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Linkage Based Community Detection in Social Networks
Get PDFCommunity detection is one of important research problems in the field of social network analysis. It is the process of unfolding dense subgroups in the network also called as communities. Communities are the set of users which are strongly correlated with each other as compared to users lying outside of the subgroups. They correspond to the potential functional units in the complex network. Understanding the structural topology of the communities are quite useful in exploring the behaviour of the network. However, due to unprecedented growth of size and complexity in real-world networks, exploring the hidden communities has been a challenging task. Although a number of algorithms have been developed to address the community detection problem, still major concerns lie in scalability and consistency in the output. In this thesis, we have analyzed the topological features of various real-world networks and identified the functional groups corresponding to communities. Most of them are dependent on objective function based on a parameter such as modularity. However, it suffers from a problem known as resolution limit, where potential communities with few number of nodes could be missing in the result of community detection algorithm.
The first contribution of the thesis is on development of computational efficient community detection algorithm which is based on a new objective function known as MIN-MAX modularity. It can also be used for measuring the quality of community partition. Unlike other scoring metric, it does not exhibit the problem of resolution limit
The second contribution is based on development of distributed and scalable community detection algorithms which are able to handle the complexity and large size real-world networks. The proposed distributed algorithms are based on scale-free networks that exhibit power-law degree distribution which is often more resemble with the real-world networks
The third contribution is based on development of meta-heuristic solutions to tackle the community detection problem in complex network. We have used genetic algorithm and ant colony optimization techniques to develop the community detection algorithm. The major objective of the meta heuristic algorithms is to deliver the solution in less computational time, which will differ only by a constant factor from the optimal solution. The experimental analysis on some real-world and synthetic networks shows that it outperforms over other existing traditional community detection algorithms
The fourth contribution focuses on designing the scalable algorithms that identify the influential communities in the network. In order to explore the influential community, we have adopted three different approaches. First one is fuzzy and rough set theory, which capture the degree of uncertainty in belongingness of a node in the network. The second one is the centrality analysis. It has been observed that any social group or community usually formed from a central point. If we are able to capture the central node or influential nodes in the network, it would be easy to explore the hidden communities lying within it. However, as the real-world network’s size is huge and complex, processing it in traditional tools is quite challenging. We have developed map-reduce based algorithms for identifying the central nodes in the network. We have leveraged this central nodes in exploring the influential communities. The third one is based on the link prediction problem that identify the relationships between nodes, which are either missing or does not exist currently but likely to be appear in future. It has been observed that strength of ties has significant roles in community evolution in the network. It is desirable to quantify the strength of missing links, as the missing links may have the major contribution in forming the clusters in the network. To address this problem, map-reduce based scalable and distributed algorithms have been developed to identify and quantify the strength of the links
Electro-Formation of Cu-Graphene Composites and Its Property Evaluation
Get PDFIn the current study, few-layer graphene particles (FLGPs) have been synthesized by electrochemical exfoliation method. Two different electrolytes of 1M H2SO4 and HNO3 were used. The electrolyte produces anions of 2 4 SO and 3 NOwhich interact with pyrolytic graphite sheets to intercalate and produce FLGPs. Further, the prepared FLGPs are reduced by ascorbic acid and hydrazine hydrate and are leveled as RFLGPs(Vc) and RFLGPs(Hy) respectively. The prepared graphene particles were then analyzed by various scientific analyses such as TGA, XRD, FTIR, XPS, UV and Raman spectroscopy.
Thermal stability and yield of graphene particles are done by TGA analysis. XRD and Raman spectroscopy were used for structural properties, lattice spacing and crystal structure of graphene particles. The (001) and (002) lattice plane of graphene oxide and graphene has been observed at 13º and 26.2º from XRD analysis. The as-synthesized graphene were expected to be functionalized which was confirmed by FTIR analysis and the functional groups are hydroxy, carboxy, epoxides and alcohol. The prepared FLGPs were then analyzed by XPS to quantify carbon oxygen ratio. The electronic transitions of π-π* and n-π* have been analyzed by UV-visible spectra. The topographical and morphological analysis of graphene has been carried out by FESEM and TEM analysis.
