IAES International Journal of Artificial Intelligence最新文献_第10页

Classification and visualization: Twitter sentiment analysis of Malaysia’s private hospitals 分类和可视化:马来西亚私立医院的Twitter情绪分析

IAES International Journal of Artificial Intelligence Pub Date : 2023-01-01 DOI: 10.11591/ijai.v12.i4.pp1793-1802

Khyrina Airin Fariza Abu Samah, Nur Maisarah Nor Azharludin, L. Riza, M.N.H. Hasrol Jono, N. A. Moketar

{"title":"Classification and visualization: Twitter sentiment analysis of Malaysia’s private hospitals","authors":"Khyrina Airin Fariza Abu Samah, Nur Maisarah Nor Azharludin, L. Riza, M.N.H. Hasrol Jono, N. A. Moketar","doi":"10.11591/ijai.v12.i4.pp1793-1802","DOIUrl":"https://doi.org/10.11591/ijai.v12.i4.pp1793-1802","url":null,"abstract":"Malaysia has many private’s hospitals. Thus, feedback is important to improve service quality, becoming reviews for other patients. Reviews use the channel service provided on social media, such as Twitter. Nevertheless, online reviews are unstructured and enormous in volume, which leads to difficulties in comparing private hospitals. In addition, no single websites compare private hospitals based on users’ interests, bilingual reviews, and less time-consuming. Due to that, this study aims to classify and visualize the Twitter sentiment analysis of private hospitals in Malaysia. The scope focuses on five factors: 1) administrative procedure, 2) cost, 3) communication, 4) expertise, and 5) service. Term frequency-inverse document frequency is used for text mining, information retrieval techniques, and the Naïve Bayes, a machine learning algorithm for the classification. The user can visualize the specified state’s private hospitals and compare them with any selected state. The system’s functionality and usability have been tested to ensure it meets the objectives. Functionality testing proved that the private hospital’s Twitter sentiment could be predicted based on the training and testing data as intended, with 77.13% and 77.96% accuracy for English and Bahasa Melayu, respectively, while the system usability scale based on the usability testing resulted in an average final score of 95.42%.","PeriodicalId":52221,"journal":{"name":"IAES International Journal of Artificial Intelligence","volume":"186 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65354628","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

Dyslexia deep clustering using webcam-based eye tracking 基于网络摄像头的眼动追踪的阅读障碍深度聚类

IAES International Journal of Artificial Intelligence Pub Date : 2023-01-01 DOI: 10.11591/ijai.v12.i4.pp1892-1900

Mohamed Ikermane, A. E. Mouatasim

{"title":"Dyslexia deep clustering using webcam-based eye tracking","authors":"Mohamed Ikermane, A. E. Mouatasim","doi":"10.11591/ijai.v12.i4.pp1892-1900","DOIUrl":"https://doi.org/10.11591/ijai.v12.i4.pp1892-1900","url":null,"abstract":"Dyslexia is a neurodevelopmental impairment that causes difficulties in reading and can have significant academic, social, and economic impacts. In Morocco, Dyslexia accounts for 37% of children's school failures. Early detection of dyslexia is crucial to help children reach their academic potential and prevent low self-esteem. To address this issue, a dyslexia screening tool using webcam-based eye tracking was developed for the Arabic language. The tool was tested on a dataset of 61 students from three primary schools in southern Morocco, and the results showed that using Arabic dyslexic-friendly typefaces improved reading performance, particularly for those with low reading performance. Deep clustering was used to reduce the dimensionality of the dataset, and the subjects were gathered using unsupervised k-means based on AutoEncoder output. The three clusters produced showed a significant difference in many dyslexia traits, such as the number and duration of fixations, as well as the saccade period. These findings suggest that webcam-based eye-tracking techniques have the potential to be used as an initial dyslexia diagnosis tool to assess if a child exhibits some of the typical symptoms of dyslexia and whether they should seek a professional full dyslexia diagnosis.","PeriodicalId":52221,"journal":{"name":"IAES International Journal of Artificial Intelligence","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65355368","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

Improving Indonesian multietnics speaker recognition using pitch shifting data augmentation 利用频移数据增强改进印尼语多民族说话人识别

IAES International Journal of Artificial Intelligence Pub Date : 2023-01-01 DOI: 10.11591/ijai.v12.i4.pp1901-1908

Kristiawan Nugroho, Isworo Nugroho, De Rosal Ignatius Moses Setiadi, Omar Farooq

{"title":"Improving Indonesian multietnics speaker recognition using pitch shifting data augmentation","authors":"Kristiawan Nugroho, Isworo Nugroho, De Rosal Ignatius Moses Setiadi, Omar Farooq","doi":"10.11591/ijai.v12.i4.pp1901-1908","DOIUrl":"https://doi.org/10.11591/ijai.v12.i4.pp1901-1908","url":null,"abstract":"Speaker recognition to recognize multiethnic speakers is an interesting research topic. Various studies involving many ethnicities require the right approach to achieve optimal model performance. The deep learning approach has been used in speaker recognition research involving many classes to achieve high accuracy results with promising results. However, multi-class and imbalanced datasets are still obstacles encountered in various studies using the deep learning method which cause overfitting and decreased accuracy. Data augmentation is an approach model used in overcoming the problem of small amounts of data and multiclass problems. This approach can improve the quality of research data according to the method applied. This study proposes a data augmentation method using pitch shifting with a deep neural network called pitch shifting data augmentation deep neural network (PSDA-DNN) to identify multiethnic Indonesian speakers. The results of the research that has been done prove that the PSDA-DNN approach is the best method in multi-ethnic speaker recognition where the accuracy reaches 99.27% and the precision, recall, F1 score is 97.60%.","PeriodicalId":52221,"journal":{"name":"IAES International Journal of Artificial Intelligence","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65355388","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

