Downlink and Uplink Intelligent Reflecting Surface Aided Networks: NOMA and OMA

Intelligent reflecting surfaces (IRSs) are envisioned to provide reconfigurable wireless environments for future communication networks. In this paper, both downlink and uplink IRS-aided non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) networks are studied, in which an IRS is deployed to enhance the coverage by assisting a cell-edge user device (UD) to communicate with the base station (BS). To characterize system performance, new channel statistics of the BS-IRS-UD link with Nakagami-$m$ fading are investigated. For each scenario, the closed-form expressions for the outage probability and ergodic rate are derived. To gain further insight, the diversity order and high signal-to-noise ratio (SNR) slope for each scenario are obtained according to asymptotic approximations in the high-SNR regime. It is demonstrated that the diversity order is affected by the number of IRS reflecting elements and Nakagami fading parameters, but the high-SNR slope is not related to these parameters. Simulation results validate our analysis and reveal the superiority of the IRS over the full-duplex decode-and-forward relay.Comment: Accepted for publication in the IEEE Transactions on Wireless Communication

Traceable GISAXS measurements for pitch determination of a 25 nm self-assembled polymer grating

The feature sizes of only a few nanometers in modern nanotechnology and next-generation microelectronics continually increase the demand for suitable nanometrology tools. Grazing incidence small-angle X-ray scattering (GISAXS) is a versatile technique to measure lateral and vertical sizes in the nm-range, but the traceability of the obtained parameters, which is a prerequisite for any metrological measurement, has not been demonstrated so far. In this work, the first traceable GISAXS measurements, demonstrated with a self-assembled block copolymer grating structure with a nominal pitch of 25 nm, are reported. The different uncertainty contributions to the obtained pitch value of 24.83(9) nm are discussed individually. The main uncertainty contribution results from the sample-detector distance and the pixel size measurement, whereas the intrinsic asymmetry of the scattering features is of minor relevance for the investigated grating structure. The uncertainty analysis provides a basis for the evaluation of the uncertainty of GISAXS data in a more general context, for example in numerical data modeling.Comment: 9 pages, 6 figures; submitted to Journal of Applied Crystallograph

Identifying Destination Image of Rural Areas: The Case of Brookings, South Dakota

A clear understanding of destination image is crucial for developing effective marketing and positioning strategies. The purpose of the study is to examine the images of Brookings perceived by actual tourists. An online questionnaire was developed and sent to email subscribers of the largest local event center. A total of 344 valid responses were received. Overall tourists had positive perceptions of Brookings as a tourism destination. The study identified six Brookings’ image dimensions, including Outdoor Activities and Natural Scenery, Atmosphere, Tourism Infrastructure, Value for Money and Convenience, Historic Attractions, and College Town Style. The social and cultural environment is the most favored element in Brookings. As a college town, Brookings was differentiated from other rural tourism destinations. It is suggested that the city and the university work in partnership to increase visitation both to the campus and the community. To enhance Brookings’ image, destination marketers should focus on the low-rated image items and incorporate them in destination marketing materials

Cloud computing resource scheduling and a survey of its evolutionary approaches

A disruptive technology fundamentally transforming the way that computing services are delivered, cloud computing offers information and communication technology users a new dimension of convenience of resources, as services via the Internet. Because cloud provides a finite pool of virtualized on-demand resources, optimally scheduling them has become an essential and rewarding topic, where a trend of using Evolutionary Computation (EC) algorithms is emerging rapidly. Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources. It then paints a landscape of the scheduling problem and solutions. According to the taxonomy, a comprehensive survey of state-of-the-art approaches is presented systematically. Looking forward, challenges and potential future research directions are investigated and invited, including real-time scheduling, adaptive dynamic scheduling, large-scale scheduling, multiobjective scheduling, and distributed and parallel scheduling. At the dawn of Industry 4.0, cloud computing scheduling for cyber-physical integration with the presence of big data is also discussed. Research in this area is only in its infancy, but with the rapid fusion of information and data technology, more exciting and agenda-setting topics are likely to emerge on the horizon