The FESEM microscopy shows the agglomeration and layer structure. The TEM analysis gives the number of layers of graphene particles. The in-house synthesized graphene was found to consist of few layers and was partially functionalized too. The prepared FLGPs and RFLGPs have been used as reinforcement with the copper matrix to synthesize Cu- FLGPs nanocomposite.
Copper-graphene nano-composites were synthesized by the electrodeposition method.
FLGPs and RFLGPs of different concentrations (0.1, 0.3 and 0.5 g/L) were added into the copper matrix. The Cu films are plated first onto the steel substrate at different temperatures (25, 20 and 15 °C) to decide the deposition temperature (based upon the film characteristics obtained). Synthesis of the composite films were then carried out and compared in both silent and ultrasonic stirring conditions in the aqueous electrolyte. Cu deposited at 15 °C was best and was chosen to carry out the composite film deposition.
The synthesized specimens (Cu and composite films) were characterized by surface Profilometry, XRD, SEM, EDS and AFM analyses. Furthermore, the distribution of
Xi graphene was found to be better in the presence of ultrasound as witnessed from the structural and micro-graphical analysis. Then after the micro and nano-mechanical as well as electrical resistivity properties of the composites were measured to evaluate the performance of the films. The composite films have 31% improved hardness as compared to the pure copper films. The electrical resistivity has been increased from 1.6×10-6 -cm to 3.6×10-6 -cm. The electrodeposited Cu-FLGPs composite shows improved mechanical and comparable electrical properties as well as compared to the pure copper thin film. The Cu-RFLGPs composite shows 38% higher hardness as compared to pure copper thin film. The Cu-RFLGPs composites did show an adhesive type of wear leading to delamination of Cu layers. Apart from mechanical properties, the electrical resistivity of the sono-electroplated films was found to be improved as well. The corrosion behaviors of Cu-FLGPs as well as Cu-RFLGPs composite films have been analyzed by threeelectrode cell setup. Tests were carried out in two solutions i.e. standard borate buffer and 3.5% NaCl to simulate the general and pitting corrosion behavior respectively. All the composite films show well developed passivation regions in borate buffer and the pitting was also evident from the potentio-dynamic polarization plots. The general corrosion tendency and rate was found to be less in composite films. Further pitting was also less in composite films. The mechanism of such observation was proposed by EIS study. Out of the two types, Cu-RFLGPs composites have superior mechanical, electrical and anticorrosive properties
An Investigation of Dissimilar Pipe Welding of AISI 304 Stainless Steel with CP Copper
No full textA study on dissimilar metal welding of commercially pure copper and AISI 304 SS pipes with different thicknesses has been carried out. Three different welding processes, namely, pulsed Nd:YAG laser beam, pulsed TIG Arc and continuous CO2 laser beam welding have been compared. For studying the effects of process parameters, viz. peak power, pulse duration, frequency, beam diameter (for laser beam) / stand-off distance (for TIG), processing speed, energy density etc. Controlled set of experiments are conducted as per standard DOE (Design of Experiment) methods. Temperature buildup during welding has been measured by K-type thermocouples with a data acquisition system. Mechanical and metallurgical characterization of the welds, i.e., tensile strength, bead geometry, microhardness, etc., have been performed. Microstructure of the weld pool has been characterized by SEM, EDX and XRD. Effect of ramp down parameters on the closure bead shape has been studied in pulsed TIG arc welding. The results have been analyzed statistically with RSM (Response Surface Method). Finite element modeling of the process has been done and simulations have been run at the parameter combination levels selected during experimentation. Customized jigs and attachments have been designed and fabricated for automation of the welding process of pipes.
