Vessels Classification in Retinal Images by Graph-Based Approach

The classification of retinal vessels into artery/vein (A/V) is an important phase for automating the detection of vascular changes. This paper presents an automatic approach for A/V classification based on the analysis of a graph extracted from the retinal vasculature. Classifier classifies the entire vascular tree deciding on the type of each intersection point (graph nodes) and assigning one of two labels to each vessel segment (graph links). Final classification of a vessel segment as A/V is performed through the combination of the graph-based labeling results with a set of intensity features. Our method out performs recent approaches for A/V classification. Normal retinal images vessels are segmented using the morphological operations and then using graph trace algorithm for identification the center line of the vessels and trace the pixel values as a feature and use the KNN classifier to classify the feature and assign which is the artery and which is the vein in retinal image. From features we extract the thickness of the vessels to identify the disease details. DOI: 10.17762/ijritcc2321-8169.150316

An Investigation on Strength Development of Cement with Cenosphere and Silica Fume as Pozzolanic Replacement

In the detailed study presented in this paper, an attempt was made to study the strength of cement when cenosphere (CS) and silica fume (SF) were used as replacement. Tests were carried out on mix with cenosphere as replacement for cement which has 12% of constant replacement of silica fume to the mass of cement, and this is made to stabilize the strength which was lost due to addition of cenosphere. From the test results, it was concluded that the strength loss of binder due to replacement of cenosphere can be stabilized by silica fume and still a safe value of strength can be achieved. Furthermore, the strength reduction is due to the consumption of hydration products and cloggy microstructure as observed in this study

Cu‐Oxide Nanoparticles Catalyzed Synthesis of Nitriles and Amides from Alcohols and Ammonia in Presence of Air

The synthesis and functionalization of nitrogen-containing compounds continue to be important due to their wide applications. In particular, the preparation of nitriles and amides applying cost-effective and green methodologies is of central importance because these products represent valuable fine and bulk chemicals and serve as key precursors and central intermediates in organic synthesis and drug discovery as well as materials. Here, the preparation of nitriles and primary amides from alcohols and ammonia by a heterogeneous Cu-catalyzed aerobic oxidation process is reported. The optimal catalyst for this synthesis is based on supported copper oxide-nanoparticles, which are prepared by the impregnation and pyrolysis of simple copper nitrate on carbon. Applying these reusable nanoparticles, various simple, substituted, and functionalized aromatic, heterocyclic, and aliphatic nitriles are synthesized starting from inexpensive and easily accessible alcohols and ammonia in the presence of air. In addition, the synthesis of selected primary amides in a water medium is also performed using these Cu nanoparticles. © 2022 The Authors. Advanced Sustainable Systems published by Wiley-VCH GmbH

Markov Model for Acute Hypertension Analysis

ABSTRACT Accurate determination of usual or average blood pressure (BP) is necessary for the assessment of risk for stroke and coronary heart disease. In this study, we provide a statistically based guide for using results of blood pressure monitoring to resolve this issue. We collected blood pressure samples from 900 people for evaluation of borderline or stage I hypertension. A Markov model is used for calculate the probability that a patient's blood pressure falls within the hypertensive range (>140/90 mm Hg). From the analysis of the results, there is a 15% probability that the patient's "true" average blood pressure is actually in the hypertensive range. This approach may be useful for clinical decision making and also for the design of clinical trials

Signal & Image Processing

Abstract : A hybrid image compression method is proposed in this pape

A Novel Approach for Univariate Outlier Detection

Abstract-In many applications outlier detection is an important task. In the process of Knowledge Discovery in Databases, isolation of outlying data is important. This isolation process improves the quality of data and reduces the impact of outlying data on the existing values. Numerous methods are available in the detection process of outliers in univariate data sets. Most of these methods handle one outlier at a time. In this paper, Grubb’s statistics, sigma rule and fence rules deal more than one outliers at a time. In general, when multiple outliers are present, presence of such outliers prevents us from detecting other outliers. Hence, as soon as outliers are found, removing outlier is an important task. Multiple outliers are evaluated on different data sets and proved that results are effective. Separate procedures are used for detecting outliers in continuous and discrete data. Experimental results show that our method works well for different data