Current Trends in Wireless Networking

Current Trends in Wireless Networking. DigitalLibrary@CUSAT. ...

Current status and biodiversity modification in the coastal wetland ecosystems of India with objectives for its sustainable management

The South West (S.W.) coast of India is blessed with a series of wetland systems popularly referred to as backwaters covering a total area of 46128.94 ha. These backwaters are internationally renowned for their aesthetic and scientific values including being a repository for several species fish and shell fishes. This is more significant in that three wetlands (Vembanad, Sasthamcotta and Ashtamudi) have recently been designated as Ramsar sites of international importance. Thirty major backwaters forming the crux of the coastal wetlands form an abode for over 200 resident or migratory fish and shellfish species. The fishing activities in these water bodies provide the livelihood to about 200,000 fishers and also provide full-time employment to over 50,000 fishermen. This paper describes the changes on the environmental and biodiversity status of selected wetlands, during 1994-2005 period. The pH was generally near neutral to alkaline in range. The salinity values indicated mixohaline condition ranging from 5.20-32.38 ppt. in the 12 wetlands. The productivity values were generally low in most of the wetlands during the study, where the gross production varied from 0.22 gC/m3/day in Kadinamkulam to 1.10 gC/m3/day in the Kayamkulam. The diversity of plankton and benthos was more during the pre-monsoon compared to the monsoon and post-monsoon periods in most of the wetlands. The diversity of plankton and benthos was more during the pre-monsoon compared to the monsoon and post-monsoon periods in most of the wetlands. The average fish yield per ha. varied from 246 kg. in Valapattanam to 2747.3 kg. in Azhikode wetland. Retting of coconut husk in most of the wetlands led to acidic pH conditions with anoxia resulting in the production of high amounts of sulphide, coupled with high carbon dioxide values leading to drastic reduction in the incidence and abundance of plankton, benthic fauna and the fishery resources. The major fish species recorded from the investigation were Etroplus suratensis, E. maculatus, Channa marulius, Labeo dussumieri, Puntius sp. Lutianus argentimaculatus, Mystus sp., Tachysurus sp. and Hemiramphus sp. The majority of these backwaters are highly stressed, especially during the pre monsoon period when the retting activity is at its peak. The study has clearly reflected that a more restrained and cautious approach is needed to manage and preserve the unique backwater ecosystems of South-west India

Chemical gas sensors based on functionalized self-actuated piezo-resistive cantilevers

Der Schwerpunkt dieser Arbeit liegt in der Anwendung funktionalisierter Mikrocantilever mit integrierter bimorpher Aktuation und piezo-resistiver Detektion als chemische Gassensoren für den schnellen, tragbaren und preisgünstigen Nachweis verschiedener flüchtiger Substanzen. Besondere Beachtung erfährt die Verbesserung der Cantilever-Arbeitsleistung durch den Betrieb in speziellen Modi. Weiterer Schwerpunkt liegt in der Untersuchung von spezifischen Sorptionswechselwirkungen und Anwendung von innovativen Funktionsschichten, die bedeutend auf die Sensorselektivität wirken.

CoDaPack. An Excel and Visual Basic based software of compositional data analysis. Current version and discussion form upcoming versions

In the eighties, John Aitchison (1986) developed a new methodological approach for the statistical analysis of compositional data. This new methodology was implemented in Basic routines grouped under the name CODA and later NEWCODA inMatlab (Aitchison, 1997). After that, several other authors have published extensions to this methodology: Marín-Fernández and others (2000), Barceló-Vidal and others (2001), Pawlowsky-Glahn and Egozcue (2001, 2002) and Egozcue and others (2003). (...)

Enhancing fault management performance of two-step QoS routing algorithms in GMPLS networks

In this paper a novel methodology aimed at minimizing the probability of network failure and the failure impact (in terms of QoS degradation) while optimizing the resource consumption is introduced. A detailed study of MPLS recovery techniques and their GMPLS extensions are also presented. In this scenario, some features for reducing the failure impact and offering minimum failure probabilities at the same time are also analyzed. Novel two-step routing algorithms using this methodology are proposed. Results show that these methods offer high protection levels with optimal resource consumption

Robust fault detection using consistency techniques for uncertainty handling

Often practical performance of analytical redundancy for fault detection and diagnosis is decreased by uncertainties prevailing not only in the system model, but also in the measurements. In this paper, the problem of fault detection is stated as a constraint satisfaction problem over continuous domains with a big number of variables and constraints. This problem can be solved using modal interval analysis and consistency techniques. Consistency techniques are then shown to be particularly efficient to check the consistency of the analytical redundancy relations (ARRs), dealing with uncertain measurements and parameters. Through the work presented in this paper, it can be observed that consistency techniques can be used to increase the performance of a robust fault detection tool, which is based on interval arithmetic. The proposed method is illustrated using a nonlinear dynamic model of a hydraulic system

