33 research outputs found
Partial purification and characterization of limonoate dehydrogenase from Rhodococcus fascians for the degradation of limonin
An extracellular limonoate dehydrogenase was purified 10-fold from a cell-free extract of Rhodococcus fascians by ammonium sulfate precipitation, dialysis, and ultrafiltration. This purified dehydrogenase catalyzed theconversion of limonoate to 17-dehydrolimonoate. The enzyme showed optimum activity at pH 8.0 and 40oC, with Km value of 0.9 µM, and requires Zn ions and sulfhydryl groups for catalytic action. The enzyme activity was inhibited by Hg2+ and NaN3 ions. The degradation of limonin (66%) in Kinnow mandarin juice was successfully demonstrated with partiallypurified limonoate dehydrogenase. With scale-up preparation of limonoate dehydrogenase, a successful debittering operation of fruit juices appears feasible.<br /
Retinal Blood Vessel Segmentation Algorithm for Diabetic Retinopathy using Wavelet: A Survey
Blood vessel structure in retinal images have an important role in diagnosis of diabetic retinopathy. There are several method present for automatic retinal vessel segmentation. For developing retinal screening systems blood vessel segmentation is the basic foundation since vessels serve as one of the main retinal landmark features. The most common signs of diabetic retinopathy include hemorrhages, cotton wool spots, dilated retinal veins, and hard exudates. A patient with diabetic retinopathy disease has to undergo periodic screening of eye. For the diagnosis, doctors use color retinal images of a patient required from digital fundus camera. We present a method that uses Gabor wavelet for vessel enhancement due to their ability to enhance directional structures and euclidean distance technique for accurate vessel segmentation. Retinal angiography images are mainly used in the diagnosis of diseases such as diabetic retinopathy and hypertension etc. In diabetic retinopathy structure of retinal blood vessels change that leads to adult blindness. To overcome this problem automatic biomedical diagnosis system is required.The main stage of diabetic retinopathy are Non-proliferative diabetic retinopathy (NPDR) and proliferative diabetic retinopathy (PDR). Eye care specialist can screen vessel abnormalities using an efficient and effective computer based approach to the automated segmentation of blood vessels in retinal images. Automated segmentation reduces the time required by a physician or a skilled technician for manual labeling. Thus a reliable method of vessel segmentation would be valuable for the early detection and characterization of changes due to such diseases. This article presents the automated vessel enhancement and segmentation technique for colored retinal images. Segmentation of blood vessels from image is a difficult task due to thin vessels and low contrast between vessel edges and background. The proposed method enhances the vascular pattern using Gabor wavelet and then it uses euclidean distance technique to generate gray level segmented image.
DOI: 10.17762/ijritcc2321-8169.15030
Comparative studies on age and growth patterns of cultivated and wild Catla catla (Hamilton)
144-149Catla catla (Hamilton) is one of the fastest growing Indian
major carps (IMCs) with increasing market demand. Consistent
demand and exploitation invites the attention of ichthyologists for
its conservation strategies. Age and growth studies play a pivotal
role for managing the fishery stocks in different water bodies.
