Authorized Deduplication of Files in Cloud Environment
Data deduplication is one of vital information compression procedures for disposing of copy duplicates of rehashing information, and has been generally utilized as a part of cloud storage to lessen the measure of storage room and spare data transfer capacity. To secure the classification of sensitive information while supporting deduplication, the convergent encryption method has been proposed to encode the information before outsourcing. To better ensure information security, this paper makes the primary endeavor to formally address the issue of approved information deduplication. Not quite the same as customary deduplication frameworks, the differential benefits of clients are additionally considered in copy check other than the information itself. We likewise display a few new deduplication developments supporting approved copy check in a half and half cloud design. Security examination exhibits that our plan is secure as far as the definitions indicated in the proposed security show. As a proof of idea, we execute a model of our proposed approved duplicate check plan and direct testbed experiments utilizing our model. We demonstrate that our proposed authorized duplicate check scheme brings about negligible overhead contrasted with normal operations.
Published by: Shrikrishna Kerur, Dr. Anand N. Diggikar
Author: Shrikrishna Kerur
Paper ID: V3I4-1234
Paper Status: published
Published: July 25, 2017
Novel Fuzzy logic controller based Multivariable Energy Management Strategy for Standalone DC Micro grids
Due to substantial generation and demand fluctuations in standalone green electricity control schemes are becoming crucial for the electricity sharing and voltage regulation functions. The classical power management strategies rent the maximum energy factor monitoring (MPPT) algorithms and rely on batteries in case of possible extra or deficit of strength. However, so as to recognize constant present day-constant voltage (IU) charging regime and growth the life span of batteries, electricity control strategies require being more flexible with the power curtailment feature. The paper proposes a method for the hybrid solar photovoltaic and wind energy device in Battery management for stand-alone applications. Battery charging manner is non-linear, time-varying with an enormous time delay so it is difficult to achieve the best energy management performance by using traditional control approaches. A fuzzy manipulate approach for battery charging or discharging utilized in a renewable power generation system is analysed in the paper. To improve the life cycle of the battery, fuzzy control manages the desired state of charge (SOC). A fuzzy logic-based controller for use for the Battery SOC manipulate of the designed hybrid system is proposed and in comparison with a classical PI controller for the overall performance validation. The whole designed device is modelled and simulated the use of MATLAB/Simulink Environment.
Published by: Navneet Singh Saini, Davesh Bindal
Author: Navneet Singh Saini
Paper ID: V3I4-1220
Paper Status: published
Published: July 25, 2017
Classification of Leaf Disease Based On Multiclass SVM Classifier
India, the country where the main source of income is from agriculture. Farmers grow variety of crops based on their requirement. Since the plants suffer from disease, the production of crop decreases due to infections caused by several types of diseases on its leaf, fruit and stem. Leaf diseases are mainly caused by bacteria, fungi, virus etc. Diseases are often difficult to control. Diagnosis of the disease should be done accurately and proper actions should be taken at the appropriate time. Image Processing is the trending technique in detection and classification of plant leaf disease. This work describes how to automatically detect leaf diseases. The given system will provide fast, spontaneous, precise and very economical method in detecting and classifying leaf diseases. This paper is envisioned to assist in the detecting and classifying leaf diseases using Multiclass SVM classification technique. First the affected region is discovered using segmentation by K-means clustering, then features (color and texture) are extracted. Lastly, classification technique is applied in detecting the type of leaf disease. The proposed system effectively detects and also classify the disease with accuracy of 92%.
Published by: Pooja Kulinavar, Vidya I. Hadimani
Author: Pooja Kulinavar
Paper ID: V3I4-1205
Paper Status: published
Published: July 25, 2017
Analysis of Air Pollution
This research paper is an attempt towards analyzing real time air pollution data collected by PAQS sensor devices from some key locations in Bangalore. Air pollution in most of the metropolitan cities in India is turning out to be a major threat to our environment and hazardous to our health. Many infections and diseases related to lungs and throat are caused by the polluted air we breathe. There is a growing need to conduct regular measurements of air quality data and analyze it.
Published by: Rajeshwari K. Rai
Author: Rajeshwari K. Rai
Paper ID: V3I4-1221
Paper Status: published
Published: July 25, 2017
Non Destructive Method by Penetrant Testing
This paper presents results from a literature review of defect characteristics essential for non-destructive testing (NDT). Most of the major NDT methods are included in the study – Penetrant Testing (PT), The study was performed by means of searching in scientific databases, , etc. Mainly, the following It is concluded that for Penetrant testing, the defect geometry, the defect size and the defect. A number of investigations address the relationships between the defect parameters like roller depth, surface defects Also the phenomena of the electrical contacts between the defect surfaces (for a crack) was studied. Defect parameters that are essential to the quality of Penetrant testing are defect position in the object (includes the depth), orientation, size, crack surface roughness, closure and tip radius. This investigation has been focused on those parameters that are not that easy to reconstruct and only briefly discussed the influence on the signal response due to defect position, orientation and size.
Published by: Shyamji, Dr. Suresh Prasad
Author: Shyamji
Paper ID: V3I4-1219
Paper Status: published
Published: July 25, 2017
Effectively Reconstructing the Routing Paths in Sensor Networks
In wireless sensor networks, sensor nodes are usually self-organized or self sorted, delivering data to a central sink in a multi-hop manner. Reconstructing the per-packet routing path enables fine-grained diagnostic analysis and performance optimizations of the network. The performances of existing path reconstruction approaches like MNT, however, goes down rapidly in large scale networks with loss links or failed links. We present Pathfinder, a vigorous path reconstruction method against packet losses as well as routing dynamics. At the node side, Pathfinder exploits temporal correlation between a set of packet paths and efficiently compresses the path information using path difference. At the sink side, Pathfinder infers packet paths from the compressed information and employs intelligent path speculation to reconstruct the packet paths with high reconstruction ratio. We propose a novel analytical model to analyze the performance of Pathfinder. We further calculate Pathfinder compared with two most related approaches using traces from a large scale deployment and extensive simulations by means of graph. Results show that Pathfinder outperforms existing approaches, achieving both high reconstruction ratio and low transmission cost compared to MNT.
Published by: Mohammad Peer M. Shaikh, Prof. Anand D. Vaidya
Author: Mohammad Peer M. Shaikh
Paper ID: V3I4-1218
Paper Status: published
Published: July 24, 2017