Partial disjoint path for multi-layer protection in GMPLS networks

In this paper, different recovery methods applied at different network layers and time scales are used in order to enhance the network reliability. Each layer deploys its own fault management methods. However, current recovery methods are applied to only a specific layer. New protection schemes, based on the proposed partial disjoint path algorithm, are defined in order to avoid protection duplications in a multi-layer scenario. The new protection schemes also encompass shared segment backup computation and shared risk link group identification. A complete set of experiments proves the efficiency of the proposed methods in relation with previous ones, in terms of resources used to protect the network, the failure recovery time and the request rejection ratio

SQualTrack: A Tool for Robust Fault Detection

One of the techniques used to detect faults in dynamic systems is analytical redundancy. An important difficulty in applying this technique to real systems is dealing with the uncertainties associated with the system itself and with the measurements. In this paper, this uncertainty is taken into account by the use of intervals for the parameters of the model and for the measurements. The method that is proposed in this paper checks the consistency between the system's behavior, obtained from the measurements, and the model's behavior; if they are inconsistent, then there is a fault. The problem of detecting faults is stated as a quantified real constraint satisfaction problem, which can be solved using the modal interval analysis (MIA). MIA is used because it provides powerful tools to extend the calculations over real functions to intervals. To improve the results of the detection of the faults, the simultaneous use of several sliding time windows is proposed. The result of implementing this method is semiqualitative tracking (SQualTrack), a fault-detection tool that is robust in the sense that it does not generate false alarms, i.e., if there are false alarms, they indicate either that the interval model does not represent the system adequately or that the interval measurements do not represent the true values of the variables adequately. SQualTrack is currently being used to detect faults in real processes. Some of these applications using real data have been developed within the European project advanced decision support system for chemical/petrochemical manufacturing processes and are also described in this paper

Constraint satisfaction techniques under uncertain conditions for fault diagnosis in nonlinear dynamic systems

The speed of fault isolation is crucial for the design and reconfiguration of fault tolerant control (FTC). In this paper the fault isolation problem is stated as a constraint satisfaction problem (CSP) and solved using constraint propagation techniques. The proposed method is based on constraint satisfaction techniques and uncertainty space refining of interval parameters. In comparison with other approaches based on adaptive observers, the major advantage of the presented method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements and model errors and without the monotonicity assumption. In order to illustrate the proposed approach, a case study of a nonlinear dynamic system is presented

Fault diagnosis by refining the parameter uncertainty space of nonlinear dynamic systems

This paper deals with fault detection and isolation problems for nonlinear dynamic systems. Both problems are stated as constraint satisfaction problems (CSP) and solved using consistency techniques. The main contribution is the isolation method based on consistency techniques and uncertainty space refining of interval parameters. The major advantage of this method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements, and model errors. Interval calculations bring independence from the assumption of monotony considered by several approaches for fault isolation which are based on observers. An application to a well known alcoholic fermentation process model is presented

Application for fault location in electrical power distribution systems

Fault location has been studied deeply for transmission lines due to its importance in power systems. Nowadays the problem of fault location on distribution systems is receiving special attention mainly because of the power quality regulations. In this context, this paper presents an application software developed in Matlabtrade that automatically calculates the location of a fault in a distribution power system, starting from voltages and currents measured at the line terminal and the model of the distribution power system data. The application is based on a N-ary tree structure, which is suitable to be used in this application due to the highly branched and the non- homogeneity nature of the distribution systems, and has been developed for single-phase, two-phase, two-phase-to-ground, and three-phase faults. The implemented application is tested by using fault data in a real electrical distribution power system

An Interval Intelligent-based Approach for Fault Detection and Modelling

Not considered in the analytical model of the plant, uncertainties always dramatically decrease the performance of the fault detection task in the practice. To cope better with this prevalent problem, in this paper we develop a methodology using Modal Interval Analysis which takes into account those uncertainties in the plant model. A fault detection method is developed based on this model which is quite robust to uncertainty and results in no false alarm. As soon as a fault is detected, an ANFIS model is trained in online to capture the major behavior of the occurred fault which can be used for fault accommodation. The simulation results understandably demonstrate the capability of the proposed method for accomplishing both tasks appropriately

Who or what was the inspiration for choosing your current course of study?

Award winning student essay. This essay won the Student Writing Award Scheme via the HE Academy Subject Network for Information and Computer Sciences.