Forecasting occupancy in hospitality business with autoregressive time-series models does not intercept occasional impact of public events. Our goal was to find appropriate datasets and enrich existing predictive models to account for rare and explicable demand surges. The paper proposes processing framework: data source types and formats, and forecast algorithms based on natural language processing. The study shows that classical models using word collocations outperform state of the art deep neural networks. Also, the collocations that turn out to be important, occupy certain locations in a graph that represents the natural language. The findings may result in yet improved forecasts, leading to smarter offer pricing and, finally, increased competitiveness in hospitality business. They may also serve public interest in areas like parking management or public transport planning. INDEX TERMS Time series analysis, recurrent neural networks, regression analysis, natural language processing, predictive models.
The increasing energy demands of networks and networked devices represent a threat to the development of the Future Internet. In this respect, recent research projects were devoted to extending next generation networks, architectures and protocols in the green direction. This paper presents a complex demonstration network specifically designed to assess the viability and the real impact of green networking mechanisms on industrial prototypes. The demonstrator reproduces a complete wire-line network chain from the core devices to the subscriber terminals, integrating quite a few green mechanisms able to interoperate efficiently and achieve significant reductions in energy consumption. The experimental results and the ensuing impact analysis show how the aggregation of multiple devices with green capabilities can guarantee a satisfactory performance level, while also allowing huge energy savings
Conway's Law states that in successful software projects, the organizational structure of programmer teams corresponds to the architecture of the developed system. It means that, ideally, each developer team works on its software module, and only on that module. We propose an approach to assess the difference between code structure and organizational structure. It is based on agglomerative clustering of modules and developers, followed by the search for best possible mapping between the groups. We applied the approach to a number of popular open source projects. The results show that these projects hardly obey Conway's law, due to the scale-free nature of both types of deduced networks, i.e., of software modules and the developers.
Abstract. An idea of a global system for dynamic contracting data paths in the global IP network is presented. System scalability and efficiency is based on the current natural hierarchy of Internet providers. Architecture of the bandwidth market service accomplishing operation of such system is outlined. Benefits from dynamic provisioning of such dedicated paths with QoS guarantees are shown. Utilization of various technologies for this system is discussed.
The paper proposes a design procedure for the creation of a robust and effective hybrid algorithm, tailored to and capable of carrying out a given design optimisation task. In the course of algorithm creation, a small set of simple optimisation methods is chosen, out of which those performing best will constitute the hybrid algorithm. The simplicity of the method allows implementing ad-hoc modifications if unexpected adverse features of the optimisation problem are found. It is postulated to model a system that is smaller but conceptually equivalent, whose model is much simpler than the original one and can be used freely during algorithm construction. Successful operation of the proposed approach is presented in two case studies (power plant set-point optimisation and waveguide bend shape optimisation). The proposed methodology is intended to be used by those not having much knowledge of the system or modelling technology, but having the basic practice in optimisation. It is designed as a compromise between brute force optimisation and design optimisation preceded by a refined study of the underlying problem. Special attention is paid to cases where simulation failures (regardless of their nature) form big obstacles in the course of the optimisation process.
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