Quality of life among cancer patients receiving treatment in the Regional Cancer Hospital, IGMC, Shimla, Himachal Pradesh
Cancer is characterized by uncontrolled growth and spread of cancerous cells. It can be defined as a disease in which there is uncontrolled growth of abnormal cells by disregarding the normal rules of cell division. Normal cells are constantly providing signals that dictate whether the cell should divide, differentiate into another cell, or die Cancer cells develop a degree of autonomy from these signals, resulting in uncontrolled growth and proliferation. The aim of the study to assess the quality of life and improve the quality of life among cancer patients by distributing informational booklet. The descriptive research design was adopted to collect data from patients with cancer in Regional Cancer Hospital IGMC, Shimla, and using convenience sampling technique. Data was collected by the EORTC questionnaire. The pilot study findings showed that 70% of cancer patients have an average quality of life.30 % of cancer patients were below the average quality of life.
Published by: Pratibha Sharma, Kavita Verma, Sangeeta Sharma
Author: Pratibha Sharma
Paper ID: V5I4-1224
Paper Status: published
Published: July 22, 2019
Use of Triaxial GeoGrids for subgrade stabilisation and pavement optimisation
Triaxial Geo Grids were first founded in the year of 2007 so as to enable civil engineers to stabilize granular layers subjected to dynamic and static loads. Triaxial geogrid is having a 360° isotropic tensile properties, wherein on laying off the geogrid the aggregates interlock within a triangular slot, for which the efficient deep fibers of the triaxial geogrids assists in confining the aggregate particles. This, in turn, stabilizes the layer and enhances the performance of the subgrade resulting in pavement optimization. Prior to surfacing in the global market triaxial geogrids were under six years of development with a focus on improving the performance under trafficking of the granular layers in which they were included. This involved the use of full-scale testing facilities such as the Transport Research Laboratory (TRL) in the UK. This paper provides a general idea on the possibility to implement Triaxial Geogrids to form a mechanically stabilized layer (MSL) so as to save cost in term of material and construction effort especially in areas where the effective CBR of soil is found to be much below the permissible limit as per IRC specifications thereby extending the design life of the pavement structure. In addition, the proposed MSL would create a flexural stiff platform where the effects of the variable quality of support from the foundation soil can be smoothed out.
Published by: Sayan Mukherjee, Siddesh Pai
Author: Sayan Mukherjee
Paper ID: V5I4-1232
Paper Status: published
Published: July 20, 2019
Online fault detection system for cooling tower in power plant by using PLC-SCADA
This paper provides a big approach for power plant automation system of Fault Detection in cooling towers on the basis of PLC and SCADA. The techniques and program which are used in this paper are helpful to detect the fault occurs inside the cooling tower of the thermal power plant. A cooling tower is also used for removing the heat from the condensate water which is flowing through the pipes of the tower so that it is called a heat removal system. Water to be cooled and then returned for use in recirculation through the system in the cooling tower. The New fault detection and fault finding system based on upcoming data from the detection sensors which are used for fault detection. In this system, a combination of PLC internal program and visualization of fault on SCADA window gives easy fault finding and clearing process. In this paper, there are two software used for finding the faulty condition (PLC - Allen Bradley- RS Logix 500 and SCADA- Wonderware Intouch .) RS Logix 500 uses ladder logic for finding the faults and Wonderware Intouch used to show faulty condition on the windows. This paper includes three types of failure of fault detection in cooling tower which are major caused in steam power Plant during operation. In this whole process SCADA is used for online visualization of faulty condition..
Published by: Abhijeet Raut, Swapnil Mohod
Author: Abhijeet Raut
Paper ID: V5I4-1230
Paper Status: published
Published: July 20, 2019
3-DPGR (3-level Daubechies wavelet, PCA, GLCM and RBF Kernal) method used for brain MRI categorization
Abnormal growth of cells in the brain is called a brain tumor. A brain tumor consists of a collection of abnormally functioning brain cells that have begun to grow and reproduce inappropriately. The uncontrolled growth of a group of cells compresses and damages normal brain structures, which causes a variety of neurological symptoms. According to the reports of National Cancer Institute, Primary brain tumors are the leading cause of tumor cancer deaths in children, now surpassing acute lymphoblast leukemia and are the third leading cause of cancer death in young adults ages 20 to 39. There are more than 120 different types of brain tumors, making effective treatment very complicated. As per classification system defined by the World Health Organization (WHO), a brain tumor is named for the cell type of origin. Brain tumors can either originate from within the brain or from cancer cells that have metastasized from other organs or tissues. Various techniques are developed in the past to detect brain tumor. This research work proposed a Modified Technique for Brain MRI Categorization using 3-DPGR (3-level Daubechies wavelet, PCA, GLCM and RBF Kernal) Method.
Published by: Bharti, Bharti, Manit Kapoor, Dr. Naveen Dhillon
Author: Bharti
Paper ID: V5I4-1163
Paper Status: published
Published: July 19, 2019
Determinants of customer satisfaction of E-shopping: A study on special reference to Idukki District
Online shopping is the process whereby consumers directly buy goods, services etc. from a seller interactively in real-time without an intermediary service over the internet. Online shopping is the process of buying goods and services from merchants who sell on the Internet. Since the emergence of the World Wide Web, merchants have sought to sell their products to people who surf the Internet. Shoppers can visit web stores from the comfort of their homes and shop as they sit in front of the computer. Consumers buy a variety of items from online stores. As far as e-Commerce business is concerned, ensuring a high level of online customer satisfaction remains an integral, eternal element in achieving and maintaining long-term business success. This study is intended to study customer satisfaction using E-commerce based on a sample from Idukki district. And also analyze and summaries the specific elements of E-commerce customer satisfaction and the various elements of customers expectations and perceptions
Published by: Jinu Joy
Author: Jinu Joy
Paper ID: V5I4-1215
Paper Status: published
Published: July 19, 2019
A review paper on: Heart disease data set analysis using data mining classification techniques
Health care industry is one of the fastest growing industries in 21st century. This is the era of increasing health problems and chronic diseases. The major chronic diseases faced world over are cardio vascular diseases such as stroke and heart attacks. Heart disease is one of the common causes of death worldwide. According to WHO as many as, 17.9 Million people die of Cardio Vascular Diseases each year, 31% of all the deaths worldwide. Diagnosis of the disease is one of the most important task of medical science. Medical professionals need a decision support system for early prediction of heart diseases with good accuracy rate which can be achieved with the help of data mining techniques. The healthcare industry produces large amount of data each day. Data mining helps in extracting hidden information and patterns from a large and complex database which is helpful in making decisions. The main objective of this research is to develop a heart disease prediction system by using data mining techniques with a good accuracy rate. Here we have a pre processed data set consisting of 303 records and 14 predictors such as Gender, blood pressure, chest pain type etc. as input for BPN and Decision Tree. In this research we will compare two data mining algorithms: Decision tree and Back propagation network Algorithm and predict the presence or absence of heart disease in a patient. The algorithm with highest accuracy rate will be considered good for heart disease prediction in hospitals.
Published by: Shreya Kalta, Keshav Kishore, Aman Kumar
Author: Shreya Kalta
Paper ID: V5I4-1195
Paper Status: published
Published: July 19, 2019
