Ion imprinted polymers for the selective extraction of silver(I) ions in aqueous media: Kinetic modeling and isotherm studies

Ion imprinted polymers (IIPs) for selective extraction of Ag(I) ions from aqueous solution were synthesized by a precipitation polymerization method using two functional monomers, 4-vinyl pyridine (4-VP) and 1-vinyl imidazole (1-VID), and N,N-ethylene bisacrylamide (EBAm) as the cross linker. Batch adsorption experiments were carried out as a function of Ag(I) imprinted polymer amount, agitation time, pH and initial Ag(I) concentration. The kinetic studies indicated that pseudo-second-order kinetic model best describes the adsorption behavior, while the adsorption data correlated well with the Langmuir isotherm. Furthermore the selectivity studies revealed that the ion imprinted polymers had a higher absorption capacity and a higher selectivity, for the Ag(I) ions, than the control polymers.     

Active Robust Resource Management in Cluster Computing Using Policies

We present an implementation of a policy-based management architecture for emerging communications and computing paradigms such as Active Networks and the Grid. To manage such open, highly distributed and decentralized environments, an approach based on policy concepts is adopted, allowing support for active, dynamic adaptability in network elements, services and end-user applications, as well as achieving decentralization and distribution. We present our flexible, extensible policy and event specifications in XML, and describe our management architecture. One key feature of our approach is the distributed infrastructure: the Directory and the Management Information Distribution system. The second feature is the Resource and Security Management elements residing on the multi-node managed systems. These combine to provide a light-weight, self-organizing management architecture. As an applications example, we describe the implementation of our management system applied to the Application Level Active Networking (ALAN) environment, implemented in the European Commission Information Society Technologies (IST) project ANDROID.     

Colour invariants under a non-linear photometric camera model and their application to face recognition from video

Illumination invariance remains one of the most researched, yet the most challenging aspect of automatic face recognition. In this paper the discriminative power of colour-based invariants is investigated in the presence of large illumination changes between training and query data, when appearance changes due to cast shadows and non-Lambertian effects are significant. Specifically, there are three main contributions: (i) a general photometric model of the camera is described and it is shown how its parameters can be estimated from realistic video input of pseudo-random head motion, (ii) several novel colour-based face invariants are derived for different special instances of the camera model, and (iii) the performance of the largest number of colour-based representations in the literature is evaluated and analysed on a database of 700 video sequences. The reported results suggest that: (i) colour invariants do have a substantial discriminative power which may increase the robustness and accuracy of recognition from low resolution images in extreme illuminations, and (ii) that the non-linearities of the general photometric camera model have a significant effect on recognition performance. This highlights the limitations of previous work and emphasizes the need to assess face recognition performance using training and query data which had been captured by different acquisition equipment.     

Discriminative extended canonical correlation analysis for pattern set matching

In this paper we address the problem of matching sets of vectors embedded in the same input space. We propose an approach which is motivated by canonical correlation analysis (CCA), a statistical technique which has proven successful in a wide variety of pattern recognition problems. Like CCA when applied to the matching of sets, our extended canonical correlation analysis (E-CCA) aims to extract the most similar modes of variability within two sets. Our first major contribution is the formulation of a principled framework for robust inference of such modes from data in the presence of uncertainty associated with noise and sampling randomness. E-CCA retains the efficiency and closed form computability of CCA, but unlike it, does not possess free parameters which cannot be inferred directly from data (inherent data dimensionality, and the number of canonical correlations used for set similarity computation). Our second major contribution is to show that in contrast to CCA, E-CCA is readily adapted to match sets in a discriminative learning scheme which we call discriminative extended canonical correlation analysis (DE-CCA). Theoretical contributions of this paper are followed by an empirical evaluation of its premises on the task of face recognition from sets of rasterized appearance images. The results demonstrate that our approach, E-CCA, already outperforms both CCA and its quasi-discriminative counterpart constrained CCA (C-CCA), for all values of their free parameters. An even greater improvement is achieved with the discriminative variant, DE-CCA.     

Hierarchical On-line Appearance-Based Tracking for 3D head pose,eyebrows, lips,eyelids and irises

In this paper, we propose an On-line Appearance-Based Tracker (OABT) for simultaneous tracking of 3D head pose, lips, eyebrows, eyelids and irises in monocular video sequences. In contrast to previously proposed tracking approaches, which deal with face and gaze tracking separately, our OABT can also be used for eyelid and iris tracking, as well as 3D head pose, lips and eyebrows facial actions tracking. Furthermore, our approach applies an on-line learning of changes in the appearance of the tracked target. Hence, the prior training of appearance models, which usually requires a large amount of labeled facial images, is avoided. Moreover, the proposed method is built upon a hierarchical combination of three OABTs, which are optimized using a Levenberg–Marquardt Algorithm (LMA) enhanced with line-search procedures. This, in turn, makes the proposed method robust to changes in lighting conditions, occlusions and translucent textures, as evidenced by our experiments. Finally, the proposed method achieves head and facial actions tracking in real-time.     

Going deeper in hidden sadness recognition using spontaneous micro expressions database

Multimedia Tools and Applications - Recognition of facial micro-expressions (MEs), which indicates conscious or unconscious suppressing of true emotions, is still a challenging task in the...     

Application level active network (alan) server management architecture

This paper presents the details of the policy-based security and resource management architecture for Application Level Active Network (alan) servers.alan is an active network architecture which enables deployment of user-customised processes (proxylets), which enhance the existing services or introduce new services to the end-user, on the select group of servers in anip network. The issues of security and resource management in this scenario are of crucial importance so as to efficiently facilitate and control the resource consumption of user-specified processes on the active servers, as well as to protect the server platforms from unauthorised proxylet deployment or malevolent behaviour. The architecture allowing efficient resource and security control is presented in this paper, including detaileduml diagrams capturing the management functionality, as well as a set of concrete management policies for thealan scenario. The examplexml policies are also given, and the deployment of this architecture in real-life trials is described. This development forms a part of a larger management architecture foralan-enabled networks developed in the context of theist projectandroid (Active Network DistRibuted Open Infrastructure Development).     

Bubbles in solvent microextraction: the influence of intentionally introduced bubbles on extraction efficiency

Significant improvements to microdrop extractions of triazine pesticides are realized by the intentional incorporation of an air bubble into the solvent microdroplet used in this microextraction technique. The increase is attributed partly to greater droplet surface area resulting from the air bubble being incorporated into the solvent droplet as opposed to it sitting thereon and partly to thin film phenomena. The method is useful at nanogram/liter levels (LOD 0.002-0.012 μg/L, LOQ 0.007-0.039 μg/L), is precise (7-12% at 10 μg/L concentration level), and is validated against certified reference materials containing 0.5 and 5.0 μg/L analyte. It tolerates water and fruit juice as matrixes without serious matrix effects. This new development brings a simple, inexpensive, and efficient preconcentration technique to bear which rivals solid phase microextraction methods.