A new convolution approach for the time-delay identification of systems with arbitrary entries

In this paper, an online delay identification approach of continuous-time linear systems with unstructured entries is achieved via a new algebraic technique. The arbitrary input and output trajectories are chosen with close and abundant crossing zero. Initial conditions and static disturbances are taken into account in the design of the identification approach. The proposed method is based on a distributional algebraic technique and a convolution approach. A proposed theorem is hence enounced to identify a single time-delay of such systems. The effectiveness of the proposed approach is demonstrated by an illustrative example. The obtained results show the high performances of the proposed time-delay identification approach in severe operation conditions of the considered system.     

Isolation and characterisation of lactic acid bacteria strains from raw camel milk for potential use in the production of fermented Tunisian dairy products

The aim of this work was to study the suitability of camel milk for the production of dairy products by lactic acid fermentation. Sixty strains of lactic acid bacteria (LAB) were isolated from camel milk. The strains were tested for their acidification activity, ability to use citrate, exopolysaccharide production, lipolytic, proteolytic activities and resistance to antibiotics. Ten strains were investigated for their ability to metabolize carbohydrates and that resulted in the identification of 5 Lactococcus lactis, 1 Lactobacillus pentosus, 2 Lactobacillus plantarum, 1 Lactobacillus brevis and 1 Pediococcus pentosaceus strains. Two strains of Lactococcus lactis SCC133 and SLch14 were selected to produce traditional Tunisian fermented dairy products (Lben, Raib, Jben cheese and Smen). These strains were chosen based on their acid production capacity and their ability to produce a high yield of biomass.     

Changes in Lipid Composition and Antioxidant Capacity of Bitter Orange (<Emphasis Type="Italic">Citrus aurantium.</Emphasis> L) and Mandarin (<Emphasis Type="Italic">Citrus reticulata.</Emphasis> Blanco) Oilseeds on Different Stages of Maturity

Oilseeds from bitter orange and mandarin and its antioxidant activities were investigated in this study. The effects of harvesting times (D1: green color, D2 yellow color, D3: orange color) on the extraction yield of oilseed were studied. The maximum yield of 44% was achieved at D3 (bitter orange). The chemical composition of the oilseed was analyzed by gas chromatography (GC). The main methyl esters were linoleic acid (C18:2, 32–42%), palmitic acid (C16:0, 22–26%)), stearic acid (C18:0, 9.01%) and linolenic acid (C18:3, 4–10%). The antioxidant activity of oilseed was assessed by means of 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical-scavenging assay and β-carotene bleaching test. Both methods demonstrated notable antioxidant activities of bitter orange and mandarin oilseeds, which is nearly comparable to the references ascorbic acid and butylated hydroxytoluene (BHT). The antioxidant activities of the oilseeds were also found to be harvesting time-dependent.     

Experimenting Active Reliable Multicast on Application-Aware Grids

The ever growing needs for computation power and accesses to critical resources have launched in a very short time a large number of grid projects and many realizations have been done on dedicated network infrastructures. On Internet-based infrastructures, however, there are very few distributed or interactive applications (MPI, DIS, HLA, remote visualization) because of insufficient end-to-end performances (bandwidth, latency, for example) to support such an interactivity. For the moment, computing resources and network resources are viewed separately in the Grid architecture and we believe this is the main bottleneck for achieving end-to-end performances. In this paper, we promote the idea of a Grid infrastructure able to adapt to the applications needs and thus define the idea of application-aware Grid infrastructures where the network infrastructure is tightly involved in both the communication and processing process. We report on our early experiences in building application-aware components based on active networking technologies for providing a low latency and a low overhead multicast framework for applications running on a computational Grid. Performance results from both simulations and implementation prototypes confirm that introducing application-aware components at specific location in the network infrastructure can succeed in providing not only performances for the end-users but also new perspectives in building a communication framework for computational Grids.     

Optimal Robust Control for Unstable Delay System

Proportional-Integral-Derivative control system has been widely used in industrial applications. For uncertain and unstable systems, tuning controller parameters to satisfy the process requirements is very challenging. In general, the whole system’s performance strongly depends on the controller’s efficiency and hence the tuning process plays a key role in the system’s response. This paper presents a robust optimal Proportional-Integral-Derivative controller design methodology for the control of unstable delay system with parametric uncertainty using a combination of Kharitonov theorem and genetic algorithm optimization based approaches. In this study, the Generalized Kharitonov Theorem (GKT) for quasi-polynomials is employed for the purpose of designing a robust controller that can simultaneously stabilize a given unstable second-order interval plant family with time delay. Using a constructive procedure based on the Hermite-Biehler theorem, we obtain all the Proportional-Integral-Derivative gains that stabilize the uncertain and unstable second-order delay system. Genetic Algorithms (GAs) are utilized to optimize the three parameters of the PID controllers and the three parameters of the system which provide the best control that makes the system robust stable under uncertainties. Specifically, the method uses genetic algorithms to determine the optimum parameters by minimizing the integral of time-weighted absolute error ITAE, the Integral-Square-Error ISE, the integral of absolute error IAE and the integral of time-weighted Square-Error ITSE. The validity and relatively effortless application of presented theoretical concepts are demonstrated through a computation and simulation example.