2022 International Conference on Innovative Trends in Information Technology (ICITIIT)最新文献_第3页

Multi Tasking Synthetic Speech Detection on Indian Languages 印度语言的多任务合成语音检测

2022 International Conference on Innovative Trends in Information Technology (ICITIIT) Pub Date : 2022-02-12 DOI: 10.1109/ICITIIT54346.2022.9744221

A. R. Ambili, Rajesh Cherian Roy

引用次数: 3

Data Imputation Techniques: An Empirical Study using Chronic Kidney Disease and Life Expectancy Datasets 数据代入技术:使用慢性肾脏疾病和预期寿命数据集的实证研究

2022 International Conference on Innovative Trends in Information Technology (ICITIIT) Pub Date : 2022-02-12 DOI: 10.1109/ICITIIT54346.2022.9744211

Sainath Reddy Sankepally, Nishoak Kosaraju, K. Mallikharjuna Rao

{"title":"Data Imputation Techniques: An Empirical Study using Chronic Kidney Disease and Life Expectancy Datasets","authors":"Sainath Reddy Sankepally, Nishoak Kosaraju, K. Mallikharjuna Rao","doi":"10.1109/ICITIIT54346.2022.9744211","DOIUrl":"https://doi.org/10.1109/ICITIIT54346.2022.9744211","url":null,"abstract":"Data is a collection of information from the activities of the real world. The file in which such data is stored after transforming into a form that machines can process is generally known as data set. In the real world, many data sets are not complete, and they contain various types of noise. Missing values is of one such kind. Thus, imputing data of these missing values is one of the significant task of data pre-processing. This paper deals with two real time health care data sets namely life expectancy (LE) dataset and chronic kidney disease (CKD) dataset, which are very different in their nature. This paper provides insights on various data imputation techniques to fill missing values by analyzing them. When coming to Data imputation, it is very common to impute the missing values with measure of central tendencies like mean, median, mode Which can represent the central value of distribution but choosing the apt choice is real challenge. In accordance with best of our knowledge this is the first and foremost paper which provides the complete analysis of impact of basic data imputation techniques on various data distributions which can be classified based on the size of data set, number of missing values, type of data (categorical/numerical), etc. This paper compared and analyzed the original data distribution with the data distribution after each imputation in terms of their skewness, outliers and by various descriptive statistic parameters.","PeriodicalId":184353,"journal":{"name":"2022 International Conference on Innovative Trends in Information Technology (ICITIIT)","volume":"205 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115910343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

String Kernels for Document Classification: A Comparative Study 用于文档分类的字符串核:比较研究

2022 International Conference on Innovative Trends in Information Technology (ICITIIT) Pub Date : 2022-02-12 DOI: 10.1109/ICITIIT54346.2022.9744134

Nikhil V. Chandran, A. S., A. V. S.

引用次数: 5

Speed Control of Permanent Magnet Synchronous Machine using Genetic and Fuzzy Algorithm 基于遗传和模糊算法的永磁同步电机速度控制

2022 International Conference on Innovative Trends in Information Technology (ICITIIT) Pub Date : 2022-02-12 DOI: 10.1109/ICITIIT54346.2022.9744234

Arundhuti Haldar, Riddhi Khatua

引用次数: 0

NLP Based Automated Business Report Summarization 基于NLP的自动业务报告摘要

2022 International Conference on Innovative Trends in Information Technology (ICITIIT) Pub Date : 2022-02-12 DOI: 10.1109/ICITIIT54346.2022.9744151

Faizal B, Sajimon Abraham

引用次数: 0

Balancing of an imbalanced dataset by applying SMOTE variants and predicting neonatal mortality using ensemble learning techniques

2022 International Conference on Innovative Trends in Information Technology (ICITIIT) Pub Date : 2022-02-12 DOI: 10.1109/ICITIIT54346.2022.9744204

Sivarajan A, Bala Aditya A, Sivasankar E

引用次数: 0

Comparative Analysis of Various Machine Learning Techniques for Flood Prediction 洪水预测中各种机器学习技术的比较分析

2022 International Conference on Innovative Trends in Information Technology (ICITIIT) Pub Date : 2022-02-12 DOI: 10.1109/ICITIIT54346.2022.9744177