Results from mechanical testings have been encouraging, with weld strengths realized in between those of the base metals. In most cases, joint failure has taken place away from the fusion zone and in the weaker component (Copper). A few welds fabricated with pulsed Nd:YAG laser failed at HAZ or in the base metal. Some parametric combinations resulted in solidification cracking at the crown. Microstructural characterization shows presence of unmixed zones, partially mixed zones and carbide precipitation similar to results reported by previous researchers. Use of frequency as a tool for controlling weld pool agitation and the weld bead shape has been tried and found to be effective. Pulsed TIG arc welding and CO2 laser welding have been found to be more suitable for welding load bearing structures. Pulsed Nd:YAG laser has been found to be more suitable for welding smaller pipe thicknesses. The results and the models proposed by the present study can serve as an useful tool for further improvisations in autogenous welding of CP Copper and AISI 304 SS
Experimental Investigations of Unsteady Flow Over Rough Bed Channels with and Without Emergent Rigid Vegetation
No full textThe Ph.D. thesis deals with the experimental investigation on flow structures over rough bed channels with and without emergent rigid vegetation. Experiments over dense grass bed are conducted at National Institute of Technology Rourkela (NITR) to investigate the lateral velocity profiles, bed shear stress, Reynolds shear stress and turbulence characteristics under unsteady flow conditions as compared to the steady flow conditions for a given flow depth. The flow structures of unsteady open-channel flow over a rough bed with and without emergent rigid vegetation are also investigated in an 18 m long and 3 m wide laboratory flume at INRAE Lyon-Villeurbanne, France. Steady flows are also studied and served as reference flows. For both steady and unsteady flows, four geometries are tested: (1) uniform bed roughness (uniform dense synthetic grass modelling meadow); (2) a uniform staggered distribution of emergent wooden circular cylinders (model of rigid vegetation) set on bed roughness; (3) a uniform unsteady (longitudinal roughness transition from woodland to dense grass); and (4) a non-uniform unsteady (longitudinal roughness transition from dense grass to woodland). For lower unsteady flow cases (longer period flow hydrograph), lateral distribution of depth-averaged velocity and bed shear stress is plotted at three different cross-sections and compared with the results from steady flow conditions. Variations of Reynolds stress along the vertical and lateral direction are analyzed. Turbulence characteristics, i.e., turbulent kinetic energy (TKE), mean kinetic energy (MKE) and dissipation rate has also been analyzed. For higher unsteady flow cases (short period flow hydrograph), transient flow depths are simultaneously measured at six longitudinal positions using ultra-sonic sensors. Transient velocities are measured at one longitudinal position over the water column using a side looking ADV probe to estimate depth-averaged velocity. In order to compute ensemble averages of the flow parameters, 109 runs of the same hydrographs are injected repeatedly at the flume entrance. Two consecutive runs are separated by a base flow. The ensemble averages of the measured discharge, flow depths and velocity are found to be converged when using 45, 50, and 72 runs respectively. After the data convergence, the discharge, velocity, Reynolds shear stress etc. have been finalized for the present unsteady flow analysis. The present study therefore focuses on these. A particular attention is paid to the convergence of flow parameters based on ensemble averages: (1) to confirm the mean velocity profiles for unsteady accelerated, and decelerated flows, and uniform flows over a rough bed; (2) to study the vertical distribution of mean flow, turbulent statistics and Reynolds shear stress for unsteady accelerated, decelerated, and uniform flows over a rough bed with emergent rigid vegetation, (3) to study the vertical distribution of mean flow, turbulent statistics and Reynolds shear stress for unsteady accelerated, decelerated, and uniform flows over a rough bed (downstream of roughness transition), and (4) to study the vertical distribution of mean flow, turbulent statistics and Reynolds shear stress for unsteady accelerated, decelerated, and non-uniform flows over a rough bed (upstream of roughness transition). The variations of vertical profiles of mean streamwise velocity, turbulence statistics and Reynolds shear stress for the unsteady flow cases along the vertical direction are analysed and also compared to the steady flow conditions. The hysteresis loops in the depth-averaged velocity/flow depth relationships for unsteady flow conditions have been illustrated for the four geometries highlighting the weak effect compared to the effects of un-stationarity
Ownership Structure, Firm Performance, and Stock Liquidity: Empirical Evidence from Indian Listed Firms
No full textThis study empirically examines the determining factors of ownership structure, and its effect on corporate performance and stock liquidity of Indian listed firms. This study covers two distinct market conditions such as pre-crisis and post-crisis period by considering FY 2008- 09 as the crisis year. Pre-crisis period covers 08 years from FY 2000-01 to FY 2007-08, while post-crisis period covers 08 years from FY 2008-09 to FY 2016-17. Non-financial listed firms from NSE are employed, where 316 companies for pre-crisis and 403 companies for post-crisis period. This study employs panel modelling approaches like static and dynamic panel models for the examination of hypotheses.
