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Search Results: 1 - 10 of 21017 matches for " Shakti; Kumar Kukreja "
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Genetic transformation studies and scale up of hairy root culture of Glycyrrhiza glabra in bioreactor
Mehrotra,Shakti; Kumar Kukreja,Arun; Singh Khanuja,Suman Preet; Nath Mishra,Bhartendu;
Electronic Journal of Biotechnology , 2008,
Abstract: the study was undertaken to induce hairy roots in glycyrrhiza glabra in leaf explants and to optimize the nutritional requirement for its growth kinetics at shake flask and bioreactor level. pathogenecity of agrobacterium depends upon transformation ability of strain and age, type, and physiological state of explants. agrobacterium rhizogenes strain k599 was used to infect leaf explants of g. glabra. explants of different age groups were obtained from 2 to 5 weeks old in vitro grown cultures. bacterial strain k599 could induce hairy roots in 3 and 4 weeks old leaf explants cultured on b5, ms, nb and wp basal semi-solid medium. leaf explants of 2 and 5 weeks old culture were not responsive to bacterial infection in terms of hairy root induction. maximum transformation frequency (tf) of tested bacterial strain was 47% obtained in 3 weeks old explants after 25 days of incubation on ms basal semi solid medium. nb and b5 both media composition showed 20% of transformation frequency after 28 and 38 days respectively. wp medium did not support induction of roots in cultured leaf explants infected with a. rhizogenes strain k599even after 50 days of incubation. further, when all the four media combinations were tested for root growth it was found that though wp was not responsive for hairy root induction, yet all four basal media supported hairy root growth and a gradual increase in fresh weight biomass was observed with an increase in culture duration. however amongst all, the nb medium composition supported best growth of hairy roots followed by ms, b5 and wp media. about 20 times increase in root biomass on fresh weight basis was recorded after 45days of culture in nb medium. initial inoculum of roots (0.18 g. f.wt./ flask) containing 50 ml of liquid culture medium produced 3.59 g (f. wt.) biomass. a fast growing hairy root clone g6 was grown in a 5 l capacity mechanically agitated bioreactor provided with a nylon mesh septum. after 30 days of sterile run, 310 g of root b
Efficiency of Brown Stock Pulp washing in Liquid Properties
Jitender Kumar,V. K. Kukreja
International Journal of Engineering Science and Technology , 2011,
Abstract: Washing is simply bulk removal of the liquor surrounding the pulp fibers. In a laboratory washing cell, the mechanism of the displacement washing of unbleached Kraft pulp was investigated. The efficiency of displacement washing depends on the degree of mixing and also on the rate of desorption and diffusion of dissolved solids and chemicals from the pulp fibers. Using the step function input change method, the washing breakthrough curves obtained experimentally were described by the axially dispersed plug flow model. A correlation between Peclet numbers, Kappa numbers the wash yield, and pH of wash liquid was derived as well.The level of sorbed sodium varies with kappa number and pH. The effect of the superficial wash liquid velocity and of the mobility of displacing and displaced liquids upon the axial dispersion coefficient was discussed.
Soft Computing Framework for Routing in Wireless Mesh Networks: An Integrated Cost Function Approach
Shakti Kumar,Brahmjit Singh,Sharad Sharma
Computer Science , 2013,
Abstract: Dynamic behaviour of a WMN imposes stringent constraints on the routing policy of the network. In the shortest path based routing the shortest paths needs to be evaluated within a given time frame allowed by the WMN dynamics. The exact reasoning based shortest path evaluation methods usually fail to meet this rigid requirement. Thus, requiring some soft computing based approaches which can replace "best for sure" solutions with "good enough" solutions. This paper proposes a framework for optimal routing in the WMNs; where we investigate the suitability of Big Bang-Big Crunch (BB-BC), a soft computing based approach to evaluate shortest/near-shortest path. In order to make routing optimal we first propose to replace distance between the adjacent nodes with an integrated cost measure that takes into account throughput, delay, jitter and residual energy of a node. A fuzzy logic based inference mechanism evaluates this cost measure at each node. Using this distance measure we apply BB-BC optimization algorithm to evaluate shortest/near shortest path to update the routing tables periodically as dictated by network requirements. A large number of simulations were conducted and it has been observed that BB-BC algorithm appears to be a high potential candidate suitable for routing in WMNs.
