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Case Study

Assessing the knowledge of caregivers of patients undergoing peritoneal dialysis in the Mahaweli c region, Sri Lanka

Continuous Ambulatory Peritoneal Dialysis (CAPD) was identified as the best alternative treatment for developing countries like Sri Lanka having an increasing number of CKD and CKDu patients. Caregivers of CAPD patients play an important role in this treatment regime. However, the assessment of knowledge of caregivers of CAPD patients was not conducted systematically. This study aims to evaluate the knowledge of caregivers and improves the knowledge. The study was conducted in three stages, i.e. pre-interventional, interventional and post-interventional. The results obtained by the pre-intervention were analyzed and gaps were identified under each key area. Strategies were identified to achieve better patient safety practices. Further, the training/ workshop plan was conducted to improve the knowledge of caregivers at Divisional Hospital Girandurukotte. To check the effectiveness of the intervention statistically, a paired t-test was used. Correct answer count was obtained for each caregiver before and after data sets separately and marks were assigned for knowledge of each caregiver. Then averages were calculated for both datasets. Finally, using the paired t-test, before and after average marks were compared. The percentage of caregivers who gave correct answers increased after the intervention. Paired T-test results illustrate that there is a significant difference between before and after intervention Since the p-value is less than the 5% significance level, it can be concluded that after the intervention average marks of caregivers increased. Therefore, this intervention positively impacts the caregiver’s awareness. Therefore, continuous educational programs for all patients and caregivers who receiving CAPD treatment are recommended to improve knowledge about treatment.

Published by: Y. M. S. S. Yapa, L. Gunerathne, S. N. Kumari, S. R. Jayasinghe

Author: Y. M. S. S. Yapa

Paper ID: V7I5-1183

Paper Status: published

Published: September 10, 2021

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Research Paper

Breast Cancer Classification using Python

This article aims to evaluate the prediction models of machine learning classification in terms of accuracy, objectivity, and reproducible of the diagnosis of malignant neoplasm with fine needle aspiration. Also, we seek to add one more class for testing in this database as recommended in earlier studies. We present six various classification methods: Multilayer Perceptron, Decision Tree, Support Vector Machine, Random Forest, and Deep Neural Network for evaluation. In the field of assisted cancer diagnosis, it's expected that the involvement of machine learning in diseases will give doctors a second opinion and help them to form a faster / better determination. There is an enormous number of studies in this area using traditional machine learning methods and in other cases, using deep learning for this purpose.

Published by: M. Rishika Reddy, P. Harshavardhan, V. Aashrith Surya, Kosgi Rohith, D. Haswanth

Author: M. Rishika Reddy

Paper ID: V7I5-1182

Paper Status: published

Published: September 10, 2021

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Thesis

Morphometric Analysis of middle Kaligandaki Sub Basin and Flood Mapping using HEC-RAS

Watershed analysis based on morphometric parameters gives an idea about the basin characteristics regarding slope, topography, soil condition, runoff characteristics, surface water potential, etc. These characteristics are very important for watershed planning and management. The potential disaster of flash flood and soil erosion is anticipated by studying morphometric parameters of the Kaligandaki basin. In the middle Kaligandaki sub-basin, the Kaligandaki river from Tatopani to Modibeni has human settlements concentrated along its sides like the Beni bazaar. They are always at risk of erosion and flood inundation. In monsoon, due to heavy rainfall, the Kaligandaki river erodes and inundates the lands near its bank. From the analysis of morphometric parameters, the erosion and inundation of land near river banks are justified. The study of flood inundation map obtained by processing discharge of river in HEC-RAS indicates the settlement and structures near the river are very prone to flood disaster. This study can be referenced for flood planning and disaster reduction measures in the Beni bazaar.

Published by: Kalyan Paudel, Kaushal Chandra G. C.

Author: Kalyan Paudel

Paper ID: V7I5-1172

Paper Status: published

Published: September 10, 2021

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Research Paper

Accident detection and rescue system

The Rapid growth of technology and infrastructure has made our lives easier. The advent of technology has also increased the traffic hazards and the road accidents take place frequently which causes huge loss of life and property because of the poor emergency facilities. The incidence of accidental deaths increased by 44.2% in 2011 from 2001. Our project will provide an optimum solution to this drawback. Nowadays we are able to track vehicles using many applications which helps in securing personal vehicles, public vehicles, feet units and others. Furthermore, there is a rapid increase in the occurrence of Road accidents. This paper is about a system that is developed to automatically detect an accident and alert the nearest hospitals and medical services about it. This system can also locate the place of the accident so that the medical services can be directed immediately towards it. The goal of this paper is to build up an Accident Alert System Using Arduino. The system comprises Sensors, GPS & GSM Module support in sending messages. The Sensors is used to detect vibrations and impact are used to detect an accident. Short Message will contain GPS [Latitude, Longitude] which helps in locating the vehicles

Published by: Mihri Lad, Om Bellilkatti, Kanshiq Ladha, Deepak Khachane

Author: Mihri Lad

Paper ID: V7I5-1180

Paper Status: published

Published: September 8, 2021

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Case Study

The Biofuel Price Stabilization Mechanism

This article studies the capacity of biofuels to reduce motor fuel price fluctuations. We hypothesize the dependence between crude oil and biodiesel blend prices in Spain and the EU. Copula models are a method of study. Results suggest that the practice of blending biodiesel with diesel can protect consumers against extreme crude oil price increases. This can also help reduce the carbon emissions and the Green House Gases (GHG's) emitted upon burning fossil fuels

Published by: Soham Das

Author: Soham Das

Paper ID: V7I5-1166

Paper Status: published

Published: September 7, 2021

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Review Paper

Sentiment analysis of COVID-19 Vaccination Tweets on Twitter using Machine Learning Algorithm

After Declaring pandemic in March 2020 public health prevention measures have proven to be somewhat effective in limiting the spread of COVID-19. Protective immunity through vaccination will be great importance of in ending the pandemic. This work aims to identify the sentiments of the masses towards vaccination by analyzing the text tweets. 68,654 tweets are retrieved from Twitter posted within the timeline from December 2020 to January 2021. Sentiment, polarity score, and subjectivity score were computed and analyzed on the basis of text and date columns. According to the polarity and subjectivity scores, tweets were classified as positive, negative, and neutral using the TextBlob library of natural language processing. Also, the user’s view on the vaccination was analyzed using machine learning algorithms such as Naïve Bayes (NB) and Logistic Regression (LR). The highest accuracy achieved was 90% by Logistic Regression (LR). It was observed from the results that the sentiments towards the vaccine were positive on the initial day but a shift to negative sentiments was observed. Later, the sentiment towards vaccines is again positive.

Published by: Disha Jethva

Author: Disha Jethva

Paper ID: V7I5-1175

Paper Status: published

Published: September 7, 2021

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