Abstract
Several concurrent applications running on a sensor network may cause a node to transmit packets at distinct periods, which increases the radio-switching rate and has significant impact in terms of the overall energy consumption. We propose to batch the transmissions together by defining a harmonizing period to align the transmissions from multiple applications at periodic boundaries. This harmonizing period is then leveraged to design a distributed protocol called Network-Harmonized Scheduling (NHS) that coordinates transmissions across nodes and provides real-time guarantees in a multi-hop network. © 2014 IEEE.

Abstract
In this paper, an optic disk (OD) localization method is proposed for the retinal images based on a novel patch filtering approach. The patch filtering has been performed sequentially based on clustering in two stages. In the first stage, the patches are selected exploiting an 'isotropic' measure based on the ratio of maximum and minimum eigenvalues of the moment matrix representing the structure tensor. In the second stage, the patch filtering is based on the saliency measure. Finally, the optic disk is located from the centroids of the selected patches. Promising results are obtained for the low-contrast pathological retinal images using STARE database providing high localization accuracy.

Abstract
The incredible appeals of smartphones and the unprecedented progress in the development of mobile and wireless networks in recent years have enabled ubiquitous availability of myriad media contents. Consequently, it has become problematic for mobile users to find relevant media items. However, context awareness has been proposed as a means to help mobile users find relevant media items anywhere and at any time. The contribution of this paper is the presentation of a context-aware media recommendation framework for smart devices (CAMR). CAMR supports the integration of context sensing, recognition, and inference, using classification algorithms, an ontology-based context model and user preferences to provide contextually relevant media items to smart device users. This paper describes CAMR and its components, and demonstrates its use to develop a context-aware mobile movie recommendation on Android smart devices. Experimental evaluations of the framework, via an experimental context-aware mobile recommendation application, confirm that the framework is effective, and that its power consumption is within acceptable range. © 2014 Springer International Publishing Switzerland.

Abstract

Abstract

Abstract
Disturbance Management is a major issue in process industries like the pulp and paper (P&P) case and is mostly performed in the execution/control level. That approach is confined to the amendment of plans sent by upper levels and can thus be problematic. This paper moves towards the integration of planning and control, starting from the planning's point of view. The application of Simulation-Optimization (S-O) allows considering uncertainty, but keeping a deterministic tractable optimization model. Indeed, it is the simulation model that incorporates more complex elements such as stochastic variables, as well as integrates (with more or less detail) the execution/control behaviour. In this work, we present a case study of a P&P mill, focusing on the two most critical production resources (the digester and the paper machine). The feedback obtained by simulating their interaction is used to adjust the slacks introduced in the intermediate tank. In this way, we are able to generate plans that are not only optimized concerning company's indicators, but also robust against disturbances.