Proceedings of Intelligent Computing and Technologies Conference最新文献_第2页

Co-occurrence Based Approach for Differentiation of Speech and Song 基于共现的语音与歌曲区分方法

Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-07-12 DOI: 10.21467/proceedings.115.17

Arijit Ghosal, R. Ghoshal

{"title":"Co-occurrence Based Approach for Differentiation of Speech and Song","authors":"Arijit Ghosal, R. Ghoshal","doi":"10.21467/proceedings.115.17","DOIUrl":"https://doi.org/10.21467/proceedings.115.17","url":null,"abstract":"Discrimination of speech and song through auditory signal is an exciting topic of research. Preceding efforts were mainly discrimination of speech and non-speech but moderately fewer efforts were carried out to discriminate speech and song. Discrimination of speech and song is one of the noteworthy fragments of automatic sorting of audio signal because this is considered to be the fundamental step of hierarchical approach towards genre identification, audio archive generation. The previous efforts which were carried out to discriminate speech and song, have involved frequency domain and perceptual domain aural features. This work aims to propose an acoustic feature which is small dimensional as well as easy to compute. It is observed that energy level of speech signal and song signal differs largely due to absence of instrumental part as a background in case of speech signal. Short Time Energy (STE) is the best acoustic feature which can echo this scenario. For precise study of energy variation co-occurrence matrix of STE is generated and statistical features are extracted from it. For classification resolution, some well-known supervised classifiers have been engaged in this effort. Performance of proposed feature set has been compared with other efforts to mark the supremacy of the feature set.","PeriodicalId":413368,"journal":{"name":"Proceedings of Intelligent Computing and Technologies Conference","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122327275","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: 0

Smart Bag based on RFID and Internet of Things 基于RFID和物联网的智能包

Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-07-12 DOI: 10.21467/proceedings.115.13

Amarjeet Singh Chauhan, Dayal Nigam

{"title":"Smart Bag based on RFID and Internet of Things","authors":"Amarjeet Singh Chauhan, Dayal Nigam","doi":"10.21467/proceedings.115.13","DOIUrl":"https://doi.org/10.21467/proceedings.115.13","url":null,"abstract":"The Smart Bag is a very innovative and helpful project that uses RFID Technology [1] for identifying books / items smartly. The Radio Frequency Identification sensor uses a reader to get information about the item from a tag attached to it. Smart Bag initially used this technology. Technologies or devices which are used in development of The Smart Bag are RFID Sensor, HX711 Load Cell Sensor, NodeMCU, Arduino, and GPS. The Books / items can be identified by using RFID tag and it will store the count of books / items to its memory and matches the items according to schedule. The circuit for communication comprises of NodeMCU and RFID receiver in which passing of messages / alerts, reading of books / item is done. When the books / items are placed inside the bag, the RFID receiver reads the RFID Tag and sends the Books / items in the bag to the NodeMCU [2]. The NodeMCU compares it with the schedule list. If any book / item is missing then the NodeMCU generates an alert of missing books / item. The smart bag has GPS function also, which sends the Real-time Location of a Bag or a Kid to the Guardian or Parents. Initially, this project is for those small kids who regularly go to school.","PeriodicalId":413368,"journal":{"name":"Proceedings of Intelligent Computing and Technologies Conference","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124278830","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: 0

Stock Price Prediction: LSTM Based Model 股票价格预测:基于LSTM的模型

Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-07-12 DOI: 10.21467/proceedings.115.19

Ranjan Roy, K. Ghosh, Apurbalal Senapati

引用次数: 0

Study of Horizontal Impact Forces Arising from Terrain on Off-Road Vehicles and Minimizing Their Effects on Ride Quality 地形对越野车辆水平冲击力及对平顺性影响最小化的研究

Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-06-28 DOI: 10.21467/proceedings.115.18

Bitopan Das, R. Ghosh

{"title":"Study of Horizontal Impact Forces Arising from Terrain on Off-Road Vehicles and Minimizing Their Effects on Ride Quality","authors":"Bitopan Das, R. Ghosh","doi":"10.21467/proceedings.115.18","DOIUrl":"https://doi.org/10.21467/proceedings.115.18","url":null,"abstract":"Vehicles with off-road capabilities in the present times have begun to focus more on ride comfort. One of the most common uses of such vehicles is to help commuters travel on rough terrain, away from paved roads. Vertical suspensions carry out the work of minimizing the impact from objects like rocks and stones that comprise the terrain. However, such undulations in the terrain are not just vertically bulged. The geometry of the object, i.e., the rock/stone and the wheel coming in contact with the object gives rise to the familiar vertical impact forces for which vertical suspensions are provided. The other component of the impact force arising from the same irregular geometry of the undulation, i.e., the horizontal component of impact force which acts parallel to the axle of the wheels remains neglected. This might lead to passengers experiencing sideways swaying while inside the vehicle, even if there are independent vertical suspensions. In this paper, a study of the effects of horizontal component of impact forces on off-road vehicles was done and after that, spring-shock absorber arrangements to counter these forces were analyzed with springs of different spring-stiffness values.","PeriodicalId":413368,"journal":{"name":"Proceedings of Intelligent Computing and Technologies Conference","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114156106","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: 0

