Hate Speech Detection on Social Media Using Machine Learning Algorithms

Rupesh; Ritik; Pranav; Mangesh; A. B.

doi:https://doi.org/10.54216/JCHCI.020203

Journal of Neutrosophic and Fuzzy Systems | 2022

Applying Machine Learning Techniques To Maximize The Performance of Loan Default Prediction

In peer-to-peer (P2P) lending, borrowers would access loans with lower interest rates than what they usually got from traditional lenders. People can directly borrow from the P2P platform with the rules that make them easy to borrow loans and invest free funds into P2P, which can benefit both borrowers and lenders. However, the easy way to borrow loans comes with risks. One of the major issues is that borrowers may default on the loan taken. In such cases, they can get loans quickly from P2P online platforms without any bank interferences. Thus, the lender can calculate his risk for loan default. In this project, we consider the P2P lending data to predict the loan default reassuring the lender to continue providing loans in the future. In our analysis, we consider the Logistic Regression, Naive Bayes, Random Forest, K Nearest Neighbour, and Decision tree to classify loan data based on their likelihood of default. The simulation result in our algorithm provides a significant accuracy of 94.6%.

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Vinay Padimi mail -

Venkata Sravan Telu mail -

Devarani Devi Ningombam mail

link https://doi.org/10.54216/JNFS.020204

Volume & Issue

Vol. Volume 2 / Iss. Issue 2

Details open_in_new

Journal of Cognitive Human-Computer Interaction | 2022

Smart City's Security Model for Management of Image Data on Cloud

In modern world of advancement, cloud technology is taking its grip. COVID-19 also enhance the use of the cloud services. The cloud concept comes with the new advancement of technology, but with that data breaches and data hacks are also increasing. In the cloud-based environment, we suggested the model of security enhancement which, make use pf role-based security model where the files are shared according to the role and the access of such file is controlled using TPA validation and apart for that the concept of authentication of user is also suggested using the Pattern Lock based graphical system for pattern formation. The pattern obtained are validated using the various of online password or pattern strength validation tools, results which are obtained proves that pattern obtained through the proposed concept performs better against the attack.

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Pooja mail -

Manish Kumar Mukhija mail -

Satish Kumar Alaria mail

link https://doi.org/10.54216/JCHCI.020101

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

Details open_in_new

Fusion: Practice and Applications | 2022

Detection of Covid-19 using Cough Sounds

Coronavirus, the pandemic due to which about 4 million have lost their lives and counting, is still on. Many scientists and researchers are trying to find ways to detect coronavirus as soon as possible in the human body so that they can start their medication and precaution as soon as possible. Still, due to lack of lab facilities, the RT-PCR is taking more than three days to give the report, and in the meanwhile, patients get serious and life in danger. So in this paper, we proposed an audio-based coronavirus detection technique in which we can get results in minutes. Coronavirus is a respiratory disease, and the sound produced while breathing can tell us about the presence of coronavirus. Audio-based detection was already used for the detection of asthma, pneumonia. So, in this paper, we implemented a combination of machine learning and deep learning techniques to find the presence of Covid-19, and the model has an accuracy of 78% and an f1 score of 74%. This technique can be used as a starting point for just audio data to diagnose diseases and save lives.

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Harsh Taneja mail -

Abhinav mail -

Apoorv mail -

Himanshu Mangal mail -

Naman Agarwal mail

link https://doi.org/10.54216/FPA.070202

Volume & Issue

Vol. Volume 7 / Iss. Issue 2

Details open_in_new

Journal of Cognitive Human-Computer Interaction | 2022

Automated Attendance System using Real Time Face Recognition and MySQL Database

This project aims to design a automated attendance system using face-recognition and MySQL database. We have presented our idea to implement an “Automated Attendance System Using Real Time Face recognition and MySQL Database”. The application includes face identification, which saves time as well as being purely software based it can be flagged as eco-friendly as it reduces the use of paper and also send a message to the student of his attendance record in the end of every day. This system also eliminates the chances of fake attendance because of the face being used as a biometric for authentication. This system avoids the concept of fake attendance where attendance plays an important role. The proposed system is designed in Python as well as SQL database. The algorithm used in the system compare the image captured encoded value with the value already available with us to recognize the face. The system has output in the form of MYSQL Database.

