International Journal of Computer and Applications

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Remote Sensing And Image Interpretation

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U.s. agency for international development

Magnetic sorting using magnetic beads has become a routine methodology for the separation of key cell populations from biological suspensions. Due to the inherent ability of magnets to provide forces at a distance, magnetic cell manipulation is now a standardized process step in numerous processes in tissue engineering, medicine, and in fundamental biological research. Herein we review the current status of magnetic particles to enable isolation and separation of cells, with a strong focus on the fundamental governing physical phenomena, properties and syntheses of magnetic particles and on current applications of magnet-based cell separation in laboratory and clinical settings. We highlight the contribution of cell separation to biomedical research and medicine and detail modern cell-separation methods (both magnetic and non-magnetic). In addition to a review of the current state-of-the-art in magnet-based cell sorting, we discuss current challenges and available opportunities for further research, development and commercialization of magnetic particle-based cell-separation systems.

http://iopscience.iop.org/article/10.1088/0034-4885/78/1/016601/pdf

Fundamentals and application of magnetic particles in cell isolation and enrichment: a review

Close range hyperspectral imaging of plants: A review

Peptide fragments from alfalfa mosaic virus involved multiple antigenic components directing and empowering the immune system to protect the host from infection. MHC molecules are cell surface proteins, which take active part in host immune reactions and involvement of MHC class-I & II in response to almost all antigens. Coat protein of alfalfa mosaic virus contains 221 aa residues. Analysis found five MHC ligands in coat protein as 64-LSSFNGLGV-72; 86- RILEEDLIY-94; 96-MVFSITPSY-104; 100- ITPSYAGTF-108; 110- LTDDVTTED-118; having rescaled binding affinity and c-terminal cleavage affinity more than 0.5. The predicted binding affinity is normalized by the 1% fractil. The MHC peptide binding is predicted using neural networks trained on c-terminals of known epitopes. In analysis predicted MHC/peptide binding is a log transformed value related to the IC50 values in nM units. Total numbers of peptides found are 213. Predicted MHC binding regions act like red flags for antigen specific and generate immune response against the parent antigen. So a small fragment of antigen can induce immune response against whole antigen. This theme is implemented in designing subunit and synthetic peptide vaccines. The sequence analysis method allows potential drug targets to identify active sites against plant diseases. The method integrates prediction of peptide MHC class I binding; proteosomal c-terminal cleavage and TAP transport efficiency.

Prediction of MHC binding peptides and epitopes from alfalfa mosaic virus.

Recent advances in the sensors technology for imaging spectroscopy coupled with high computing power, raise the demand to develop the algorithms for processing and analysis of hyperspectral data for various applications. Well known techniques and algorithms are available for processing multispectral data in the literature. Researchers tried to use similar approaches for hyperspectral data analysis and succeeded up to some extent. Several techniques for atmospheric correction, dimensionality reduction, endmember extraction and classification has been developed and reported accordingly. To process and evaluate the hyperspectral data for domain applications require generalized framework. This article critically reviews most of the existing hyperspectral data processing and analysis approaches and gives generalized framework. Which offers considerate view for future potential and focuses emerging challenges in the development of robust algorithms for hyperspectral data processing and analysis.

A Research Review on Hyperspectral Data Processing and Analysis Algorithms

Terrestrial Laser Scanners (TLS) are used to get dense point samples of large object’s surface. TLS is new and efficient method to digitize large object or scene. The collected point samples come into different formats and coordinates. Different scans are required to scan large object such as heritage site. Point cloud registration is considered as important task to bring different scans into whole 3D model in one coordinate system. Point clouds can be registered by using one of the three ways or combination of them, Target based, feature extraction, point cloud based. For the present study we have gone through Point Cloud Based registration approach. We have collected partially overlapped 3D Point Cloud data of Department of Computer Science & IT (DCSIT) building located in Dr. Babasaheb Ambedkar Marathwada University, Aurangabad. To get the complete point cloud information of the building we have taken 12 scans, 4 scans for exterior and 8 scans for interior facade data collection. There are various algorithms available in literature, but Iterative Closest Point (ICP) is most dominant algorithms. The various researchers have developed variants of ICP for better registration process. The ICP point cloud registration algorithm is based on the search of pairs of nearest points in a two adjacent scans and calculates the transformation parameters between them, it provides advantage that no artificial target is required for registration process. We studied and implemented three variants Brute Force, KDTree, Partial Matching of ICP algorithm in MATLAB. The result shows that the implemented version of ICP algorithm with its variants gives better result with speed and accuracy of registration as compared with CloudCompare Open Source software.

/pdf/evaluation-of-partially-overlapping-3d-point-cloud-s-4lr36iqdsq.pdf

Evaluation of partially overlapping 3d point cloud's registration by using icp variant and cloudcompare

In this paper we propose the Support Vector Machine (SVM) based recognition scheme towards the recognition of Gujarati handwritten numerals. The preprocessing is done considering morphological operations. For computing the features, each isolated numeral is segmented into blocks. These blocks create base for four sets of features. Then we derived affine invariant moments as features. The features obtained from these blocks are fed to SVM classifier. We obtained the recognition rate of 91% approximately. Keywords- handwritten character recognition, affine invariant moments, support vector machine, Gujarati script

Support vector machine based gujarati numeral recognition

Heart rate variability (HRV) is an intrinsic property of heart and active research domain of the medical research community since last two decades. But in biometrics it is still in its infancy. This article is intended to present the state of art into heart-based biometrics and also explore the possibility of using HRV in biometric recognition systems. Subsequently, we designed hardware and software for data collection and also developed software for HRV analysis in Matlab, which generates 101 HRV Parameters (Features) using various HRV analysis techniques like statistical, spectral, geometrical, etc., which are commonly used and recommended for HRV analysis. All these features have their relative significance in medical interpretations and analysis, but among these 101 features reliable features that can be useful for biometric recognition were unknown; therefore feature selection becomes a necessary step. We used five different wrapper algorithms for feature selection, and obtained 10 reliable features out of 101. Using the proposed 10 HRV features, we used KNN for classification of subjects. The classification test gave us encouraging results with 82.22 % recognition rate.

Karbhari V. Kale

Papers

Prediction of MHC binding peptides and epitopes from alfalfa mosaic virus.

A Research Review on Hyperspectral Data Processing and Analysis Algorithms

Evaluation of partially overlapping 3d point cloud's registration by using icp variant and cloudcompare

Support vector machine based gujarati numeral recognition

Heart-Based Biometrics and Possible Use of Heart Rate Variability in Biometric Recognition Systems