Pitfalls on computing liquid-liquid phase equilibria using the k-value method

Poster presented in the 11th Mediterranean Congress of Chemical Engineering, Barcelona, October 21-24, 2008.

A study of a soft computing based method for 3D scenario reconstruction

Several recent works deal with 3D data in mobile robotic problems, e.g., mapping. Data comes from any kind of sensor (time of flight, Kinect or 3D lasers) that provide a huge amount of unorganized 3D data. In this paper we detail an efficient approach to build complete 3D models using a soft computing method, the Growing Neural Gas (GNG). As neural models deal easily with noise, imprecision, uncertainty or partial data, GNG provides better results than other approaches. The GNG obtained is then applied to a sequence. We present a comprehensive study on GNG parameters to ensure the best result at the lowest time cost. From this GNG structure, we propose to calculate planar patches and thus obtaining a fast method to compute the movement performed by a mobile robot by means of a 3D models registration algorithm. Final results of 3D mapping are also shown.

A GIS-based methodology to quantitatively define an Adjacent Protected Area in a shallow karst cavity: The case of Altamira cave

Different types of land use are usually present in the areas adjacent to many shallow karst cavities. Over time, the increasing amount of potentially harmful matter and energy, of mainly anthropic origin or influence, that reaches the interior of a shallow karst cavity can modify the hypogeal ecosystem and increase the risk of damage to the Palaeolithic rock art often preserved within the cavity. This study proposes a new Protected Area status based on the geological processes that control these matter and energy fluxes into the Altamira cave karst system. Analysis of the geological characteristics of the shallow karst system shows that direct and lateral infiltration, internal water circulation, ventilation, gas exchange and transmission of vibrations are the processes that control these matter and energy fluxes into the cave. This study applies a comprehensive methodological approach based on Geographic Information Systems (GIS) to establish the area of influence of each transfer process. The stratigraphic and structural characteristics of the interior of the cave were determined using 3D Laser Scanning topography combined with classical field work, data gathering, cartography and a porosity–permeability analysis of host rock samples. As a result, it was possible to determine the hydrogeological behavior of the cave. In addition, by mapping and modeling the surface parameters it was possible to identify the main features restricting hydrological behavior and hence direct and lateral infiltration into the cave. These surface parameters included the shape of the drainage network and a geomorphological and structural characterization via digital terrain models. Geological and geomorphological maps and models integrated into the GIS environment defined the areas involved in gas exchange and ventilation processes. Likewise, areas that could potentially transmit vibrations directly into the cave were identified. This study shows that it is possible to define a Protected Area by quantifying the area of influence related to each transfer process. The combined maximum area of influence of all the processes will result in the new Protected Area. This area will thus encompass all the processes that account for most of the matter and energy carried into the cave and will fulfill the criteria used to define the Protected Area. This methodology is based on the spatial quantification of processes and entities of geological origin and can therefore be applied to any shallow karst system that requires protection.

Flexible Framework for Real-Time Embedded Systems Based on Mobile Cloud Computing Paradigm

The development of applications as well as the services for mobile systems faces a varied range of devices with very heterogeneous capabilities whose response times are difficult to predict. The research described in this work aims to respond to this issue by developing a computational model that formalizes the problem and that defines adjusting computing methods. The described proposal combines imprecise computing strategies with cloud computing paradigms in order to provide flexible implementation frameworks for embedded or mobile devices. As a result, the imprecise computation scheduling method on the workload of the embedded system is the solution to move computing to the cloud according to the priority and response time of the tasks to be executed and hereby be able to meet productivity and quality of desired services. A technique to estimate network delays and to schedule more accurately tasks is illustrated in this paper. An application example in which this technique is experimented in running contexts with heterogeneous work loading for checking the validity of the proposed model is described.

A Computational Method based on Radio Frequency Technologies for the Analysis of Accessibility of Disabled People in Sustainable Cities

The sustainability strategy in urban spaces arises from reflecting on how to achieve a more habitable city and is materialized in a series of sustainable transformations aimed at humanizing different environments so that they can be used and enjoyed by everyone without exception and regardless of their ability. Modern communication technologies allow new opportunities to analyze efficiency in the use of urban spaces from several points of view: adequacy of facilities, usability, and social integration capabilities. The research presented in this paper proposes a method to perform an analysis of movement accessibility in sustainable cities based on radio frequency technologies and the ubiquitous computing possibilities of the new Internet of Things paradigm. The proposal can be deployed in both indoor and outdoor environments to check specific locations of a city. Finally, a case study in a controlled context has been simulated to validate the proposal as a pre-deployment step in urban environments.

Denitrification Enzymes-Based Biosensors: the Case of Haloarchaeal Enzymes

In the last two decades, the increase in the use of artificial fertilizers and the disposal of industrial wastes have been the main factors responsible for the progressive increase in nitrate and nitrite levels in groundwater and soil. A variety of analytical strategies have been developed for nitrate and nitrite detection but electrochemical biosensors, which are simple, cheap, easily miniaturized and suitability for real-time detection, are proved to be a powerful tool. Various types of biosensors based on the use of whole cells or on the immobilization of denitrification enzymes have been developed, but their use is limited in environmental analysis under extreme conditions such as brines, acidic or basic wastewaters, salted soils, etc. Extremophilic denitrifying microorganism are good candidates for the development of new nitrate and nitrite biosensors and, in particular, haloarchaeal based biosensors would have advantages over bacterial based biosensors since the microorganisms and the purified denitrifying enzymes tolerate a wide range of temperature and salinity. This work summarizes new highlights on the potential uses of denitrifying haloarchaeal enzymes to make enzyme-based biosensors.