Low-cost convolutional neural network for tomato plant diseases classifiation 低成本卷积神经网络在番茄病害分类中的应用

IAES International Journal of Artificial Intelligence Pub Date : 2023-01-01 DOI: 10.11591/ijai.v12.i1.pp162-170

Soumia Bensaadi, A. Louchene

引用次数: 6

Hybrid gated recurrent unit bidirectional-long short-term memory model to improve cryptocurrency prediction accuracy 提高加密货币预测精度的混合门控循环单元双向长短期记忆模型

IAES International Journal of Artificial Intelligence Pub Date : 2023-01-01 DOI: 10.11591/ijai.v12.i1.pp251-261

Ferdiansyah Ferdiansyah, S. H. Othman, Raja Zahilah Md Radzi, D. Stiawan, T. Sutikno

引用次数: 5

Neural network-based parking system object detection and predictive modeling 基于神经网络的停车系统目标检测与预测建模

IAES International Journal of Artificial Intelligence Pub Date : 2023-01-01 DOI: 10.11591/ijai.v12.i1.pp66-78

Ziad El Khatib, A. B. Mnaouer, S. Moussa, Omar Mashaal, N. A. Ismail, Mohd Azman Bin Abas, Fuad Abdulgaleel

引用次数: 1

Cuckoo search algorithm for construction site layout planning 布谷鸟搜索算法用于施工现场布局规划

IAES International Journal of Artificial Intelligence Pub Date : 2023-01-01 DOI: 10.11591/ijai.v12.i2.pp851-860

Meilinda Fitriani Nur Maghfiroh, A. A. N. Perwira Redi, Janice Ong, M. Fikri

引用次数: 1

BMSP-ML: big mart sales prediction using different machine learning techniques bsmp - ml:使用不同的机器学习技术进行大型市场销售预测

IAES International Journal of Artificial Intelligence Pub Date : 2023-01-01 DOI: 10.11591/ijai.v12.i2.pp874-883

Rao Faizan Ali, Amgad Muneer, Ahmed Almaghthawi, Amal Alghamdi, Suliman Mohamed Fati, Ebrahim Abdulwasea Abdullah Ghaleb

引用次数: 1

Early prediction of diabetes diagnosis using hybrid classification techniques 利用混合分类技术早期预测糖尿病诊断

IAES International Journal of Artificial Intelligence Pub Date : 2023-01-01 DOI: 10.11591/ijai.v12.i3.pp1139-1148

L. Srinivasan, Reshma Verma, Mysore Dakshinamurthy Nandeesh

{"title":"Early prediction of diabetes diagnosis using hybrid classification techniques","authors":"L. Srinivasan, Reshma Verma, Mysore Dakshinamurthy Nandeesh","doi":"10.11591/ijai.v12.i3.pp1139-1148","DOIUrl":"https://doi.org/10.11591/ijai.v12.i3.pp1139-1148","url":null,"abstract":"Diabetes can be mentioned as one of the most lethal and constant sicknesses that may cause an arise in the glucose levels. Design and development of performance efficient diagnosis tool is important and plays a vigorous role in initial prediction of disease and help medical experts to start with suitable treatment or medication. The insulin produced by pancreases in the subject’s body will be affected leading to several dysfunctionalities to various body organs such as kidney, heart eyes and nervous system with their normal functionalities. Hence, preliminary stage detection with proper care and medication could reduce the risk of these problems. In the area of medicine to discover patient’s data as well as to attain a predictive model or a set of rules, classification techniques have been continuously used. This study helped diagnose diabetes by selecting three important artificial intelligence techniques namely the optimal decision tree algorithm model, Type-2 fuzzy expert system and adaptive neuro fuzzy inference system which is modified. In the present research work, a hybrid model is proposed in order to improve the classification prediction and accuracy. The Pima Indian diabetes dataset from machine learning repository dataset was used to carry out validation and predication of the model accuracy.","PeriodicalId":52221,"journal":{"name":"IAES International Journal of Artificial Intelligence","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65350718","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

Particle swarm optimization for the optimal layout of wind turbines inside a wind farm 风电场内风力机优化布局的粒子群算法

IAES International Journal of Artificial Intelligence Pub Date : 2023-01-01 DOI: 10.11591/ijai.v12.i3.pp1260-1269

Mariam El jaadi, Touria Haidi, Doha Bouabdallaoui

引用次数: 3