Browsing by Author "Garg, Ashish"

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    Monitoring Global Forest Cover Using Data Mining
    (2010-07-14) Mithal, Varun; Boriah, Shyam; Garg, Ashish; Steinbach, Michael; Kumar, Vipin; Potter, Christopher; Klooster, Steven; Castilla-Rubio, Juan Carlos
    Forests are a critical component of the planet's ecosystem. Unfortunately, there has been significant degradation in forest cover over recent decades as a result of logging, conversion to crop,plantation, and pasture land, or disasters (natural or man made) such as forest fires, floods, and hurricanes. As a result, significant attention is being given to the sustainable use of forests. A key to effective forest management is quantifiable knowledge about changes in forest cover. This requires identification and characterization of changes and the discovery of the relationship between these changes and natural and anthropogenic variables. In this paper, we present our preliminary efforts and achievements in addressing some of these tasks along with the challenges and opportunities that need to be addressed in the future. At a higher level, our goal is to provide an overview of the exciting opportunities and challenges in developing and applying data mining approaches to provide critical information for forest and land use management.
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    Pre-processing of the validation data used in the paper titled "Model-Free Time Series Segmentation Approach for Land Cover Change Detection"
    (2011-08-17) Garg, Ashish; Manikonda, Lydia; Kumar, Shashank; Krishna, Vikrant; Boriah, Shyam; Steinbach, Michael; Kumar, Vipin; Toshniwal, Durga; Potter, Christopher; Klooster, Steven
    This report describes the detailed steps of pre-processing the validation data which is used for comparative evaluation of the algorithms proposed in the paper titled "A Model-Free Segmentation Approach for Land Cover Change Detection".
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    Targeted drug delivery and enhanced intracellular release using functionalized liposomes.
    (2009-12) Garg, Ashish
    The ability to target cancer cells using an appropriate drug delivery system can significantly reduce the associated side effects from cancer therapies and can help in improving the overall quality of life, post cancer survival. Integrin a5b1 is expressed on several types of cancer cells, including colon cancer and plays an important role in tumor growth and metastasis. Thus, the ability to target the integrin a5b1 using an appropriate drug delivery nano-vector can significantly help in inhibiting tumor growth and reducing tumor metastasis. The work in this thesis focuses on designing and optimizing, functionalized stealth liposomes (liposomes covered with polyethylene glycol (PEG)) that specifically target the integrin a5b1. The PEG provides a steric barrier allowing the liposomes to circulate in the blood for longer duration and the functionalizing moiety, PR_b peptide specifically recognizes and binds to integrin a5b1 expressing cells. The work demonstrates that by optimizing the amount of PEG and PR_b on the liposomal interface, nano-vectors can be engineered that bind to CT26.WT colon cancer cells in a specific manner and internalize through a5b1-mediated endocytosis. To further improve the efficacy of the system, PR_b functionalized pH-sensitive stealth liposomes that exhibit triggered release under mild acidic conditions present in endocytotic vesicles were designed. The study showed that PR_b functionalized pH-sensitive stealth liposomes, undergo destabilization under mildly acidic conditions and incorporation of the PR_b peptide does not significantly affect the pH-sensitivity of the liposomes. PR_b functionalized pH-sensitive stealth liposomes bind to CT26.WT colon carcinoma cells that express integrin a5b1, undergo cellular internalization, and release their load intracellularly in a short period of time as compared to other formulations. PR_b-targeted pH-sensitive stealth liposomes encapsulating 5-fluorouracil (5-FU) show significantly higher cytotoxicity than the PR_b-targeted inert stealth liposomes and the non-targeted stealth liposomes (both pH-sensitive and inert). The studies demonstrated that optimized PR_b functionalized pH sensitive liposomes have the potential to deliver a payload, such as chemotherapeutic agents, directly to colon cancer cells in an efficient and specific manner.
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    Time series segmentation techniques for land cover change detection
    (2013-05) Garg, Ashish
    Ecosystem-related observations from remote sensors on satellites offer a significant possibility for understanding the location and extent of global land cover change. In this study, we focus on time series segmentation techniques in the context of land cover change detection. We propose a model based time series segmentation algorithm inspired by an event detection framework proposed in the field of statistics. We also present a novel model free change detection algorithm for detecting land cover change that is computationally simple, efficient, non-parametric and takes into account the inherent variability present in the remote sensing data. A key advantage of this method is that it can be applied globally for a variety of vegetation without having to identify the right model for specific vegetation types. We evaluate the change detection capacity of the proposed techniques on both synthetic and MODIS EVI data sets. We illustrate the importance and relative ability of different algorithms to account for the natural variation in the EVI data set.