Routing in Wireless Mesh Networks: Two Soft Computing Based Approaches
Sharad Sharma,Shakti Kumar,Brahmjit Singh
Computer Science , 2013, DOI: 10.5121/ijmnct.2013.3304
Abstract: Due to dynamic network conditions, routing is the most critical part in WMNs and needs to be optimised. The routing strategies developed for WMNs must be efficient to make it an operationally self configurable network. Thus we need to resort to near shortest path evaluation. This lays down the requirement of some soft computing approaches such that a near shortest path is available in an affordable computing time. This paper proposes a Fuzzy Logic based integrated cost measure in terms of delay, throughput and jitter. Based upon this distance (cost) between two adjacent nodes we evaluate minimal shortest path that updates routing tables. We apply two recent soft computing approaches namely Big Bang Big Crunch (BB-BC) and Biogeography Based Optimization (BBO) approaches to enumerate shortest or near short paths. BB-BC theory is related with the evolution of the universe whereas BBO is inspired by dynamical equilibrium in the number of species on an island. Both the algorithms have low computational time and high convergence speed. Simulation results show that the proposed routing algorithms find the optimal shortest path taking into account three most important parameters of network dynamics. It has been further observed that for the shortest path problem BB-BC outperforms BBO in terms of speed and percent error between the evaluated minimal path and the actual shortest path.
Cost-effective Approaches for in vitro mass Propagation of Rauwolfia serpentina Benth. Ex Kurz.
Manoj Kumar Goel,Arun Kumar Kukreja,Suman Preet Singh Khanuja
Asian Journal of Plant Sciences , 2007,
Abstract: The present study describes a highly efficient and a very cost effective micropropagation protocol for exsitu conservation of an important medicinal plant, Rauwolfia serpentina using glass beads as support matrix in liquid culture medium and as a potential alternative to agar and market grade sugar as carbon source. Glass beads can replace the conventionally used gelling agent agar without compromising the quality of the in vitro regenerated shoots/plantlets of R. serpentina. This practice could be helpful in achieving more than 95% reduction in cost media for the production of single regenerated shoot, moreover, the glass beads can be reused for indefinite time after proper acid wash.
Intellectual Behavior of a Group of Wild Animals: A Computational Intelligence Study
Avtar Singh Buttar,Ashok Kumar Goel,Shakti Kumar
International Journal of Soft Computing & Engineering , 2013,
Abstract: Numerous methodologies have been invented inspired by nature and based on real life behavior of species which perform task in a group. In this paper, a novel methodology based on intelligent chasing and hunting methods adopted by the animals in a group to chase & hunt their prey is presented. The dog is taken as prime model for developing the methodology. The method is named as “Dog Group Wild Chase & Hunt Drive (DGCHD) [18]. The algorithm is implemented on Traveling Salesman benchmark problem available in literature. The problem has been solved by different researchers for testing their proposed novel intelligent algorithms in various nature inspired technologies such as Ant Colony System, Genetic Algorithms etc. The results obtained are very optimistic and encouraging.
Dimensionality Reduction using SOM based Technique for Face Recognition
Dinesh Kumar,C.S. Rai,Shakti Kumar
Journal of Multimedia , 2008, DOI: 10.4304/jmm.3.1.1-6
Abstract: Unsupervised or Self-Organized learning algorithms have become very popular for discovery of significant patterns or features in the input data. The three prominent algorithms namely Principal Component Analysis (PCA), Self Organizing Maps (SOM), and Independent Component Analysis (ICA) have widely and successfully been used for face recognition. In this paper a SOM based technique for dimensionality reduction has been proposed. This technique has also been successfully used for face recognition. A comparative study of PCA, SOM and ICA along with the proposed technique for face recognition has also been given. Simulation results indicate that SOM is better than the other techniques for the given face database and the classifier used. The results also show that the performance of the system decreases as the number of classes increase.
