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International Journal of Data Analysis Techniques and Strategies最新文献

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Detecting text in license plates using a novel MSER-based method 基于mser的车牌文本检测方法
International Journal of Data Analysis Techniques and Strategies Pub Date : 2020-01-01 DOI: 10.1504/ijdats.2020.10033823
Mohamed Admi, S. Fkihi, R. Faizi
{"title":"Detecting text in license plates using a novel MSER-based method","authors":"Mohamed Admi, S. Fkihi, R. Faizi","doi":"10.1504/ijdats.2020.10033823","DOIUrl":"https://doi.org/10.1504/ijdats.2020.10033823","url":null,"abstract":"","PeriodicalId":38582,"journal":{"name":"International Journal of Data Analysis Techniques and Strategies","volume":"52 1","pages":"335-348"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77950152","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
A novel integrated principal component analysis and support vector machines-based diagnostic system for detection of chronic kidney disease 基于主成分分析和支持向量机的慢性肾脏疾病诊断系统
International Journal of Data Analysis Techniques and Strategies Pub Date : 2020-01-01 DOI: 10.1504/ijdats.2020.106641
A. Khamparia, Babita Pandey
{"title":"A novel integrated principal component analysis and support vector machines-based diagnostic system for detection of chronic kidney disease","authors":"A. Khamparia, Babita Pandey","doi":"10.1504/ijdats.2020.106641","DOIUrl":"https://doi.org/10.1504/ijdats.2020.106641","url":null,"abstract":"","PeriodicalId":38582,"journal":{"name":"International Journal of Data Analysis Techniques and Strategies","volume":"77 1","pages":"99-113"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76492593","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
Data aggregation to better understand the impact of computerisation on employment 收集数据，以了解电脑化对就业的影响
International Journal of Data Analysis Techniques and Strategies Pub Date : 2020-01-01 DOI: 10.1504/ijdats.2020.10033820
James Otto, Chaodong Han
{"title":"Data aggregation to better understand the impact of computerisation on employment","authors":"James Otto, Chaodong Han","doi":"10.1504/ijdats.2020.10033820","DOIUrl":"https://doi.org/10.1504/ijdats.2020.10033820","url":null,"abstract":"","PeriodicalId":38582,"journal":{"name":"International Journal of Data Analysis Techniques and Strategies","volume":"96 1","pages":"299-317"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77882823","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
Prediksi Klasemen Akhir Kompetisi Sepakbola Indonesia Menggunakan Metode Perluasan Ekspektasi Phytagoras 根据对印尼足球比赛最后一轮比赛的预测，使用扩增对植物的期望方法
International Journal of Data Analysis Techniques and Strategies Pub Date : 2019-12-20 DOI: 10.24815/JARSP.V%VI%I.14123
Aceng Komarudin Mutaqin, Yhupi Praga Adri
{"title":"Prediksi Klasemen Akhir Kompetisi Sepakbola Indonesia Menggunakan Metode Perluasan Ekspektasi Phytagoras","authors":"Aceng Komarudin Mutaqin, Yhupi Praga Adri","doi":"10.24815/JARSP.V%VI%I.14123","DOIUrl":"https://doi.org/10.24815/JARSP.V%VI%I.14123","url":null,"abstract":"Makalah ini menerapkan metode perluasan ekspektasi Phytagoras pada data hasil pertandingan kompetisi sepak bola Liga Indonesia untuk memprediksi klasemen akhir kompetisi. Jumlah gol memasukan dan jumlah gol kemasukan dalam suatu pertandingan dari suatu tim selama satu musim kompetisi dimodelkan sebagai peubah acak yang berdistribusi Poisson. Dalam makalah ini data yang digunakan adalah data hasil pertandingan kompetisi sepakbola Indonesia Super League (ISL) tahun 2013. Hasil pengolahan data menunjukkan bahwa metode perluasan ekspektasi Phytagoras dengan asumsi distribusi Poisson mampu mengelompokkan dengan baik ranking dari tim peserta kompetisi ISL 2013. This paper applies the method of extending Pythagoras’ expectations to the results of the matches of the Indonesian League soccer competition to predict the final standings of the competition. The number of goals entered and the number of goals conceded in a match from a team for one season is modeled as a random variable with Poisson distribution. In this paper the data used is data on the results of the 2013 Indonesia Super League (ISL) soccer competition. The results of data processing showed that the method of expansion of Pythagoras’ expectations assuming the Poisson distribution was able to classify the ranking of participants of the ISL 2013 competition well. The team whose performance exceeds expectations is the PERSELA Team. While the team whose performance is below expectations is the SRIWIJAYA Team.","PeriodicalId":38582,"journal":{"name":"International Journal of Data Analysis Techniques and Strategies","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82218772","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
Data mining classification techniques - comparison for better accuracy in prediction of cardiovascular disease 数据挖掘分类技术——在心血管疾病预测中提高准确性的比较
International Journal of Data Analysis Techniques and Strategies Pub Date : 2019-11-25 DOI: 10.1504/ijdats.2019.103756
Richa Sharma, S. Singh, Sujata Khatri