Concentrated ownership mostly prevails in Indian corporates, while promoters or founders are found to be largest owners and they dominate the space of management policy making. According to agency perspective, India has agency issues between major and minor owners, unlike Anglo-Saxon countries. Empirical findings indicate that concentration level improves with better legal framework during the pre-crisis period, while superior profitability and industry life cycle improves concentration level during post-crisis period. Mostly, promoters are interested in the firms‟ profitability, growth opportunity and leverage. While institutional investors are mostly driven by bigger firms and better growth options irrespective of the different market conditions.
Ownership concentration is ineffective in influencing the profitability and market value during pre-crisis phase, while it improves profitability through their active engagement during post-crisis phase. Engagement by promoters improves the profitability during both the study periods and boosts the stock returns during post-crisis phase. Foreign institutions adversely influence profitability during pre-crisis period, while no effect in post-crisis period. Foreign players favourably affect market value during both the periods, while their activism negatively influences stock return during pre-crisis stage but have a positive impact during the post-crisis period. Remarkably, domestic institutions are found to be completely ineffective in influencing both the financial and market performance.
Ownership concentration adversely affects the stock liquidity during both stages of the economy while promoters have a declining effect during post-crisis period. Foreign institutions have an adverse effect on stock liquidity during both the market conditions, whereas domestic institutional engagement has no effect during both the periods. Retail investors‟ participation has an incremental effect on stock liquidity regardless of market conditions.
This research adds many contributions to the ownership literature. The use of two broad structure of ownership such as ownership concentration and identities would definitely widen the existing ownership studies. Determinants of corporate ownership structure is innovative for Indian market. Further, work on the determining factors of promoters and institutional ownership will add novelty to the current governance literature. Next, consideration of two distinct market conditions to find the time-dependent and time-independent determining factors is completely novel. The use of GMM improves the robustness of the findings by reducing the endogeneity issues, which is contemporarineous
Connectionist Models for Solving Linear and Nonlinear Equations
No full textVarious engineering and science problems may transform into linear and nonlinear equations, in general. In recent decades, Artificial Neural Network (ANN) has emerged as one of the prominent mechanism for solving linear and nonlinear equations. Although linear and nonlinear equations may be solved by different known analytical and numerical methods but those are sometimes having different complexity to handle. Traditional numerical methods may sometimes fail to solve these equations due to the involvement of singularities or complexity of the function etc. Moreover, (for example) there may exist two closely positioned roots or due to discontinuity of the curve in the problems of root finding and then the known numerical methods may sometimes difficult to use. In case of linear system of equations, the traditional numerical methods sometimes fail if the system is not diagonally dominant, positive definite etc. In those cases, ANN based methods may be an alternative for solving the equations. In this regard, detail ANN procedure with various example problems related to transcendental, Diophantine and linear system of equations with their network architectures have been addressed here to demonstrate the proposed procedure.
Further, solving linear and nonlinear eigenvalue problems are also challenging task. For example, dynamic analysis of structure without damping may transform into a linear eigenvalue problem and with damping it leads to a nonlinear eigenvalue problem. Linear eigenvalue problems are studied though by many authors, but nonlinear eigenvalue problems are not studied much. However, these methods (for both linear as well as nonlinear) may sometimes be problem dependent and difficult to handle. As such, in these cases, ANN may also be advantageous over the existing methods. Few examples of linear eigenvalue problems such as vibration analysis of spring mass system and multi-storey shear building have been investigated. On the other hand, two examples of overdamped spring mass systems have been examined to show the efficacy of the proposed method in case of nonlinear eigenvalue problem.
