International journal of artificial intelligence & applications最新文献_第2页

Data Augmentation Techniques and Transfer Learning Approaches Applied to Facial Expressions Recognition Systems 数据增强技术和迁移学习方法在人脸表情识别系统中的应用

International journal of artificial intelligence & applications Pub Date : 2022-01-31 DOI: 10.5121/ijaia.2022.13104

Enrico Randellini, Leonardo Rigutini, Claudio Saccà

引用次数: 0

Movie Success Prediction and Performance Comparison using Various Statistical Approaches 电影成功预测和性能比较使用各种统计方法

International journal of artificial intelligence & applications Pub Date : 2022-01-31 DOI: 10.5121/ijaia.2022.13102

Manav Agarwal, S. Venugopal, Rishab Kashyap, R. Bharathi

{"title":"Movie Success Prediction and Performance Comparison using Various Statistical Approaches","authors":"Manav Agarwal, S. Venugopal, Rishab Kashyap, R. Bharathi","doi":"10.5121/ijaia.2022.13102","DOIUrl":"https://doi.org/10.5121/ijaia.2022.13102","url":null,"abstract":"Movies are among the most prominent contributors to the global entertainment industry today, and they are among the biggest revenue-generating industries from a commercial standpoint. It's vital to divide films into two categories: successful and unsuccessful. To categorize the movies in this research, a variety of models were utilized, including regression models such as Simple Linear, Multiple Linear, and Logistic Regression, clustering techniques such as SVM and K-Means, Time Series Analysis, and an Artificial Neural Network. The models stated above were compared on a variety of factors, including their accuracy on the training and validation datasets as well as the testing dataset, the availability of new movie characteristics, and a variety of other statistical metrics. During the course of this study, it was discovered that certain characteristics have a greater impact on the likelihood of a film's success than others. For example, the existence of the genre action may have a significant impact on the forecasts, although another genre, such as sport, may not. The testing dataset for the models and classifiers has been taken from the IMDb website for the year 2020. The Artificial Neural Network, with an accuracy of 86 percent, is the best performing model of all the models discussed.","PeriodicalId":93188,"journal":{"name":"International journal of artificial intelligence & applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47463314","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

Reviewing Process Mining Applications and Techniques in Education 回顾过程挖掘在教育中的应用和技术

International journal of artificial intelligence & applications Pub Date : 2022-01-31 DOI: 10.5121/ijaia.2022.13106

Athanasios Sypsas, D. Kalles

引用次数: 4

Artificial Intelligence Techniques for the Modeling of a 3G Mobile Phone Base Radio 用于3G移动电话基站无线电建模的人工智能技术

International journal of artificial intelligence & applications Pub Date : 2022-01-31 DOI: 10.5121/ijaia.2022.13107

Eduardo Calo, Gabriel Vaca, Cristina Sánchez, David Jines, Giovanny Amancha, Ángel Flores, A. Santana G, Fernanda Oñate

{"title":"Artificial Intelligence Techniques for the Modeling of a 3G Mobile Phone Base Radio","authors":"Eduardo Calo, Gabriel Vaca, Cristina Sánchez, David Jines, Giovanny Amancha, Ángel Flores, A. Santana G, Fernanda Oñate","doi":"10.5121/ijaia.2022.13107","DOIUrl":"https://doi.org/10.5121/ijaia.2022.13107","url":null,"abstract":"The principal objective of this work is to be able to use artificial intelligence techniques to be able to design a predictive model of the performance of a third-generation mobile phone base radio, using the analysis of KPIs obtained in a statistical data set of the daily behaviour of an RBS. For the realization of these models, various techniques such as Decision Trees, Neural Networks and Random Forest were used. which will allow faster progress in the deep analysis of large amounts of data statistics and get better results. In this part of the work, data was obtained from the behaviour of a third-party mobile phone base radio generation of the Claro operator in Ecuador, it should be noted that. To specify this practical case, several models were generated based on in various artificial intelligence technique for the prediction of performance results of a mobile phone base radio of third generation, the same ones that after several tests were creation of a predictive model that determines the performance of a mobile phone base radio. As a conclusion of this work, it was determined that the development of a predictive model based on artificial intelligence techniques is very useful for the analysis of large amounts of data in order to find or predict complex results, more quickly and trustworthy. The data are KPIs of the daily and hourly performance of a radio base of third generation mobile telephony, these data were obtained through the operator's remote monitoring and management tool Sure call PRS.","PeriodicalId":93188,"journal":{"name":"International journal of artificial intelligence & applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47192335","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

Digital Transformation of Financial Services using Artificial Intelligence, Machine Learning, and Cloud Computing 利用人工智能、机器学习和云计算实现金融服务的数字化转型

International journal of artificial intelligence & applications Pub Date : 2021-11-30 DOI: 10.5121/ijaia.2021.12603

Prudhvi Parne

{"title":"Digital Transformation of Financial Services using Artificial Intelligence, Machine Learning, and Cloud Computing","authors":"Prudhvi Parne","doi":"10.5121/ijaia.2021.12603","DOIUrl":"https://doi.org/10.5121/ijaia.2021.12603","url":null,"abstract":"Digital disruption is redefining industries and changing the way business function. Artificial Intelligence is the future of banking as it brings the power of advanced data analytics to combat fraudulent transactions and improve compliance. Financial services are the economical backbone of any nation in the world. There are billions of financial transactions which are taking place and all this data is stored and can be considered as a gold mine of data for many different organizations. No human intelligence can dig in this amount of data to come up with something valuable. This is the reason financial organizations are employing artificial intelligence to come up with new algorithms which can change the way financial transactions are being carried out. Artificial Intelligence can complete the task in a very short period. Artificial intelligence can be used to detect frauds, identify possible attacks, and any other kind of anomalies that may be detrimental for the institution. This paper discusses the role of artificial intelligence and machine learning in the finance sector. Additionally, the paper will provide the necessary strategies that any banking organization can follow when digitizing its operations when implementing Artificial Intelligence, Machine learning and Cloud Computing.","PeriodicalId":93188,"journal":{"name":"International journal of artificial intelligence & applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44541852","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 New Perspective of Paramodulation Complexity by Solving 100 Sliding Block Puzzles 从解100个滑块难题看调变复杂度