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Sumithra M. mail -

Vettri Chezhian P. mail -

Raj Kumar K. mail -

Nithish Kumar S. mail

link https://doi.org/10.54216/JCHCI.020102

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

Details open_in_new

Journal of Cognitive Human-Computer Interaction | 2022

Innovation for Better Education System using Artificial Intelligence

In today’s world, Gen Z finds it difficult to maintain attention during classes. Students tend to get distracted easily. With the flow of information all around them, a constant search for new activities is on the rise. To understand the needs of individual students the emotional status of the students are taken into account. Our education system uses Local Binary Pattern (LBP) algorithm for feature extraction and emotion intensity recognition. The extracted features are used as input for the AI algorithm which creates the personalized lessons for each individual according to their needs. The lessons are categorized into three categories based on their understanding capability along with the personalized time-line. This innovation helps students to achieve greater heights by using personalized lessons according to their capacity. A tracking system is implemented to monitor the emotions and attention level of the students, thereby ensuring successful completion of academics. As teachers, continuous acquiring of knowledge is vital. This innovative AI system helps teachers stay updated in their respective field. To provide security for the students while they are in the campus, the AI system using surveillance camera detects suspicious activities and alerts the respective in-charge to take necessary actions. As a result, we provide a better education system in all aspects.

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M. Sumithra mail -

B. Buvaneswar mail -

Jessica Judith S. mail -

Dymphna Mary C. mail -

Punitha R. mail -

Pavithraa S. mail

link https://doi.org/10.54216/JCHCI.020103

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

Details open_in_new

Journal of Cognitive Human-Computer Interaction | 2022

Artificial Intelligence Based Accident Detection and Alert System

Lost time is never found again is a great sounding slogan which signifies that how every single moment is valuable for a victim striving for life in an road accident. So there is a need for right medical care at the right time. The goal of our system is to detect an accident and rescue the victim as early as possible. The system uses GPS map camera with artificial intelligence to detect the accident and an android application in which the public, police and the hospitals can connect and collaborate with each other in a best possible way in case of an emergency or accident thereby reducing the number of deaths caused by accidents.

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M. Sumithra mail -

B. Buvaneswari mail -

Sangeetha mail -

Shalini mail -

Sundareswari mail -

Vishnu PriyVishnu Priya mail

link https://doi.org/10.54216/JCHCI.020104

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

Details open_in_new

Journal of Cognitive Human-Computer Interaction | 2022

Online Vehicle Rental System

Transportation is the major need of the worker and minor need for large number of people, government, and many organizations. Without transporting goods and cargo etc. There are many rental systems available in offline but the main disadvantage in it is the customers have to visit the company to pick up a vehicle. In order to save time and effort we introduce web based online vehicle rental system. The method that exists since now is offline vehicle rental system which is a major negative for most of the customers. There are only few companies are available offline not everyone knows about the company’s existing. To avoid the disadvantage in this offline vehicle rental system, many use a method of advertising and posting flyers for their companies to acknowledge their customers about vehicle rental system. The major advantage in our web based online vehicle rental system is that the customer can book their vehicle from anywhere and anytime to their need. Their rented vehicle will be delivered to their booked location. One can see available vehicle using their mobile phones from anywhere through internet connection.