It may be noted that parameters involved in the above systems may not be crisp (exact) always because of errors in experiment, measurement and observation. In that case, the problem leads to an uncertain system. In order to handle these uncertainties, recently researchers have introduced interval and/or fuzzy numbers in place of crisp ones. In these regards, various techniques have been developed by different authors but these are sometimes valid for certain (particular) type of problems only. These methods may have few drawbacks that include number of iterations, triangularisation etc. In this context, application problems such as static problems of structures lead to system of equations. As mentioned earlier that inclusion of uncertainty makes the problem as uncertain. Similarly, computation of the interval controls using pole placement technique in case of uncertain plant system reduces to interval linear system, which itself is a challenging problem. Moreover, dynamic problems lead to eigenvalue problems which may become more complicated due to the inclusion of uncertainty. Accordingly, ANN methods have been developed to handle the above problems with ease. Different example problems have been solved in this context to validate the proposed ANN technique
Modulation of Different Proteins’ Conformational Dynamics in The Presence of ZnO Nanoparticles with Varying Surface Properties
No full textIn the recent years, with the advent of nanotechnology, nanoparticles have received immense attention in various fields including the medical and pharmaceutical industries. With increased applications, increases the risk of these nanoparticles’ exposure to the biological milieu. Hence it becomes imperative to understand the nanoparticle interaction at bio-interface especially with the protein molecules, as they are major soluble constituent of cytosol and tend to get adsorbed on nanoparticles as it enters the biological milieus. This interaction not only affects the nanoparticle properties but also induces changes in the protein conformation. Proteins are one of the most abundant and important biological molecules. A correctly folded conformation is required to execute its biological functions. However, due to various intrinsic (polypeptide sequence, mutation, presence of aggregation prone regions (APRs)) and extrinsic factors (environmental conditions) certain proteins have higher tendency to misfold into amorphous or fibrillar aggregates. This misfolding or aggregation of a protein leads to loss of its function; exert cellular toxicity and consequently onsets human disorders (e.g. Alzheimer’s disease, Huntington’s disease, Parkinson’s disease, amyotrophic lateral sclerosis and type II diabetes). Over the years, significant research interests have developed therapeutic application of nanoparticles in the protein aggregation and the diseases associated with amyloid. Due to their unique properties, nanoparticles (NPs) have shown significant effect on the protein conformation. However, the nanoparticle interaction with protein can act as a double edge sword depending on the strength of interactions, which in turn depend upon the physiochemical properties of both NPs and proteins interacting interfaces. The advantage of working with NP based therapeutics is the flexibility in controlling/modifying its physiochemical properties thus controlling the consequence of protein nanoparticle interactions. Hence in the thesis, we synthesized ZnONP to explore the effect of varying size, surface charge and hydrophobicity on the conformational dynamics of different proteins with varying aggregation prone region (APRs). In the beginning, we have reported the highly aggregation prone nature of recombinant hGPx7 and shown that the ZnONP does not show any significant effect on its aggregation propensity. With the help of computational tools, we also identified some exposed hydrophobic APRs in close proximity with its protein binding sites, indicating the role of protein-protein interaction in maintaining the compact stable state of hGPx7. The next part of the thesis gives an insight about the role of solvent polarity in disturbing protein stability and the chaperone like behaviour of ZnONP under SDS induced fibrillation of lysozyme at pH 9.0. The competitive binding between SDS and ZnONP on the exposed hydrophobic patch of lysozyme in pH 9.0 solution, was mediated mainly through electrostatic and hydrophobic interactions. The preferential binding of the lysozyme onto ZnONP inhibits the protein fibrillation by enhancing its secondary structure and activity. However, the same ZnONPs showed contrasting effects on insulin, a small globular protein vital for glucose regulation and its aggregation has been implicated in type II diabetes. However, surface functionalization of ZnONP with tryptophan and