{"title":"Data mining classification techniques - comparison for better accuracy in prediction of cardiovascular disease","authors":"Richa Sharma, S. Singh, Sujata Khatri","doi":"10.1504/ijdats.2019.103756","DOIUrl":"https://doi.org/10.1504/ijdats.2019.103756","url":null,"abstract":"Cardiovascular disease is a broad term which includes stroke or any disorder in the cardiovascular system that has the heart at its centre. This disease is a critical cause of mortality every year across the globe. Data mining utilises a variety of techniques and algorithms that could help to draw some interesting conclusions about cardiovascular disease. Data mining in healthcare can assist in predicting disease. This study aims to gain knowledge from a heart disease dataset and analyse several data mining classification techniques seeking improved accuracy and a lesser error rate in the results. The data set for the experiment is chosen from the UCI machine learning repository database. The dataset is analysed using two different data mining tools, i.e., WEKA and Tanagra. The analysis was done using the 10 fold cross validation technique. The results show that the Naive Bayes algorithm and the C-PLS algorithm outperform others with an accuracy of 83.71% and 84.44% respectively.","PeriodicalId":38582,"journal":{"name":"International Journal of Data Analysis Techniques and Strategies","volume":"26 1","pages":"356-373"},"PeriodicalIF":0.0,"publicationDate":"2019-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82141182","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: 5
Real-time data warehouse loading methodology and architecture: a healthcare use case 实时数据仓库加载方法和体系结构:一个医疗保健用例
International Journal of Data Analysis Techniques and Strategies Pub Date : 2019-11-25 DOI: 10.1504/ijdats.2019.103757
Hanen Bouali, J. Akaichi, Ala Gaaloul
{"title":"Real-time data warehouse loading methodology and architecture: a healthcare use case","authors":"Hanen Bouali, J. Akaichi, Ala Gaaloul","doi":"10.1504/ijdats.2019.103757","DOIUrl":"https://doi.org/10.1504/ijdats.2019.103757","url":null,"abstract":"In the healthcare context, existing systems suffer from the lack of supporting heterogeneity and dynamism. Consequently, resulting from sensors, streaming data brought another dimension to data mining research. This is due to the fact that, in data streams, only a time window is available. Contrary to the traditional data sources, data streams present new characteristics as being continuous, high-volume, open-ended and concept drift. To analyse event streams, data warehouse seems to be the answer to this problematic. However, classical data warehouse does not incorporate the specificity of event streams that are spatial, temporal, semantic and real-time. For these reasons, we focus inhere on presenting the conceptual modelling, the architecture and loading methodology of the real-time data warehouse by defining a new dimensionality and stereotype for classical data warehouse. To prove the efficiency of our real-time data warehouse, we adapt the model to a medical unit pregnancy care case study which show promising results.","PeriodicalId":38582,"journal":{"name":"International Journal of Data Analysis Techniques and Strategies","volume":"67 1","pages":"310-327"},"PeriodicalIF":0.0,"publicationDate":"2019-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73755237","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: 4
Enhanced auto associative neural network using feed forward neural network: an approach to improve performance of fault detection and analysis 基于前馈神经网络的增强自动关联神经网络:一种提高故障检测与分析性能的方法
International Journal of Data Analysis Techniques and Strategies Pub Date : 2019-11-21 DOI: 10.1504/ijdats.2019.103754
Subhas A. Meti, V. Sangam
{"title":"Enhanced auto associative neural network using feed forward neural network: an approach to improve performance of fault detection and analysis","authors":"Subhas A. Meti, V. Sangam","doi":"10.1504/ijdats.2019.103754","DOIUrl":"https://doi.org/10.1504/ijdats.2019.103754","url":null,"abstract":"Biosensors have played a significant role in many of present day's applications ranging from military applications to healthcare sectors. However, its practicality and robustness in its usage in real time scenario is still a matter of concern. Primarily issues such as prediction of sensor data, noise estimation and channel estimation and most importantly in fault detection and analysis. In this paper an enhancement is applied to the auto associative neural network (AANN) by considering the cascade feed forward propagation. The residual noise is also computed along with fault detection and analysis of the sensor data. An experimental result shows a significant reduction in the MSE as compared to conventional AANN. The regression based correlation coefficient has improved in the proposed method as compared to conventional AANN.","PeriodicalId":38582,"journal":{"name":"International Journal of Data Analysis Techniques and Strategies","volume":"19 1","pages":"291-309"},"PeriodicalIF":0.0,"publicationDate":"2019-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82695929","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
