Abstract COVID-19 has caused havoc globally due to its transmission pace among the inhabitants and prolific rise in number of people contracting disease worldwide. As a result, seeking information about epidemic via Internet media increased. The impact hysteria that prevailed makes believe share everything related illness without questioning truthfulness. it amplified misinformation spread on social networks disease. Today, there is an immediate need restrict disseminating false news, even...

Monitoring health of a person(s) has become major IoT application where we need to have system at home that helps inhabitants their check done without affecting daily routines. It is very much essential driven remote monitoring for ailing individuals which can inform caretakers in case an emergency. These applications are constrained by the amount data collected, managed and exchanged. The factors constraint robustness, privacy, security reliability. In this paper, survey various care...

Hate speech identification in social media has emerged as a highly debated research topic computational linguistics. Understanding linguistic phenomena low-resource languages, particular, remains major problem natural language processing. Code-mixing is common phenomenon writing, particularly multilingual societies such India. Traditional deep learning techniques trained on monolingual data will not perform well code-mixed data, and training new models are challenging due to lack of...

Identifying abusive content or hate speech in social media text has raised the research community’s interest recent times. The major driving force behind this is widespread use of websites. Further, it also leads to identifying low-resource regional languages, which an important problem computational linguistics. As part ACL-2022, organizers DravidianLangTech@ACL 2022 have released a shared task on category identification Tamil and Tamil-English code-mixed encourage further offensive Indic...

Shaik Fharook, Syed Sufyan Ahmed, Gurram Rithika, Sumith Sai Budde, Sunil Saumya, Shankar Biradar. Proceedings of the Workshop on Combating Online Hostile Posts in Regional Languages during Emergency Situations. 2022.

Early disease prediction prevents patients to encounter severe situations. Transition from symptoms stage of any takes time. Prediction in this transition is called early detection. For the heart risk study, an ensemble learning system recommended. The stack approach used predict cardiac illness using a variety heterogeneous weak learners. These include Multi-Layer Perceptron Classifier, Decision Tree Support Vector and Logistic Regression. All these ML techniques are layered stack-based...

One of the major issues to worry nowadays is busy life cycle people follow and effect they have on health. This has made neglect their In India many are below poverty line even majority population stays in rural places cost medical treatment too high. Under these situations, it not feasible for afford costly treatment. We seen being admitted hospitals at last hour forced traditional practices lose lives. To address this issue, we need a remote health monitoring system that could alert about...

Machine Learning techniques are most widely used in the field of clustering data. The K-means algorithm is one which for data sets and easy to understand simulate on different datasets. In our paper work we have yeast dataset iris datasets, resulted less accuracy with more number iterations. We simulating an improved version K- means these Improved use technique minimum spanning tree. An undirected graph generated all input points then shortest distance calculated intern results better also...

In multilingual societies like India, mixing the native language with English has become common during social media conversations. Further, due to government’s digitization push, more people from rural India are joining platforms, resulting in exponential growth of or code-mixed content. The resultant content on is available for both positive (also termed as Hope Speech) well negative context Hate Speech). To keep clean and hate free, it important remove using machine learning filters. Since...

There exist many computational methods for finding similarity in gene sequence, suitable that gives optimal is difficult task.Objective of this project to find an appropriate method compute gene/protein both within the families and across families.Many dynamic programming algorithms like Levenshtein edit distance; Longest Common Subsequence Smith-waterman have used approach similarities between two sequences.But none mentioned above real benchmark data sets.They only synthetic data.We...

In recent years, there has been a lot of focus on offensive content. The amount content generated by social media is increasing at an alarming rate. This created greater need to address this issue than ever before. To these issues, the organizers "Dravidian-Code Mixed HASOC-2020" have two challenges. Task 1 involves identifying in Malayalam data, whereas 2 includes and Tamil Code Sentences. Our team participated 2. our suggested model, we experiment with multilingual BERT extract features,...

Since personal computers became widely available in the consumer market, amount of harmful content on internet has significantly expanded. In simple terms, is anything online which causes a person distress or harm. It may include hate speech, violent content, threats, non-hope etc. The must be positive, uplifting and supportive. Over past few years, many studies have focused solving this problem through speech detection, but very identifying hope speech. This paper discusses various machine...