Manuscripts

Recent Papers

To Study Aetiology of Prostatomegaly and Corelations between Symptoms and Degree of Prostatomegaly

Dr. Noopur Priya (senior resident,general surgery), Dr.Gaurav Sali(neurosurgery resident),Dr.Kiran Kher (professor, surgery department); department of surgery,avbrh Prostatomegaly is one of the most common conditions affecting the ageing male. The effects of prostatomegaly on voiding function, however, vary greatly from patient to patient and thus make measuring its impact a challenging task.Three most common causes of prostate enlargement are benign prostatic hyperplasia (BPH), prostate cancer and prostatitis. Prostatomegaly affects the function of the urethra, urinary bladder, kidney leading to symptoms like Frequency of micturition, Nocturia, Dysuria, Hesitancy, Urgency, Lack of force and dribbling at the end, Haematuria, Retention, and symptoms of chronic renal insufficiency. Out of 166 patients enrolled in our study maximum patients were having grade III prostatomegaly.Benign Prostatic Hyperplasia was the commonest amongst all patients. The commonest symptom was increased frequency of micturition in our patients.AUA score was moderate to severe in grade I prostatomegaly patients while mild to moderate in grade III prostatomegaly patients, indicating that the symptom severity does not vary with respect to grades of the prostatomegaly.DRE showed all signs of malignancy in cases of carcinoma of the prostate.The age-adjusted Sr.PSA level was normal for benign disease of prostate and higher in carcinoma of the prostate.Carcinoma of the prostate was present mainly in grade III prostatomegaly patients.

Published by: Dr. Noopur Priya

Author: Dr. Noopur Priya

Paper ID: V3I2-1475

Paper Status: published

Published: April 8, 2017

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Complexity of Cuckoo Hashing

We will present a simple cuckoo hashing with an example of how it works. Along with it, we will present an algorithm to find loop in cuckoo hashing

Published by: Nitesh Gupta, Dr. Om Prakash

Author: Nitesh Gupta

Paper ID: V3I2-1418

Paper Status: published

Published: April 7, 2017

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CAD Diagnosis Using PSO, BAT, MLR And SVM

Coronary artery disease (CAD) is a most common type of heart disease. CAD happen when a blood clot cuts off the heart’s blood supply, causing permanent heart damage. Diagnosis of CAD can be done using angiography, echocardiogram, electrocardiogram, which are complex methods. Therefore, studies are done to predict CAD using machine learning algorithms. This study proposes, feature selection by particle swarm optimization(PSO) and Bat algorithms, clustering using K-means and classification using Multinomial logistic regression (MLR) and support vector machine (SVM) algorithms. This technique is cross checked upon 14 attributes with 303 instances. A benchmark dataset from Cleveland heart disease data is used. The Bat-SVM model achieves the highest prediction accuracy of 97 %. The proposed model has an increased accuracy from the existing systems.

Published by: Hinduja .R, Mettildha Mary .I, Ilakkiya .M, Kavya .S

Author: Hinduja .R

Paper ID: V3I2-1431

Paper Status: published

Published: April 7, 2017

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Intelligent Street Light

This project efficiently defines the control of the street lighting system and thereby saving electricity as well as helping in monitoring other aspects of the environment which are a major concern worldwide. It also describes the use of A reader module for vehicle monitoring and control. The proposed system also has vehicle theft control is also integrated into the system. The proposed system also helps to monitor pollution levels, carbon emission also the sound levels of the vehicles in traffic. The efficiency of the system is designed such that it can be readily installed in present on road conditions with the extra cost of controlling computer and the sensors.

Published by: Mrs. Anuja A. Borkar, Mr. Mandar Patil, Mr. Vedant Jangam, Mr. Akshay Adkurkar, Mr. Rishabh Narkar

Author: Mrs. Anuja A. Borkar

Paper ID: V3I2-1446

Paper Status: published

Published: April 7, 2017

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Automatic Mammogram Tumor Detection Using Supervised Learning Method

Breast cancer is the most occupied type of cancer in women that caused the most deaths among women. The early detection of breast cancer is more important for the chances of survival of the patient. This work has mainly four modules: Pre-processing, Segmentation is carried out by Active Contour algorithm and Advanced K-means algorithm, Feature extraction is done by Gray Level Co-occurrence Matrix (GLCM), Expectation Maximization (EM) and Principle Component Analysis (PCA), finally classification is done by Random Forest Classification. To achieve the objective of this work, MIAS (Mammographic Image Analysis Society) and IN breast databases are used as input images. The Accuracy achieved in this system is 95.83%.

Published by: Chandana Saipriya. V, Dhanalakshmi. B, Gnanasoundari. S, Mercy Therasa. M, Hemadevi. J

Author: Chandana Saipriya. V

Paper ID: V3I2-1450

Paper Status: published

Published: April 7, 2017

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Feature and Processing Of Recognition of Characters, Words & Connecting Motions

Recognition & Modeling of characters, words & connecting motions is accomplished based on six-degree-of-freedom hand motion data. We address air-writing on two levels: motion characters and motion words. Isolated air-writing characters can be recognized similar to motion gestures although with increased sophistication and variability. For motion word recognition in which letters are connected and superimposed in the same virtual box in space, we build statistical models for words by concatenating clustered ligature models and individual letter models. A hidden Markov model is used for air-writing modeling and recognition. We show that motion data along dimensions beyond a 2-D trajectory can be beneficially discriminating for air-writing recognition

Published by: Deepa .D, R. Dharmalingam

Author: Deepa .D

Paper ID: V3I2-1455

Paper Status: published

Published: April 7, 2017

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