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M. Sumithra mail -

B. Buvaneswari mail -

S. Ahilesharan mail -

T. Fenix Raja Singh mail -

J. Harish mail

link https://doi.org/10.54216/JCHCI.020105

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

Details open_in_new

Journal of Cognitive Human-Computer Interaction | 2022

Personnel Monitoring System Using Mobile Application during the COVID 19

Corona virus disease(COVID-19) is a disease caused by the new corona virus called severe acute respiratory syndrome corona virus  (SARS CoV-2). This disease has infected almost the entire world with a total of 47.5 million sufferers and a death total of 1.2 million people, WHO categorizes it as a global pandemic. Proven efforts to reduce the spread of COVID-19 include limiting physical interactions between humans or physical distance, maintaining the cleanliness of hands and limbs by washing with soap, and limiting outdoor activities by staying at home. Government and private agencies have required employees to report their health conditions via web pages. Real-time and accurate mobile applications can help prevent the spread of COVID-19. This research will develop a real-time monitoring and command system using mobile applications and cloud computing technology. The application will collect GPS-based location data and the user's body condition in the form of temperature and oxygen levels in the blood. User data is stored and processed in a real-time database in cloud computing which can be accessed through an application on the user's smart phone. The database also stores data on COVID-19 sufferers and where they live. Advice is given by the app when the recording of the body condition points to the early symptoms of COVID-19.

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Nishanthi G. mail -

Yuvashree A. mail -

Jessinda Joseph mail -

Supraja R. mail

link https://doi.org/10.54216/JCHCI.020201

Volume & Issue

Vol. Volume 2 / Iss. Issue 2

Details open_in_new

Journal of Cognitive Human-Computer Interaction | 2022

A Survey on Cyber Security Meets Artificial Intelligence: AI– Driven Cyber Security

The computerized version of human intelligence is Artificial Intelligence(AI). Artificial Intelligence systems combine large sets of data with intelligent and iterative processing algorithms in order to make predictions, based on patterns and features in the data that they analyse. With the booming technologies such as IOT and Cloud Computing, huge amounts of data are generated and collected that require cyber security protection today. There is a growing need for cyber security methods which are both robust and intelligent due to the ever-increasing complexity of cyber crimes. While data can be used to benefit business interests, it poses a number of challenges in terms of security and privacy protection. Artificial Intelligence (AI) based technologies, such as machine learning statistics, big data analysis, deep learning and so on, have been used to deal with cyber security threats. These technologies are used for intrusion detection systems, malicious software detection, and encrypted communications. In the rapidly growing field of AI driven security, scientists from multiple disciplines work together to combat cyber threats. AI models require unique cyber security defence and protection technologies. This survey provides various method, different datasets and methodologies that may be used for the proposed IA enabled cyber security technologies. This study aims to classify the AI-based cyber security solutions gathered and describe how they can help solve problems in the field of cyber security.

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S. P. Samyuktha mail -

P. Kavitha mail -

V. A. Kshaya mail -

P. Shalini mail -

R. Ramya mail

link https://doi.org/10.54216/JCHCI.020202

Volume & Issue

Vol. Volume 2 / Iss. Issue 2

Details open_in_new

Journal of Cognitive Human-Computer Interaction | 2022

Hate Speech Detection on Social Media Using Machine Learning Algorithms

There is an enormous growth of social media which fully promotes freedom of expression through its anonymity feature. Freedom of expression is a human right but hate speech towards a person or group based on race, caste, religion, ethnic or national origin, sex, disability, gender identity, etc. is an abuse of this sovereignty. It seriously promotes violence or hate crimes and creates an imbalance in society by damaging peace, credibility, and human rights, etc. To overcome this problem, the hate speech detection model is made which will classify the speech and if the speech used by user is containing hate word, it will be detected and system will sent an alert message to user about it. In order to solve various hate speech problems we use some of the machine learning algorithms such as logistic regression and random forest. If user disrupts cyber guidelines, then strict action shall be taken and user’s account will be ban forever. This help to reduce cyber crimes in effective and efficient manner.

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Rupesh Chaudhari mail -

Ritik Gad mail -

Pranav Gawali mail -

Mangesh Gite mail -

A. B. Pawa mail

link https://doi.org/10.54216/JCHCI.020203

Volume & Issue

Vol. Volume 2 / Iss. Issue 2

Details open_in_new