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Thesis

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2014 - 20175
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Subject: Computer Science and Engineering × End date: 2017 × Type: Thesis × Thesis Type: M.Tech ×
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Now showing 1 - 5 of 5
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    Development of software to determine the maturity level of plum using image processing techniques
    (Punjab Agricultural University, Ludhiana, 2017) Harpuneet Kaur; Sawhney, B. K.
    Maturity is the key factor which determines the storage life and ripening quality of fruits. In order to provide marketing flexibility and to ensure the acceptable eating quality to the buyer it is very crucial to determine the right maturity stage. Maturity indices are also important for trade regulation, marketing strategy and for efficient use of labor and resources. The proposed system is based on the implementation of image processing techniques using digital images of different maturity stages of the plum. The external quality features like color, texture and size have been analyzed with MATLAB Image Processing Toolbox. Color feature has been extracted by using mean RGB values. Entropy, Local Binary Pattern and Discrete Cosine transformation have been used for extracting textural features. Correlation coefficients between images of various categories were recorded to determine the most dominant factor for classification. Multi Attribute Decision Making theory has been used for taking final decision. The developed system accurately determines the maturity level. Results indicated that color is the most dominant factor for classifying the plums according to maturity level. When the length and width computed from application were compared with the manual readings, the error percentage was less than 2.4%.
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    Development of software to estimate woody volume of a live tree
    (Punjab Agricultural University, Ludhiana, 2017) Singla, Nikita; Derminder Singh
    Tree volume is one of the oldest areas of interest and is a crucial task in tree management system. Estimating the woody volume of a live tree is important for economic, scientific purposes and provides a tool to researcher/grower. It provides the useful information about the commercial value of wood to the potential buyer/seller. Manual methods are being used largely to calculate woody volume of a tree. These methods are based on different log rules, cumbersome and laborious. The present work proposed a digital image processing technique to estimate the woody volume of a live tree. The developed program successfully determines the woody volume of standing tree trunk with MATLAB image processing techniques. In this method three parameters an individual tree were extracted from digital images of the tree. Calibration factor was also calculated to make the method independent of camera distance from the tree. The method was tested on several samples of trees and compared to experimental results. This software generates information about height, diameter and volume of the tree. The percentage error of height, diameter and volume of standing tree by proposed method was found to be less than 6.65%.
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    Parallel Implementation & Performance Evaluation of BLAST Algorithm on LINUX Cluster
    (Punjab Agricultural University, Ludhiana, 2014) Dhankher, Nisha; Gupta, O.P.
    BLAST is an efficient heuristic based algorithm, used for calculating local alignment between biological sequences. Due to exponential growth in the size of genomic databases, traditional techniques of sequence search proved to be slow. To address the above problem, an open source and parallel version of BLAST called mpiBLAST was developed by the programmers. In mpiBLAST, the master process distributes the database fragments among worker nodes to compute the sequence search in parallel. As merging and writing of the results is done sequentially by the master process, it would create performance bottleneck with increasing number of processors and varying database sizes. To handle this high nonsearch overhead, mpiBLAST-PIO was introduced. This study describes the optimized and extended version of mpiBLAST called mpiBLAST-PIO. The goal of this research was to investigate the performance of parallel implementation of BLAST in comparison to sequential NCBI-BLAST by measuring Speedup and efficiency on HPC Platform using Infiniband. Different options of mpiBLAST-PIO were activated that helped in understanding the optimal parameters for achieving highly scalable parallel BLAST implementation. The results found that parallel-writing of the results, can evolve as an efficient solution when high-performance parallel file system is available.
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    Quantised Compressive Sampling using Genetic Algorithm in Dense Wireless Sensor Networks
    (Punjab Agricultural University, Ludhiana, 2014) Preetkamal Singh; Gupta, O.P.
    Due to increasing exchange of data in services such as internet, e-mail and data file transfer; wireless networking has gone through an exponential growth. The wireless senor network is made of small or large number of tiny nodes which have limited battery power. Source node can easily route the data to destination if it has sufficient battery power. If the destination node is far away from the source node, then the source node should have large battery power to transmit data. But after few transmissions a threshold level comes, when that source node is dead and no node is present for transmission. And the overall lifetime of network will decrease. In wireless sensor network, the nodes have limited battery capacity and limited initial energy that is consumed at different rates. The lifetime of network is defined as the time until the first node fails. Some of the major challenges in wireless sensor networks are to minimize the energy consumption, end- to- end delay and to increase the throughput of sensor node to enhance the lifetime of sensor network. The routing protocols have great impact on the lifetime of sensor network. During research work, the objective has been confined to increase the lifetime of the network using the HUFFMAN’s data compression technique and then Genetic Algorithm is used further to transmit data to the Base Station. It has been found that network lifetime is highly enhanced in terms of increased number of rounds. The data compression is being applied on the cluster head which aggregates the data being collected from all other sensor nodes. So in this way the big amount of redundant data is being removed at the cluster head level. The simulation has been performed in MATLAB software. The work is being performed in the homogeneous environment. The balance in the energy consumption is also achieved by performing this data compression technique. Because it reduces the extra load on the cluster head which makes its life much longer as compare to earlier one. In the future, the work will be focused to consider heterogeneous network and mobility of sink can also be introduced to investigate the performance of proposed technique.
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    ThesisItemOpen Access
    Implementation and Performance Analysis of ClustalW Algorithm using Parallel and Distributed Computing
    (Punjab Agricultural University, Ludhiana, 2014) Jasrotia, Swati; Din, Salam
    Parallel version of bioinformatics applications can speed up the analysis of large scale sequence data, specially sequence alignment. sharing of distributed computing resources and data with the use of parallel version softwares on high performance computing is an emerging step. Clusters provide an excellent platform for solving a range of parallel and distributed applications in both scientific and commercial areas. Personal computer clusters are replacing the mainframe systems / super computers because of its cost effectiveness. In this paper, the performance result of parallel version ClustalW software is recorded on personal computer cluster with the help of an open source rocks toolkit. An easy to deploy, contract/expand, manage and scalable distributed environment is proposed and built for bioinformatics applications. The experimental results show that multiple sequence alignment of protein sequences with ClustalW software on rocks distributed environment gives high efficiency and speed up. It also shows cluster platforms are excellent alternative to access to super computing due to its price to performance ratio