Temporal changes in Aqu/C60 physical-chemical, deposition, and transport characteristics in aqueous systems

Little is known about how temporal changes in the physical-chemical properties of C?? aggregates formed in aqueous systems (termed aqu/C??) can impact transport pathways contributing to ecological exposures. In this study three aqu/C?? suspensions of short-term (100 days), intermediate-term (300 days), and long-term (1000 days) water exposure were first characterized for particle size distribution, water/toluene phase distribution, and surface chemistry. Then, aqu/C?? deposition to a model silica surface and transport in porous media were studied by quartz crystal microbalance (QCM) and saturated sand columns. As suspension time increased, aqu/C?? particle size shifted to a larger size range as determined by asymmetric flow field-flow fractionation (AF4) and the aqu/C?? distribution to toluene was reduced, likely due to surface polarization as revealed by nuclear magnetic resonance (NMR) and UV-visible spectroscopy of the aqu/C?? suspensions. Additionally, the deposition to silica surfaces in both QCM and column studies decreased with increased water exposure time. Although a small increase in aqu/C?? aggregate size with time may partially explain the greater transport of the long-term aqu/C?? because of the decreased collector efficiency for larger submicrometer particles, the polarization of the aqu/C?? (thus a more hydrophilic surface) revealed by the toluene/water phase distribution and confirmed by NMR, is considered the determining factor.     

Accurate Trilateration for Passive RFID Localization in Smart Homes

The smart home as emerged in recent years as a new trend of research aiming to propose an alternative to postpone the institutionalization of cognitively-impaired people. These habitats are intended to provide security, guidance and direct support services to its resident. To fulfill this important mission, an algorithm first has to identify the ongoing activities of its user by tracking, in real time, the position of the main daily living objects. Many researchers addressed this issue by proposing systems based ultrasonic wave sensors, video cameras, and radio-frequency identification (RFID). However, the RFID technology, constitutes the most viable technology for smart homes. Recently, several RFID localization algorithms have been developed, mainly for commercial and industrial uses, but they are not precise enough to be used in an assistive context. Furthermore, the majority of them focuses on systems exploiting active RFID tags, which need batteries and are much more expensive. We present, in this paper, a new algorithmic approach for passive RFID localization in smart homes based on elliptical trilateration and fuzzy logic. This new algorithm has been implemented in a real smart home infrastructure. It has been rigorously tested and outperformed the comparable approaches.     

Searching for optimal integer solutions to set partitioning problems using column generation

In this paper, we describe a new approach to increase the possibility of finding integer feasible columns to a set partitioning problem (SPP) directly in solving the linear programming (LP) relaxation using column generation. Traditionally, column generation is aimed to solve the LP‐relaxation as quickly as possible without any concern for the integer properties of the columns formed. In our approach, we aim to generate columns forming an optimal integer solution while simultaneously solving the LP‐relaxation. Using this approach, we can improve the possibility of finding integer solutions by heuristics at each node in the branch‐and‐bound search. In addition, we improve the possibility of finding high‐quality integer solutions in cases where only the columns in the root node are used to solve the problem. The basis of our approach is a subgradient technique applied to a Lagrangian dual formulation of the SPP extended with an additional surrogate constraint. This extra constraint is not relaxed and is used to better control the subgradient evaluations and how the multiplier values are computed. The column generation is then directed, via the multipliers, to construct columns that form feasible integer solutions. Computational experiments show that we can generate optimal integer columns in a large set of well‐known test problems as compared to both standard and stabilized column generation, and simultaneously keep the number of columns smaller than standard column generation. This is also supported by tests on a case study with work‐shift generation.