A Machine Learning Based Approach for Software Test Case Selection 基于机器学习的软件测试用例选择方法

Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-06-28 DOI: 10.21467/proceedings.115.25

Victor Cheruiyot, B. Saha

引用次数: 1

Distribution System Fault Analysis Using MATLAB/SIMULINK 基于MATLAB/SIMULINK的配电系统故障分析

Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-06-28 DOI: 10.21467/proceedings.115.4

Jyotirmoy Hazarika, O. P. Roy

引用次数: 0

Twitter Data Sentiment Analysis to Understand the Effects of COVID-19 on Mental Health 推特数据情绪分析，以了解COVID-19对心理健康的影响

Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-06-28 DOI: 10.21467/proceedings.115.23

Adeola Ayandeyi, B. Saha

{"title":"Twitter Data Sentiment Analysis to Understand the Effects of COVID-19 on Mental Health","authors":"Adeola Ayandeyi, B. Saha","doi":"10.21467/proceedings.115.23","DOIUrl":"https://doi.org/10.21467/proceedings.115.23","url":null,"abstract":"Coronavirus pandemic has caused major change in peoples’ personal and social lives. The psychological effects have been substantial because it has affected the ways people live, work, and even socialize. It has also become major discussions on social media platforms as people showcase their opinions and the effect of the virus on their mental health particularly. This pandemic is the first of its kind as humans has never encountered anything like this virus. Handling it was very difficult at first as its characteristics are peculiar. Eventually, it was detected that it is airborne and so there is need to social distance. Before the virus surfaced, some countries of the world were dealing with mental health cases, with over 40 percent of adults in the USA reported experiencing mental health challenges, including anxiety and depression. Social media has become one of the major sources of information due to information sharing on a very large scale. People perception and emotions are also portrayed through their conversations. In this research work, the interaction and conversation of people on social media, particularly Twitter, will be analyzed using machine learning tools and algorithm to determine the effect of the virus on the mental health of people and help suggest the area of concentration to medical practitioners in order to speed up the recovery process and reduce the mental health issues which has escalated due to the virus.","PeriodicalId":413368,"journal":{"name":"Proceedings of Intelligent Computing and Technologies Conference","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122312736","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: 0

Data Mining and Principal Component Analysis on Coimbra Breast Cancer Dataset 科英布拉乳腺癌数据集的数据挖掘与主成分分析

Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-06-28 DOI: 10.21467/proceedings.115.5

A. Sen

引用次数: 0

Application of Swarm-Based Feature Selection and Extreme Learning Machines in Lung Cancer Risk Prediction 基于群的特征选择和极限学习机在肺癌风险预测中的应用

Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-06-28 DOI: 10.21467/proceedings.115.1

Priyam Garg, Deepti Aggarwal

{"title":"Application of Swarm-Based Feature Selection and Extreme Learning Machines in Lung Cancer Risk Prediction","authors":"Priyam Garg, Deepti Aggarwal","doi":"10.21467/proceedings.115.1","DOIUrl":"https://doi.org/10.21467/proceedings.115.1","url":null,"abstract":"Lung cancer risk prediction models help in identifying high-risk individuals for early CT screening tests. These predictive models can play a pivotal role in healthcare by decreasing lung cancer's mortality rate and saving many lives. Although many predictive models have been developed that use various features, no specific guidelines have been provided regarding the crucial features in lung cancer risk prediction. This study proposes novel risk prediction models using bio-inspired swarm-based techniques for feature selection and extreme learning machines for classification. The proposed models are applied on a public dataset consisting of 1000 patient records and 23 variables, including sociodemographic factors, smoking status, and lung cancer clinical symptoms. The models, validated using 10-fold cross-validation, achieve an AUC score in the range of 0.985 to 0.989, accuracy in the range of 0.986 to 0.99 and F-Measure in range of 0.98 to 0.985. The study also identifies smoking habits, exposure to air pollution, occupational hazards and some clinical symptoms as the most commonly selected lung cancer risk prediction features. The study concludes that the developed lung cancer risk prediction models can be successfully applied for early screening, diagnosis and treatment of high-risk individuals.","PeriodicalId":413368,"journal":{"name":"Proceedings of Intelligent Computing and Technologies Conference","volume":"288 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115893415","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: 0

Anomaly Detection using Similarity Approach on Airline Data 基于相似度方法的航空数据异常检测

Proceedings of Intelligent Computing and Technologies Conference Pub Date : 2021-06-28 DOI: 10.21467/proceedings.115.15

Utpal Kumar Sikdar, K. M. Kumar

引用次数: 0