Application of Mathematica Software to Solve Pulp Washing Model
Jitender Kumar,Ishfaq A. Ganaie,Vijay K. Kukreja
ISRN Chemical Engineering , 2013, DOI: 10.1155/2013/765896
Abstract: The removal of the bulk liquor surrounding the pulp fibers using less concentrated liquor is known as pulp washing. In the present study, a pulp washing model involving diffusion-dispersion through packed beds of finite length is presented. Separation of variables is applied to solve system of governing partial differential equations and the resulting equations are solved using Mathematica. Results from the present case are compared with those of previous investigators. The present case is giving better results than the previous investigators. 1. Introduction The objective of pulp and paper industry to produce its target production with high efficiency and less environmental load can only be met by initiating a meticulously planned research on mathematical methods. Pulp washing plays an important role in reduction of black liquor solids in the pulp being carried forward for further processing. The efficiency of washing depends on the degree of mixing, rate of desorption, diffusion-dispersion of dissolved solids, and chemicals from the fibrous matrix. Modeling of pulp washing is done mainly using three approaches, namely, (a) process modeling (b) physical modeling, and (c) statistical modeling. A complete review of the various process models used to describe pulp washing has been presented by [1]. Initially researchers like in [2, 3] proposed the models based on axial dispersion. Pellett [4] introduced a mathematical model combining the effects of particle diffusion and axial dispersion. A detailed model related to mass transfer in fibrous particle was given by [5]; it was also restricted for axial dispersion only. Comprehensive models involving physical features of the fibers such as fiber porosity and fiber radius were presented by [6, 7]. Extensive study of axial dispersion model has been carried out by [8–26]. The model has been solved using analytic and numerical techniques like Laplace transform technique [2–4, 10, 15, 23, 26], finite difference technique [25], orthogonal collocation method [5, 7, 12], orthogonal collocation on finite elements [6, 20, 21], Galerkin/Petrov Galerkin method [8, 19], Hermite collocation method by [11, 17, 24] and Spline collocation method [13]. The accuracy of the analytic solution undoubtedly exceeds the limit of applicability of the theory to real situations. Moreover, it is highly desirable to have a simple and consistent model of the transport phenomenon based on essential features of real situation. Keeping this modest goal in mind axial dispersion model is solved along with linear adsorption isotherm. The method
An Optimized Feature Selection for Image Classification Based on SVMACO
Priyanka Dhasal,Shiv Shakti Shrivastava,Hitesh Gupta,Parmalik Kumar
International Journal of Advanced Computer Research , 2012,
Abstract: Multi- class classification plays an import role inimage classification. Multi-class classificationused different classifier for the classification ofdata, such as binary classifier and support vectormachine. In this dissertation we proposed afeature sampling technique of imageclassification. Our sampling technique optimizedthe feature selection process and reduced theunclassified region in multi-class classification.For the process of optimization we used antcolony optimization algorithm for the properselection of feature sub set selection. Ant colonyoptimization is very famous meta-heuristicfunction inspired by biological spices. For theclassification of image data used support vectormachine. Support Vector Machines are designedfor binary classification. When dealing withseveral classes, as in object recognition and imageclassification, one needs an appropriate multiclass method. Different possibilities include:Modify the design of the SVM, as in order toincorporate the multi-class learning directly in thequadratic solving algorithm. Combine severalbinary classifiers: “One-against- One” (OAO)applies pair wise comparisons between classes,while “One-against-All” (OAA) compares a givenclass with all the others put together. OAO andOAA classification based on SVM technique isefficient process, but this SVM based featureselection generate result on the unclassified ofdata. When the scale of data set increases thecomplexity of preprocessing is also increases, it isdifficult to reduce noise and outlier of data set.Ant Colony Optimization (ACO) meta-heuristic isan effective tool in finding quality data and that’sthe main reason to use it as a feature selection forSVM.
Speed Regulation of DC Drive Using Mobile Communication
Shakti Bajaj,Ravinder Kumar Bhataia,J.Sandeep Soni
International Journal of Soft Computing & Engineering , 2013,
Abstract: The importance of the speed control of DC motors inmanufacturing industries like plastic, textile, chemical andpharmaceutical hardly needs any emphasis as it ensures efficientand consistent production. In this paper, the authors presentimplementation of a hardware circuit which is designed forremote speed control of a DC motor by using Dual Tone MultiFrequency (DTMF) tone of mobile phone. The hardware circuitincludes the use of DTMF decoder IC MT8870 and Relay driverIC ULN2003. The mobile keypad keys have been mapped to thespeeds of ‘High Speed’, ‘Medium Speed’, ‘Low Speed’ and ‘Stop’to regulate the speed of DC motor.
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