tyrosine, not only mitigates the fibrillation of insulin induced at bare ZnONP interfaces but also reduced the toxicity of oligomers formed in their presence. After exploring the effects of ZnONP on globular protein, our last choice as protein was an intrinsically disordered protein, α-synuclein. We investigated the effects of ZnONP and its varying size/surface curvature on the fibrillation propensity of α-synuclein. A concentration as well as size dependent inhibition in α-synuclein fibrillation was observed. ZnONP stabilizes the native structure of synuclein and inhibit the synuclein fibrillation by preferably binding to hydrophobic cluster of α-synuclein monomers resulting in formation of off pathway non-toxic aggregates with native random coil content. Hence, exploring the effect of ZnONP on different proteins will contribute towards a better understanding of the aggregation processes, and may open the way to designing nanoparticles that modulate protein aggregation and formation of toxic amyloid species
Analysis and Design of an Efficient PV Power Optimizer with Reduced EMI Effects and Less Sensors Counts
No full textPower optimizers (POs) based distributed maximum power point tracking (DMPPT) architecture can reduce the shading and mismatches losses in photovoltaic(PV) systems. The POs are inherently switched dynamical systems characterizedby discrete switching events that make the systems toggle between two or moretopological states in local neighborhood of the maximum power point (MPP). Due
to this switching process, MPP tracker results in various harmonics at the multiplesof switching frequency of the power converters. These harmonics are undesirable as they often associated with electromagnetic interferences (EMIs) and may also degrade the performance of the system; in particular, for DMPPT architectures. The MPP trackers must provide the desired electrical functionality, e.g., meet the EMIs regulation-standards and also exhibit the fast-tracking performance under rapidly changing solar irradiation and load uctuations.
The aim of this work is thus being devoted to the development of rapid and precise MPP trackers for various PV applications. However, constrains imposed by cost, number of sensors requirement, size/weight, and tracking performances (in terms of fast transient responses with bounded chaotic ripple speci_cations in order to reduce EMIs) essentially limit the application of conventional control techniques and their analysis methodologies. We propose an analog MPP tracker which is deliberately designed and analyzed by using the concepts of nonlinear dynamics and bifurcation theory. Such concepts not only provide the informations to design a fast-and-e_cient MPP tracker under rapidly changing environmental conditions, but also guarantees the system to operate in chaotic mode. We have developed both 1-D and 2-D discrete-time models (or maps) that will ensure reliable and safe chaotic operation of the modular photovoltaic systems (MPVS). The conditions for robust chaos thus also been derived and show how its robustness can be destroyed by introducing a small change in the switching control logic, e.g., from synchronous to asynchronous mode of operation and vice-visa. In addition, an exemplary concept of current sensorless MPP tracker with two-loop (i.e., fast inner peak current-mode-controller and slow outer voltage controller) feedback control technique has been proposed. The appropriate design of such MPPT tracker has also been performed using the singular perturbation based fast-slow-scale system analysis. We show that use of current sensors for MPP tracker can be
completely avoided and exact current information can be estimated by using a proportional-integral observer (PIO). The advantages of such PIOs in terms of ability to estimate simultaneously the states and the unknown inputs disturbances/model uncertainties have been explored and then compared with classical Luenberger observer or P-observer. Finally, all these are experimentally veri_ed using a built-in laboratory prototype MPVS
Herbicide Bioremediation Using Hyperbutachlor Tolerant Microorganisms in Batch and Continuous Systems
