Towards privacy preserving content based image retrieval in cloud computing
Content-Based Image Retrieval applications have been rapidly developed along with the increase in the quantity availability and importance of images in our daily life. However, the wide deployment of Content-Based Image Retrieval scheme has been limited by its the server computation and storage requirement. Privacy-Preserving Content-Based Image Retrieval scheme, which allows the data owner to outsource the image database and Content-Based Image Retrieval service to the cloud, without revealing the actual content of the database to the cloud server. Local features are utilized to represent the images, and Earth Mover's Distance is employed to evaluate the similarity of images. The proposed scheme transforms the Earth Mover's Distance problem in such a way that the cloud server can solve it without learning sensitive information. The security analysis and experiments show the security an efficiency of the proposed scheme using a Secure Hash Algorithm.
Published by: M. Meena, C. S. Kavya, K. Balaji, M. Kishore, P. Suman Kumar
Author: M. Meena
Paper ID: V5I2-1405
Paper Status: published
Published: March 26, 2019
A study of groundwater quality and mapping using GIS techniques in Kodungaiyur, Chennai
Groundwater quality in Kodungaiyur, Chennai district has special significance and needs great attention of all concerned since it is the major alternate source of domestic, industrial and drinking water supply. The present study monitors the groundwater quality maps using GIS techniques for a part of Kodungaiyur. Physico-chemical analysis data of the groundwater samples collected at predetermined locations forms the attribute database for the study, based on which, spatial distribution maps of major water quality parameters are prepared using curve fitting method in Arc View GIS software. GIS has been used extensively to assess the water quality all over the world, advancement of Geographical Information System (GIS) and Spatial Analysis help to integrate the laboratory analysis data with the geographic data and to model the spatial distributions of water quality parameters, most robustly and accurately. The objective of the study is to evaluate the water quality map in Kodungaiyur. For this purpose, Inverse Distance Weighed (IDW) spatial interpolation technique has been used to estimate the spatial distribution of the water quality parameters and WHO standards. The results are compared with WHO permissible limits from the point of view of the suitability of groundwater for human consumption.
Published by: S. Thangaperumal, S. Monica Shree, D. P. Noel Bhuvana Rani
Author: S. Thangaperumal
Paper ID: V5I2-1471
Paper Status: published
Published: March 26, 2019
Impact of CSR Spending on firm’s financial performance
This paper examines the impact of CSR spending on the firm’s financial performance. The government has made CSR spending mandatory by which the organizations can significant contributions to the benefit of the public. The data for the study was collected for 5 years and the study takes into consideration the top ten companies for CSR spending. In order to find out whether CSR spending has an impact, three variables are taken into consideration such as ROA, EPS, Net Profit. Independent Pooled OLS Regression, Fixed Effect and Random effect method was used. The findings were that the Net profit has a significant relationship with the CSR Spending whereas ROA and EPS have no impact.
Published by: Grizel Menezes
Author: Grizel Menezes
Paper ID: V5I2-1504
Paper Status: published
Published: March 26, 2019
Deforestation: A quantitative analysis using remote sensing and GIS
Deforestation and forest degradation are the second leading causes of greenhouse emissions and fossil fuel combustion, which is responsible for over 17% of global carbon dioxide emissions. Deforestation and forest degradation have become an important issue concerning climate change mitigation, highlighted in the Governmental Panel on Climate Change Fourth Assessment Report in 2007. About 75% of the emissions from tropical deforestation and forest degradation have been from developing countries containing large areas of tropical forest, including India. Global initiatives such as the United Nations Framework Convention on Climate Change program on Reducing Emissions. In this thesis, we are mapping about the deforestation for maintaining future of living organisms.
Published by: Thangaperumal S., k.Jaya Surya, Anbin B. Bervin
Author: Thangaperumal S.
Paper ID: V5I2-1508
Paper Status: published
Published: March 26, 2019
Neonatal incubator monitoring system using IoT
There are many innovations occurring in the medical field like needle-free diabetes, robotic check-up, etc. But still, medical accidents are happening in today world due to improper care which even leading to death. We are aware that many infants were dead in recent times due to both human error and machine error. Hence we discuss the advancements that can be brought to the present machines such that the newborn babies would be safe and thus leading to the prevention of accidents that occur in the incubator. To control the accident, need to monitor continuously with better involvement, it is done only through automation. The medical staff can monitor anytime, anywhere. Prevent the infant from the fire and also keep them safe.
Published by: Vignesh T. C., Jai Kumar S., Hari Krishna R., Krishna Raj M.
Author: Vignesh T. C.
Paper ID: V5I2-1521
Paper Status: published
Published: March 26, 2019
A study on impact of stress levels among students using random forest algorithm
Mental health presents one of the greatest and real challenges to the current generation of students. The competitive lifestyles cause them to manage different challenges to achieve their goals and people to be eager to achieve something, causing them to manage multiple frustrations and demands. In this pressurized and highly technical environment, anxiety disorders have slowly occupied their mental health. Nowadays Generalized Anxiety Disorder (GAD) is one of the mental health problems among students. It has been reported that about 2-5% of them. Here our raw data like questionnaire is a valuable resource, but it is underutilized at some circumstances. It could potentially be converted into useful and understandable knowledge via data mining technology. Data mining is capable to identify hidden patterns and relationships that can be used for predicting different disorders. For effective prediction, the random forest approach is one of the classification data mining techniques which produces good predictive characteristics. Therefore, this research adopts a random forest approach to predict different disorders like Generalized Disorder, Anxiety Disorder, Depression, and the accuracy of the predictive result is reported.
Published by: Pinninti Kusuma, Dokkari Siva
Author: Pinninti Kusuma
Paper ID: V5I2-1509
Paper Status: published
Published: March 26, 2019
