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Steffi. R
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Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Neuroscience

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Journal : IJHCS

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The Application of Machine Learning to the Prediction of Heart Attack R. Regin; S. Suman Rajest; Shynu T; Steffi. R
International Journal on Human-Computing Studies Vol. 5 No. 4 (2023): International Journal of Human Computing Studies (IJHCS) (2615-8159/ 2615-1898)
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v5i4.4259

Abstract

Heart illnesses are among the most significant contributors to mortality in the world in the modern era. Heart attacks are responsible for the death of one person every 33 seconds. disease of the cardiovascular system by disclosing the proportion of mortality all over the world that are caused by heart attacks. In order to forecast instances of heart disease, a supervised machine learning method is utilised. Because the incidence of heart strokes in younger people is growing at an alarming rate, we need to establish a method that can identify the warning signs of a heart attack at an early stage and stop the stroke before it occurs. Because it is impractical for the average person to often undertake expensive tests like the electrocardiogram (ECG), there is a need for a system that is convenient and, at the same time, accurate in forecasting the likelihood of developing heart disease. Therefore, our plan is to create a programme that, given basic symptoms such as age, sex, pulse rate, etc., can determine whether or not a person is at risk for developing a cardiac condition. The machine learning algorithm neural networks that are used in the suggested system are the most accurate and dependable.
An Approach Based on Machine Learning for Conducting Sentiment Analysis on Twitter Data S. Suman Rajest; R. Regin; Shynu T; Steffi. R
International Journal on Human-Computing Studies Vol. 5 No. 12 (2023): International Journal of Human Computing Studies (IJHCS) (2615-8159/ 2615-1898
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v5i12.5122

Abstract

Using Twitter's primary goals as a guide, we built a real-time sentiment analysis system that labels tweets according to the emotions they convey. One more way Twitter facilitates social networking is through microblogging, which allows users to record brief status updates. The analysis of the emotions conveyed at intervals between tweets allows us to get a reflection of public attitude, which is made possible by this massive amount of usage. The goal is to find the most accurate way to examine the information by primarily applying approaches based on machine learning. Data validation, cleaning, and preparation for visual representation will be performed on the entire provided dataset after the controlled AI technique (SMLT) has been used to capture various pieces of information, such as variable ID, amount and factual strategy, missing worth medicines, and univariate examination. Through the discovery of the optimal exactness computation, our inquiry provides a comprehensive guide to sensitivity analysis of model parameters in relation to performance in sentiment analysis prediction. All of the algorithms' performance metrics, including exactness recall, f1score, sensitivity, and specificity, are also computed and compared.
Planning the Most Effective Itinerary for Tourists through the use of Data Analysis R. Regin; S. Suman Rajest; Shynu T; Steffi. R
International Journal on Human-Computing Studies Vol. 5 No. 12 (2023): International Journal of Human Computing Studies (IJHCS) (2615-8159/ 2615-1898
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v5i12.5124

Abstract

In order to provide the most effective scheduling alternatives, data analysis of the information that the customer has provided is performed. The mobile application provides further recommendations, such as a list of all the appropriate sites or areas to visit inside the destination that has been picked, once the intended destination has been specified. In addition, the other significant recommendations concerning the method of transportation, the most efficient routes, the most desirable times, and the expenses associated with them will be automatically offered. Additionally, the Android Studio toolkit and the Google Maps interface are utilised in the process of application creation. Hadoop is used for the analysis of weather data. Hadoop is a Java programming platform and open-source Apache software that is utilised in the distributed world for the purpose of managing the management of enormous data volumes. One of the most significant benefits is the utilisation of the machine learning approach to cost estimation in the budget planning process. Travel plans that are efficient are provided by the intelligent local route as well as the form of transportation. The online application offers a platform that functions as a digital assistant that is intelligent and tailored to the tourists' areas of interest.
A QR Code-Based Real-Time Auditing System for Safe Online Data Storage S. Suman Rajest; R. Regin; Shynu T; Steffi. R
International Journal on Human-Computing Studies Vol. 6 No. 1 (2024): International Journal of Human Computing Studies (IJHCS)
Publisher : Research Parks Publishers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijhcs.v6i1.5186

Abstract

Up until now, auditing systems have only had a web module; these modules are complicated and not user-friendly. Protecting sensitive data stored in the cloud requires the time-consuming and laborious procedure of encrypting all of the files. To verify a user's identification in the current system, the client must input biometric data. Next, in order to safeguard the user's identity and privacy, a signature key will be validated. One major problem with biometric data is that there are a lot of circumstances that might cause it to vary, so it can't always be matched precisely. An auditing and data storage app built for the cloud is the focus of this paper. The reference ID that the client creates is used to remotely store the financial audit data in the cloud. Using a QR code scanner, this reference ID that was generated for the client is immediately transformed into a QR code. You can access the required documents by downloading them and then opening them in a dedicated app. In the event that the client's internal storage becomes corrupted or lost, this file can be restored from the cloud.
Co-Authors R. Regin R. Regin* S. Silvia Priscila S. Suman Rajest Shynu T