Get PDFIn the present thesis, an attempt has been made towards the development of an efficient biotreatment technology for handling herbicide contamination in industrial effluents and agricultural soils. Butachlor, the most complex structured and extensively used herbicide in India is of primary focus. Three hyper-butachlor tolerant bacterial strains identified as Serratia ureilytica strain AS1, Enterobacter cloacae strain FP2 and Pseudomonas putida strain G3, based on the 16S rRNA gene sequencing analysis were isolated from three different contaminated sites. To maximize the removal efficiency, the factors affecting the metabolic activity of any microorganism were optimized by the application of various statistical design of experiments. Initially the factors were screened as per the Plackett Burman design of experiment to determine the significant factors which were further optimized using the Response Surface Methodology to identify the optimum conditions where the isolated strain will yield the maximum butachlor removal efficacy. Biodegradation of butachlor and other herbicides such as alachlor and glyphosate, by the isolated strains at various initial concentrations (100 – 1000 mg/L), was studied at the optimum conditions obtained in the previous study. It was observed that with increase in the butachlor concentration, the rate of biodegradation decreases which indicates the substrate inhibition phenomenon. The degradation kinetics of the bacterial strains were fitted with various substrate inhibition models available in the literature which are able to predict the experimental data fairly. To elucidate the plausible metabolic pathway followed during the biodegradation process, the intermediate metabolites were identified. To overcome the substrate inhibition at higher butachlor concentrations, various strategies have been adopted to investigate the enhancement of the remediation efficiency. Firstly, the bacterial strains were immobilized within Ca-alginate beads and batch biodegradation experiment was carried out. The study revealed that on being immobilized, the microbial strains are able to tolerate and degrade higher butachlor concentration as compared to their freely suspended cell counterparts. Secondly, to overcome the microbial toxicity of butachlor, the bacterial strains were co-cultured to formulate a defined synthetic microbial consortium termed as SMC 1. The consortium displayed the potentiality to be a promising candidate for the remediation of butachlor and other herbicides at higher concentration both in aqueous medium as well as in the soil. viii After establishing the batch biodegradation of butachlor and other herbicides in shake flasks studies, experiments were performed in continuous mode to treat synthetic wastewater containing butachlor in packed bed bioreactors. The combined effect of external mass transfer and the biochemical reaction on the mass transfer correlation was investigated in a re-circulated packed bed bioreactor using the microbial consortium SMC1 immobilized in Ca-alginate beads. It is observed that the rate of bio-removal of butachlor from the medium is dependent on the operating parameters; feed flow rate and substrate concentration. The effect of the external mass transfer was investigated by calculating the mass flux (G), Reynold’s Number (NRe) and the mass transfer coefficient (km) for varying feed flow rates. The constants obtained from the plot of ln km vs ln G is used to determine the external mass transfer correlation between the Colburn factor (JD) and Reynolds number (NRe) which can predict the experimental data precisely. Effect of various operating parameters such as HRT, inlet loading rates on the performance of the bioreactor was investigated in another up-flow packed bed biofilm reactor filled with ceramic raschig rings immobilized with the microbial consortium SMC1. The study proposes the immobilized system of demonstrating excellent biodegradation efficacy of the immobilized microbial consortium in treating herbicide contaminated synthetic wastewater in continuous mod
Techniques for QoS Provisioning and Differentiation in OBS Networks
No full textIn an OBS network, either reactive or proactive techniques are used to resolve the wavelength contentions. Reactive routing is generally online, which responds to contentions, but does not address the more general problem of congestion. Thus, there is a need for an offline network level contention avoidance technique to minimize burst contentions. Proactive routing strategies are generally offline, which avoid wavelength contentions and increase overall performance of burst transmissions by using efficient Routing and Wavelength Assignment (RWA) mechanisms. In this context, proactive routing is a convenient approach since it easily controls the distribution of burst traffic and requires minimum support from the control plane. In this thesis, I have analyzed the efficacy of the RWA approach in providing better QoS guarantees to loss sensitive bursts. Furthermore, the review of slotted-OBS architectures suggests that the synchronization among conflicting bursts is achieved by using fiber delay lines (FDLs) and the switching of a burst in time domain is inevitable even though it uses a non-overlapping path to reach the egress node. In this thesis, I have made an attempt to synchronize bursts only when necessary; i.e. the cases where a path used for transmitting a burst conflicts with another path on a common wavelength across a shared link