Sajimon Abraham, Jyothish V R, Sijo Thomas, Benymol Jose

{"title":"Comparative Analysis of Various Machine Learning Techniques for Flood Prediction","authors":"Sajimon Abraham, Jyothish V R, Sijo Thomas, Benymol Jose","doi":"10.1109/ICITIIT54346.2022.9744177","DOIUrl":"https://doi.org/10.1109/ICITIIT54346.2022.9744177","url":null,"abstract":"A flood is a most destructive disaster that affects people, places, and lives. Due to the complication in data availability, flood prediction is always a challenging task. The conventional mode of disaster management relies on satellite images and radar outcomes. It takes enormous time for processing. Machine learning paved the way for a new perspective on this hydrological problem. Recent developments in Machine Learning (ML) and Information and Communication Technology (ICT) have led to a state-of-the-art implementation and prediction. The major objective of this work is to recognize the most accurate machine learning model to identify flood occurrence, by comparing Logistic regression, Decision Tree, Naive Bayes, and Support Vector Machines classifiers. Machine Learning strategies are evaluated using precision, recall, F1-score, RMSE, and accuracy metrics. All the strategies are applied to one-feature dataset, three-feature dataset and four-feature dataset. The quantitative evaluation demonstrates that decision tree algorithm is most suitable for flood prediction and it exponentially grows with respect to the number of features examined.","PeriodicalId":184353,"journal":{"name":"2022 International Conference on Innovative Trends in Information Technology (ICITIIT)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116400949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Miniature probability maps using resource limited embedded device for classification of histopathological images 利用资源有限的嵌入式设备对组织病理图像进行分类的微型概率图

2022 International Conference on Innovative Trends in Information Technology (ICITIIT) Pub Date : 2022-02-12 DOI: 10.1109/ICITIIT54346.2022.9744131

Anil Johny, K. Madhusoodanan

引用次数: 0

vRecruit: An Automated Smart Recruitment Webapp using Machine Learning vRecruit:一个使用机器学习的自动化智能招聘web应用程序

2022 International Conference on Innovative Trends in Information Technology (ICITIIT) Pub Date : 2022-02-12 DOI: 10.1109/ICITIIT54346.2022.9744135

Sanika Mhadgut, Neha Koppikar, Nikhil Chouhan, Parag Dharadhar, Parthak Mehta

{"title":"vRecruit: An Automated Smart Recruitment Webapp using Machine Learning","authors":"Sanika Mhadgut, Neha Koppikar, Nikhil Chouhan, Parag Dharadhar, Parthak Mehta","doi":"10.1109/ICITIIT54346.2022.9744135","DOIUrl":"https://doi.org/10.1109/ICITIIT54346.2022.9744135","url":null,"abstract":"The need for global online recruitment has risen tremendously in recent years. However, this procedure presents difficulties for recruiters in managing the flood of applications and maintaining contact with the applicants. Historically, little attention has been paid to a practical solution for virtual recruitment. As a result, the paper proposes \"vRecruit - A machine learning-based web application\" for virtual recruitment in the current paper. vRecruit’s primary features include a client-specific interview process that leverages Machine Learning-based references to context provided by the client, as well as a text-based sentiment analysis engine. All components work in unison to ensure the webapp’s end-to-end functionality, which was finally launched on flask. The face recognition method using the face api model achieved a 96% accuracy. The speech to text conversion using the Mozilla DeepSpeech model had a 7.55% word error rate, whereas the rasa Natural Language Understanding (NLU) model trained for chatbots had a 95% accuracy. The webapp provides a hassle-free virtual recruiting experience for candidates and interviewers.","PeriodicalId":184353,"journal":{"name":"2022 International Conference on Innovative Trends in Information Technology (ICITIIT)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127080804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Self cascoded body biasing technique for ultra-low-power sub-threshold ring oscillator 超低功耗亚阈值环形振荡器的自级联体偏置技术

2022 International Conference on Innovative Trends in Information Technology (ICITIIT) Pub Date : 2022-02-12 DOI: 10.1109/ICITIIT54346.2022.9744168

K. Reddy, P. Rao

引用次数: 1