Sentiment analysis-based framework for assessing internet telemedicine videos 基于情感分析的网络远程医疗视频评估框架
International Journal of Data Analysis Techniques and Strategies Pub Date : 2019-11-21 DOI: 10.1504/ijdats.2019.103755
P. M. Arunkumar, S. Chandramathi, S. Kannimuthu
{"title":"Sentiment analysis-based framework for assessing internet telemedicine videos","authors":"P. M. Arunkumar, S. Chandramathi, S. Kannimuthu","doi":"10.1504/ijdats.2019.103755","DOIUrl":"https://doi.org/10.1504/ijdats.2019.103755","url":null,"abstract":"Telemedicine services through internet and mobile devices need effective medical video delivery systems. This work describes a novel framework to study the assessment of internet-based telemedicine videos using sentiment analysis. The dataset comprises more than 1,000 text comments of medical experts collected from various medical animation videos of Youtube repository. The proposed framework deploys machine learning classifiers such as Bayes net, KNN, C 4.5 decision tree, support vector machine (SVM) and SVM with particle swarm optimisation (SVM-PSO) to infer opinion mining outputs. The results portray that SVM-PSO classifier performs better in assessing the reviews of medical video content with more than 80% accuracy. The model's inference of precision and recall values using SVM-PSO algorithm shows 87.8% and 85.57% respectively and henceforth underlines its superiority over other classifiers. The concepts of sentiment analysis can be applied effectively to the web-based user comments of medical videos and the end results can be highly critical to enhance the reputation of telemedicine education across the globe.","PeriodicalId":38582,"journal":{"name":"International Journal of Data Analysis Techniques and Strategies","volume":"21 1","pages":"328-336"},"PeriodicalIF":0.0,"publicationDate":"2019-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90558066","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: 12
Enhancement of SentiWordNet using contextual valence shifters 使用上下文价移位器增强SentiWordNet
International Journal of Data Analysis Techniques and Strategies Pub Date : 2019-11-21 DOI: 10.1504/ijdats.2019.103758
Poornima Mehta, Satish Chandra
{"title":"Enhancement of SentiWordNet using contextual valence shifters","authors":"Poornima Mehta, Satish Chandra","doi":"10.1504/ijdats.2019.103758","DOIUrl":"https://doi.org/10.1504/ijdats.2019.103758","url":null,"abstract":"Sentence structure has a considerable impact on the sentiment polarity of a sentence. In the presence of contextual valence shifters like conjunctions, conditionals and intensifiers some parts of the sentence are more relevant to determine the sentence polarity. In this work we have used valence shifters in sentences to enhance the sentiment lexicon SentiWordNet in a given document set. They have also been used to improve the sentiment analysis at document level. In the near past, micro blogging services like Twitter have become an important data source for sentiment analysis. Tweets, being restricted to 140 characters have slangs, are grammatically incorrect, have spelling mistakes and have informal expressions. The method is aimed at noisy and unstructured data like tweets on which computationally intensive tools like dependency parsers are not very successful. Our proposed system works better on both noisy (Stanford and airlines datasets of Twitter) and structured (movie review) datasets.","PeriodicalId":38582,"journal":{"name":"International Journal of Data Analysis Techniques and Strategies","volume":"46 1","pages":"337-355"},"PeriodicalIF":0.0,"publicationDate":"2019-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74154671","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: 3
Suatu Kajian Tentang Bilangan Sempurna
International Journal of Data Analysis Techniques and Strategies Pub Date : 2019-08-18 DOI: 10.24815/JDA.V2I1.12421
Saiful Amri, M. Mahmudi
{"title":"Suatu Kajian Tentang Bilangan Sempurna","authors":"Saiful Amri, M. Mahmudi","doi":"10.24815/JDA.V2I1.12421","DOIUrl":"https://doi.org/10.24815/JDA.V2I1.12421","url":null,"abstract":"Dalam tulisan ini akan dijelaskan mengenai kriteria bilangan sempurna genap dan bentuk bilangan sempurna ganjil (jika ada). Jika $2^k-1$  prima maka $2^{k-1}(2^k-1)$  berupa bilangan sempurna. Sebaliknya, semua bilangan sempurna genap berbentuk $2^{k-1}(2^k-1)$ , dimana $2^k-1$ prima. Maka masalah menentukan bilangan sempurna genap setara dengan menentukan $k$ sehingga $2^k-1$  prima. Bilangan $2^k-1$ disebut sebagai bilangan Mersenne dan ditulis dengan $M_k$. In this paper will be explained about the criteria of the even perfect numbers and the form of odd perfect numbers (if any). If is prime, then is perfect. Conversely, all even perfect numbers are of the form with is a prime. Thus, finding even perfect numbers is equivalent to find the integers for which is prime. The numbers of the form called Mersenne numbers and is denoted by .","PeriodicalId":38582,"journal":{"name":"International Journal of Data Analysis Techniques and Strategies","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82871854","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
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