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Research Paper

Innovation Performance in Saudi Arabia

The reader, of this article, will find the past 8-years data for the GII score that measures the performance of innovation for Saudi Arabia which were hosted in reports published by the Global Innovation Index. These hosted data were, statistically, analyzed in order to forecast the future scores that Saudi Arabia can achieve during the next five years. The forecasting process passes through a systematic approach starting by checking the variation and distribution (using the descriptive statistics), checking the relationships (using the Person correlation coefficient) and finally developing a “regression equation” in order to be able to forecast the behavior of the GII for the next 5 years (using Box-Jenkins approach).

Published by: Dr. Ahmad Alkhaleefah

Author: Dr. Ahmad Alkhaleefah

Paper ID: V6I3-1243

Paper Status: published

Published: June 22, 2020

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Research Paper

Home automation using Arduino with android application

In Today’s world, almost everyone has a personal smartphone or a smart device. With the help of Home Automation using an Android application, one can quickly do everyday household tasks with touch of a finger. Nowadays automation is playing a key role in making our life easier and maintaining our safety and security. With the help of automated tasks, one can very easily control the lights, increase or decrease the temperature of the room using smartphones. Home automation has been a major area of research in recent times. Home automation based on the android platform is designed to interface Arduino (8-bit microcontroller) to control a number of home appliances like lights, fans, bulbs, and many more using Relay. Bluetooth has been used for short-range communication. Different types of sensors have been used which are explained below. This paper provides a modern approach to automate household appliances and eliminate the traditional method of switching. It is a step towards easing the daily household tasks and help the elderly and disabled people.

Published by: Neha, Vijay Kumar Soni, Mohammad Ashraf, Abhimanyu Yadav

Author: Neha

Paper ID: V6I3-1558

Paper Status: published

Published: June 21, 2020

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Technical Notes

Alcohol detection system for bike using Arduino and RF

On a survey that has been done recently, said that nearly 70% of road accidents occur due to Drunk & drive, with a range of 44% to 67% in small cities. The government has made rules that rider should compulsory wear the helmet and not consume alcohol while drving. Still the riders do not obey the rules even though huge number of fines have been imposed. Not wearing the helmet causes the rider with severe injuries which may lead to death of the rider. In order to overcome this,Smart helmet and detection of alcohol present in rider’s breath is proposed. This paper attempts to explore the possibility of using the technology that would detect the level of alcohol in the blood and prevent “very-start” of the motor vehicle. The model device focused at preventing the user from driving when drunk and reduces the number of accidents occurring due to drunken driving. The model is created using Arduino Uno and Alcohol detecting sensor. The alcohol detecting sensor (MQ-3) when connected to an Arduino UNO R3 detects the level of alcohol content in blood by analyzing driver’s breath. A user friendly device that uses a non-contact breath sensor to detect breath-based alcohol. The device’s sensor sens saturated water vapor in human breath, and three semiconductor gas sensors detect ethanol, acetaldehyde, and hydrogen. The device can check whether the gas introduced into it is human breath and the alcohol level at the same time.

Published by: Meet Jitendra Raut, Sugam Mahesh Chaudhari, Aditya Anil Raut, Reshma Chaudhari

Author: Meet Jitendra Raut

Paper ID: V6I3-1562

Paper Status: published

Published: June 20, 2020

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Case Study

Classify radio signals from space

The data we are going to use consists of 2D spectrograms of deep space radio signals collected by the Allen Telescope Array at the SETI Institute. We will treat the spectrograms as images to train an image classification model to classify the signals into one of four classes. By the end of the project, you will have built and trained a convolutional neural network from scratch using Keras to classify signals from space.

Published by: Tarit Sengupta

Author: Tarit Sengupta

Paper ID: V6I3-1559

Paper Status: published

Published: June 20, 2020

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Dissertations

An exploratory study to assess the perceptions of preconception care among undergraduate girls with a view to develop information booklet in selected colleges of district Sirmour (Himachal Pradesh)

Preconception care recognizes that many adolescent girls and young women will be thrust into motherhood without the knowledge, skills, or support they need. Objectives: The study aimed to determine the level of perception among undergraduate girls regarding preconception care. Method: Exploratory research design was adopted to collect data from 288 undergraduate girls of the selected colleges of District Sirmour (H.P) using the multistage sampling technique. Data were collected by a self-administered questionnaire using 5 points Likert scale. Results: The present study findings showed that 37.2% of undergraduate girls had favorable perceptions regarding preconception care, 62.8% of undergraduate girls had moderately favorable perceptions (neither positive nor negative) regarding preconception care and none of them (0%) had unfavorable perceptions regarding preconception care. There was a significant association of age with the perception of undergraduate girls at the level of significance p<0.05.Conclusion: The results of the present study reveal that there is a lack of awareness regarding preconception care. Hence student’s perceptions regarding its benefits are not favorable. So there is a need to shift the care at the earliest to prevent further complications during pregnancy.

Published by: Nindiya Parmar, Anna Bajaj

Author: Nindiya Parmar

Paper ID: V6I3-1547

Paper Status: published

Published: June 20, 2020

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Research Paper

Effect of the regularization parameter on image-guided filter

The guided filter is derived from a local linear model. It computes the filtering output by considering the content of a guidance image (self-image or reference image). The guided filter can be used as an edge-preserving smoothing operator that behaves better near edges. It can transfer the structures of the guidance image to the filtering output, enabling new filtering applications like dehazing and guided feathering. Moreover, the guided filter naturally has a fast and non-approximate linear time algorithm, regardless of the kernel size and the intensity range. Regularization parameter (ϵ) is one of the two important factors which determines the characteristics of the guided image applied to the input image i.e. it helps to perceive the degree of the edges of an image. In this paper, we will observe the effect of the regularization parameter on a guided filtered image.

Published by: Eisita Basak, Sangita Roy, Dr. Saradindu Panda

Author: Eisita Basak

Paper ID: V6I3-1539

Paper Status: published

Published: June 20, 2020

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