Abstract
This paper presents a PhD thesis proposal in Informatics Engineering, scheduled for completion in July 2018. This PhD thesis is part of Spatio-Temporal Information Systems, with applicability in technological communication tools and visual representation of knowledge, for Digital Media (newspapers, radio and television). It is intended to maximize the efficiency and effectiveness of the value of heterogeneous, multivariate, multidimensional information characteristic of this context, produced and shared by different sources, in different formats. It is hoped that participation in this Doctoral Symposium will enrich and update the work in progress and help the preparation of the PhD thesis proposal.

Abstract
Here we propose a simplified model for the path planning of an Autonomous Underwater Vehicle (AUV) in an horizontal plane when ocean currents are considered. The model includes kinematic equations and a simple dynamic equation. Our problem of interest is a minimum time problem with state constraints where the control appears linearly. This problem is solved numerically using the direct method. We extract various tests from the Maximum Principle that are then used to validate the numerical solution. In contrast to many other literature we apply the Maximum Principle as defined in [9].

Abstract
We develop a general framework for compressive linear-projection measurements with side information. Side information is an additional signal correlated with the signal of interest. We investigate the impact of side information on classification and signal recovery from low-dimensional measurements. Motivated by real applications, two special cases of the general model are studied. In the first, a joint Gaussian mixture model is manifested on the signal and side information. The second example again employs a Gaussian mixture model for the signal, with side information drawn from a mixture in the exponential family. Theoretical results on recovery and classification accuracy are derived. The presence of side information is shown to yield improved performance, both theoretically and experimentally. © 2016 IEEE.

Abstract

Abstract
With increasing environmental concerns, the electrification of transportation plays an outstanding role in the sustainable development. In this context, plug-in electric vehicle (PEV) and demand response have indispensable impacts on the future smart grid. Since integration of PEVs into the grid is a key element to achieve sustainable energy systems, this paper presents the optimal behavior of PEV parking lots in the energy and reserve markets. To this end, a model is developed to derive optimal strategies of parking lots, as responsive demands, in both price-based and incentive-based demand response programs (DRPs). The proposed model reflects the impacts of different DRPs on the operational behavior of parking lots and optimizes the participation level of parking lots in each DRP. Uncertainties of PEVs and electricity market are also considered by using a stochastic programming approach. Numerical studies indicate that the PEV parking lots can benefit from the selective participation in DRPs.

Abstract
Interference is a fundamental issue in wireless mesh networks (WMNs) and it seriously affects the network performance. In this paper we characterize the power interference in IEEE 802.11 CSMA/CA based wireless mesh networks using directional antennas. A model based centralized call admission control (CAC) scheme is proposed which uses physical collision constraints, and transmitter-side, receiver-side and when-idle protocol collision prevention constraints. The CAC assists to manage requests from users depending on the available bandwidth in the network: when a new virtual link establishment request from a user is accepted into the network, resources such as interface, bandwidth, transmission power and channel are allocated in the participating nodes and released once the session is completed. The proposed CAC is also able to contain the interference in the WMN by managing the transmission power of nodes.