http://localhost:8080/xmlui/handle/123456789/1973 Tue, 23 Jun 2026 06:12:35 GMT 2026-06-23T06:12:35Z http://localhost:8080/xmlui/handle/123456789/3815 Title: Equilibrium and Kinetic Studies of Ni (II) Adsorption using Pineapple and Bamboo Stem Based Adsorbents Abstract: This work addresses the preparation and characterization of inexpensive adsorbents for the removal of Ni (II) from aqueous solutions. Activated carbon based adsorbents have been prepared from plant based biomass resources, namely Pineapple stem (Ananas Comosus) and Bamboo Stem (Bambuseae). Adopting phosphoric acid and heat treatment techniques, it has been observed that the bamboo stem activated charcoal (BSAC) and pineapple stem (PS) adsorbents had a BET surface area of 116 and 11.47m2/g, respectively. FTIR analysis indicated that various surface functional groups (such as C≡N stretching, stretching vibration of C=O, –CH3 wagging and C–O stretching vibration) contribute towards Ni (II) adsorption. Batch mode adsorption experiments were conducted for these adsorbents in the range of 50–300mg/L Ni (II) solution concentration, 2–10 pH, 15–300 min. contact time, and 0.02–0.1 g/50mL dosage. The BSAC adsorbent has been characterized with a metal uptake and %removal of 121.72 mg/g and 92.47, respectively, which corresponds to 45% higher metal uptake than corresponding bamboo based adsorbents presented in the literature. Further experimentation with BSAC enabled to achieve activated charcoal with surface area values similar to that of the commercial activated carbon adsorbent. The bamboo adsorbent has also been evaluated to perform similar to the commercial activated carbon for the removal and recovery of Pd (II) from synthetic electroless plating solutions. Also, a conceptual cost analysis indicated and affirmed towards the potential of the BSAC adsorbents for waste water treatment applications. Thu, 12 Sep 2013 00:00:00 GMT http://localhost:8080/xmlui/handle/123456789/3815 2013-09-12T00:00:00Z http://localhost:8080/xmlui/handle/123456789/3556 Title: De-noising SAR image using filtering techniques Authors: Taras, Surekha H.; Jadhav, Vaidahee U.; Kale, Rohini B.; Kokate, Supriya S. Abstract: In image processing, noise reduction and restoration of image is expected to improve the quality of image. Noise can occur during image capture, transmission etc. In general the result of the noise removal have a strong influence on the quality of the image processing technique. In noise reduction several linear, non-linear filtering method have been proposed. In this paper we present result for different filtering technique used to remove the noise. Filters are best for removing noise from the image. Tue, 15 Apr 2014 00:00:00 GMT http://localhost:8080/xmlui/handle/123456789/3556 2014-04-15T00:00:00Z http://localhost:8080/xmlui/handle/123456789/3544 Title: An Approach to Handle Dynamic Graph Partitioning Authors: Jagdale, Rupali J.; Kamalapur, S. M. Abstract: Large Dynamic Graphs are the big data structures. Now days it is important to study the dynamic graphs as there are different graphs are prepared like facebook, twitter, network analysis. Large Dynamic graphs are difficult to analyze. More memory is required to load this kind of graphs. Large graphs consist of complex data structure. To view these graphs in understandable form one has to make the partitions of the graph. Making partition will create overlapping sub graphs. Overlapping sub graphs will contain repeating nodes or some common nodes. These partitions can easily be analyzed and used for further processing. Dynamic graph always gets the addition or deletion of the contents like edge insertion or deletion and node insertion and deletion. There are updations which can be reflected in the sub graphs. The proposed system works on the same kind of graphs where large graph is partitioned into sub graphs. Thu, 15 Oct 2015 00:00:00 GMT http://localhost:8080/xmlui/handle/123456789/3544 2015-10-15T00:00:00Z http://localhost:8080/xmlui/handle/123456789/3543 Title: A Study to Handle Dynamic Graph Partitioning Authors: Jagdale, Rupali; Kamalapur, S. M. Abstract: Large dynamic graphs are popular and are used in areas like social sites, bio-informatics etc. Huge memory is required to load large graph. Therefore partitioning of large graphs is important in graph analysis. Dynamic updating of the graph can be done with different sub graphs of a large dynamic graph. Different methods of partitioning worked on static graphs. New methods of partitioning can be achieved through combinations of available methods. The proposed work will analyze the large dynamic graph by partitioning it. Also the system will update graph when multiple nodes and edges will be inserted or deleted at runtime. Certain works also focus on generating overlapped nodes in sub graphs. A method to represent large graph in abstract view is also be proposed. Sun, 12 Oct 2014 00:00:00 GMT http://localhost:8080/xmlui/handle/123456789/3543 2014-10-12T00:00:00Z