Madison, WI 53706, USA 8 Department of Chemistry, University of Wisconsin–Madison, Madison, WI 53706, USA 9 Department of Biomolecular Chemistry, University of Wisconsin–Madison, Madison, WI 53706, USA 10 Co-first author 11 ...

The growth in mobile data traffic is forcing network operators to find ways deliver higher bandwidth, better coverage, and quality of service (QoS) at lower development costs. One method that can be used meet this need the aggregation technique. Aggregation techniques run on several different technologies are called heterogeneous networks (HetNet). Recently, some advanced have been proposed agg...

Wi-Fi and Bluetooth Low Energy (BLE) are popular wireless communication techniques with the development of integrated combo chips, it is common these days that a single mobile/edge/IoT device supports both BLE. Given two have clearly different pros cons (e.g., high throughput vs. low power consumption), can experience significant performance improvement if link layers utilized adaptively accord...

In a population sample of 1462 middle-aged women socioeconomic data were studied in relation to obesity, assessed by a body weight index. Education, annual income, and social class were negatively correlated with weight index (WI). Husband's social class was a stronger determinant of obesity in the woman than her own class. Age of husband and number of children were significantly correlated wit...

can be interpreted as matching of an input graph (keyword) with a large set of graphs (document). More formally, in order to spot a certain keyword wi, all p graph instances gi1, ... , gip of that word wi occurring in the training set are matched against all graph words in each text line using our adapted graph matching procedure. That is, for a given word wi and a specific text line s pairwise...