International journal of artificial intelligence & applications Pub Date : 2021-11-30 DOI: 10.5121/ijaia.2021.12604

R. Ando, Yoshiyasu Takefuji

{"title":"A New Perspective of Paramodulation Complexity by Solving 100 Sliding Block Puzzles","authors":"R. Ando, Yoshiyasu Takefuji","doi":"10.5121/ijaia.2021.12604","DOIUrl":"https://doi.org/10.5121/ijaia.2021.12604","url":null,"abstract":"This paper gives complete guidelines for authors submitting papers for the AIRCC Journals. A sliding puzzle is a combination puzzle where a player slides pieces along specific routes on a board to reach a certain end configuration. In this paper, we propose a novel measurement of the complexity of 100 sliding puzzles with paramodulation, which is an inference method of automated reasoning. It turned out that by counting the number of clauses yielded with paramodulation, we can evaluate the difficulty of each puzzle. In the experiment, we have generated 100 * 8 puzzles that passed the solvability checking by countering inversions. By doing this, we can distinguish the complexity of 8 puzzles with the number generated with paramodulation. For example, board [2,3,6,1,7,8,5,4, hole] is the easiest with score 3008 and board [6,5,8,7,4,3,2,1, hole] is the most difficult with score 48653.Besides, we have succeeded in obverse several layers of complexity (the number of clauses generated) in 100 puzzles. We can conclude that the proposed method can provide a new perspective of paramodulation complexity concerning sliding block puzzles.","PeriodicalId":93188,"journal":{"name":"International journal of artificial intelligence & applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42759253","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

Automation of Best-Fit Model Selection using a Bag of Machine Learning Libraries for Sales Forecasting 使用一袋用于销售预测的机器学习库实现最佳拟合模型选择的自动化

International journal of artificial intelligence & applications Pub Date : 2021-11-30 DOI: 10.5121/ijaia.2021.12602

Pauline Sherly Jeba P, Manju Kiran, A. Sharma, Divakar Venkatesh

引用次数: 1

A Knowledge based Automatic Radiation Treatment Plan Alert System 基于知识的放射治疗计划自动预警系统

International journal of artificial intelligence & applications Pub Date : 2021-11-30 DOI: 10.5121/ijaia.2021.12601

Erwei Bai, J. Xia

引用次数: 1

Automatic Home-based Screening of Obstructive Sleep Apnea using Single Channel Electrocardiogram and SPO2 Signals 基于单通道心电图和SPO2信号的阻塞性睡眠呼吸暂停家庭自动筛查

International journal of artificial intelligence & applications Pub Date : 2021-10-01 DOI: 10.5121/ijaia.2021.12605

H. Ghandeharioun

{"title":"Automatic Home-based Screening of Obstructive Sleep Apnea using Single Channel Electrocardiogram and SPO2 Signals","authors":"H. Ghandeharioun","doi":"10.5121/ijaia.2021.12605","DOIUrl":"https://doi.org/10.5121/ijaia.2021.12605","url":null,"abstract":"Obstructive sleep apnea (OSA) is one of the most widespread respiratory diseases today. Complete or relative breathing cessations due to upper airway subsidence during sleep is OSA. It has confirmed potential influence on Covid-19 hospitalization and mortality, and is strongly associated with major comorbidities of severe Covid-19 infection. Un-diagnosed OSA may also lead to a variety of severe physical and mental side-effects. To score OSA severity, nocturnal sleep monitoring is performed under defined protocols and standards called polysomnography (PSG). This method is time-consuming, expensive, and requiring professional sleep technicians. Automatic home-based detection of OSA is welcome and in great demand. It is a fast and effective way for referring OSA suspects to sleep clinics for further monitoring. On-line OSA detection also can be a part of a closed-loop automatic control of the OSA therapeutic/assistive devices. In this paper, several solutions for online OSA detection are introduced and tested on 155 subjects of three different databases. The best combinational solution uses mutual information (MI) analysis for selecting out of ECG and SpO2-based features. Several methods of supervised and unsupervised machine learning are employed to detect apnoeic episodes. To achieve the best performance, the most successful classifiers in four different ternary combination methods are used. The proposed configurations exploit limited use of biological signals, have online working scheme, and exhibit uniform and acceptable performance (over 85%) in all the employed databases. The benefits have not been gathered all together in the previous published methods.","PeriodicalId":93188,"journal":{"name":"International journal of artificial intelligence & applications","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43303069","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

Finding Facial Expression Patterns on Videos based on Smile and Eyes-Open Confidence Values 基于微笑和睁开眼睛的自信值寻找视频中的面部表情模式

International journal of artificial intelligence & applications Pub Date : 2021-09-30 DOI: 10.5121/ijaia.2021.12503

S. Hadi, Asep K Supriatna, Faishal Wahiduddin, W. Srisayekti, A. Djunaidi, E. Fitriana, A. Abdullah, D. Ekawati

引用次数: 0