Here, we studied the age and growth patterns using opercula of
both farm grown as well as the wild grown C. catla adopting
standard methodologies. Wild specimens were caught from
Harike wetland (Ramsar site) and the cultivated one from a farm
at Dhudike in Punjab. High value of correlation coefficient ‘r’
0.976 (wetland) and 0.983 (farm) reveals the strong relationship in
total length and operculum radius of the fish. C. catla achieved
average total length from wetland and farm, respectively at 1st
(273.44 mm) 2nd (427.44 mm) 3rd (525.49 mm) 4th (624.52 mm) 5th
(744.98 mm) 6th (813.62 mm) and 1st (282.1 mm) 2nd (463 mm) 3rd
(601.7 mm) year of age of opercular bones study. The growth
parameters such as, index of species average size (φh) 135.6
(wetland) and 200.6 (farm), growth constant (Clt) showed two
growth phases from both localities i.e. sexual immaturity up to 2
years and sexual maturity afterwards. Whereas, growth
characteristic (Cth) has revealed irregular growth pattern at
wetland in comparison to growth of fish from farm. The results of
this study concluded that the fish experienced more growth from
the farm due to better and controlled conditions but, in wetland
surrounding conditions were observed to be unfavourable for
survival of the fish C. catla
Analysis of Intrusion Detection Tools for Wireless Local Area Networks
Summary Intrusion-detection systems endeavor at detecting attacks against networks or, in general, against information systems. Undeniably, it is convoluted to provide provably secure network and to maintain them in such a secure state during their lifetime and utilization. Sometimes, legacy or operational constraints do not even allow the definition of a fully secure network. Therefore, intrusion detection systems have the task of monitoring the usage of such systems to detect any apparition of insecure states. They detect attempts and active misuse either by legitimate users of the systems or by external parties to abuse their privileges or exploit security vulnerabilities. [1] This paper covers overview and analysis of Intrusion Detection Systems tools for detecting intrusions in Wireless Local Area Networks (WLAN). Twenty five research and commercial systems are evaluated based on some common parameters. A taxonomy especially designed for intrusion detection systems (IDS) is utilized to compare and evaluate different features and aspects of the products. This paper identifies a number of important design and implementation issues which provide a framework for evaluating or deploying intrusion detection systems
Delayed hemolytic reaction due to anti Jk a alloimmunization
ABSTRACT Introduction: Kidd blood group system has a special importance in transfusion medicine as the antibodies to Kidd antigens tend to go down to undetectable levels but show an anamnestic response on exposure through pregnancy or blood transfusion and cause hemolytic transfusion reaction, most commonly delayed transfusion reaction. Case Report: We report a patient who developed alloantibodies to 'Kidd a' antigen leading to delayed hemolytic transfusion reaction. Conclusion: We emphasize the steps for detecting these antibodies and the precautions to be taken once these antibodies are identified
Modified SIFT Descriptors for Face Recognition under Different Emotions
The main goal of this work is to develop a fully automatic face recognition algorithm. Scale Invariant Feature Transform (SIFT) has sparingly been used in face recognition. In this paper, a Modified SIFT (MSIFT) approach has been proposed to enhance the recognition performance of SIFT. In this paper, the work is done in three steps. First, the smoothing of the image has been done using DWT. Second, the computational complexity of SIFT in descriptor calculation is reduced by subtracting average from each descriptor instead of normalization. Third, the algorithm is made automatic by using Coefficient of Correlation (CoC) instead of using the distance ratio (which requires user interaction). The main achievement of this method is reduced database size, as it requires only neutral images to store instead of all the expressions of the same face image. The experiments are performed on the Japanese Female Facial Expression (JAFFE) database, which indicates that the proposed approach achieves better performance than SIFT based methods. In addition, it shows robustness against various facial expressions
Drought stress detection technique for wheat crop using machine learning
The workflow of this research is based on numerous hypotheses involving the usage of pre-processing methods, wheat canopy segmentation methods, and whether the existing models from the past research can be adapted to classify wheat crop water stress. Hence, to construct an automation model for water stress detection, it was found that pre-processing operations known as total variation with L1 data fidelity term (TV-L1) denoising with a Primal-Dual algorithm and min-max contrast stretching are most useful. For wheat canopy segmentation curve fit based K-means algorithm (Cfit-kmeans) was also validated for the most accurate segmentation using intersection over union metric. For automated water stress detection, rapid prototyping of machine learning models revealed that there is a need only to explore nine models. After extensive grid search-based hyper-parameter tuning of machine learning algorithms and 10 K fold cross validation it was found that out of nine different machine algorithms tested, the random forest algorithm has the highest global diagnostic accuracy of 91.164% and is the most suitable for constructing water stress detection models