Data最新文献_第10页

Similarity Association Pattern Mining in Transaction Databases 事务数据库中的相似关联模式挖掘

IF 2.6

Data Pub Date : 2021-04-05 DOI: 10.1145/3460620.3460752

M. PhridviRaj, C. V. Rao, V. Radhakrishna, Aravind Cheruvu

引用次数: 0

Hybrid solution of challenges future problems in the new generation of the artificial intelligence industry used operations research industrial processes 混合解决未来问题的挑战，在新一代人工智能产业中运用运筹学研究工业流程

IF 2.6

Data Pub Date : 2021-04-05 DOI: 10.1145/3460620.3460757

T. Mohammed, Mohammed N. Qasim, O. Bayat

{"title":"Hybrid solution of challenges future problems in the new generation of the artificial intelligence industry used operations research industrial processes","authors":"T. Mohammed, Mohammed N. Qasim, O. Bayat","doi":"10.1145/3460620.3460757","DOIUrl":"https://doi.org/10.1145/3460620.3460757","url":null,"abstract":"Key technologies such as a new generation of industrial systems highly depends on artificial intelligence, and electronic physical systems that can digitize the entire supply chain together with data mining, machine learning, and more. At present, uses of artificial intelligence-based solutions are very important to improve the accuracy and efficiency of production processes. Artificial intelligence (AI) is playing a key role in the fourth industrial revolution, and we see significant improvements in different methods of machine learning. Artificial intelligence is widely used by practitioner engineers to solve various problems. This journal provides an international forum for quick articles that describes the practical application of artificial intelligence in all areas of mechanical engineering. Many researchers cited the development of technology in industrial fields to reduce problems in industry. Both the Operations Research (OR) community and Artificial Intelligence (AI) show that these problems are still interesting. While AI focuses linearly on increasing production and mitigating industry difficulties that may be seen as a revolution in the future. AI techniques offer a richer and more flexible presentation of real problems. The article presents the architecture of the industrial laboratory and the challenges associated with the use of artificial intelligence in industrial processes.","PeriodicalId":36824,"journal":{"name":"Data","volume":"179 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2021-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74778541","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 Book Recommender System Using Collaborative Filtering Method 基于协同过滤方法的图书推荐系统

IF 2.6

Data Pub Date : 2021-04-05 DOI: 10.1145/3460620.3460744

Sewar Khalifeh, Amjed Al-mousa

引用次数: 4

Assessment of Machine Learning Security: The Case of Healthcare Data 机器学习安全评估:以医疗数据为例

IF 2.6

Data Pub Date : 2021-04-05 DOI: 10.1145/3460620.3460738

Anood Manasrah, Aisha Alkayem, Malik Qasaimeh, Samer Nofal

引用次数: 1

Study of Detection of DDoS attacks in cloud environment Using Regression Analysis 基于回归分析的云环境下DDoS攻击检测研究

IF 2.6

Data Pub Date : 2021-04-05 DOI: 10.1145/3460620.3460750

Arun Nagaraja, U. Boregowda, V. Radhakrishna

引用次数: 6

Physicians' Attitudes towards Electronic Prescribing Software: Perceived Benefits and Barriers 医生对电子处方软件的态度:感知的好处和障碍

IF 2.6

Data Pub Date : 2021-04-05 DOI: 10.1145/3460620.3460629

Wala M. Eltajoury, Abdelsalam M. Maatuk, I. Denna, Ebitisam K. Elberkawi

{"title":"Physicians' Attitudes towards Electronic Prescribing Software: Perceived Benefits and Barriers","authors":"Wala M. Eltajoury, Abdelsalam M. Maatuk, I. Denna, Ebitisam K. Elberkawi","doi":"10.1145/3460620.3460629","DOIUrl":"https://doi.org/10.1145/3460620.3460629","url":null,"abstract":"The use of health information technology has become highly effective in healthcare quality as it enhances personal and public care, broadens diagnostic accuracy, reduces medical costs and errors, and improves the effectiveness of both organizational and clinical processes. This study aims to assess physicians' perceptions of perceived benefits and barriers of electronic prescribing (e-Prescribing) software and their implementation. A self-prepared questionnaire was developed, distributed, and filled by physicians (n = 100) from different departments at Benghazi Medical Center, Libya. The Statistical Package for Social Sciences (SPSS) program was used to analyze the results. The results showed that more than 90% of physicians preferred the e-Prescribing software, with most of them believing that they were able to provide better services to patients by saving time and effort (87%), and checking drug interaction (82%), as well as reducing medical errors (89%). On the other hand, the results indicated that the main barriers are the lack of adequate infrastructure, awareness sessions, and human and material resources. Physicians prefer to use the e-Prescribing software, as it supports decision-makers to design more effective strategies and implementation plans. The study recommended the necessity of holding awareness sessions and training programs for using e-Prescribing software.","PeriodicalId":36824,"journal":{"name":"Data","volume":"26 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2021-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76876303","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

International Conference on Data Science, E-learning and Information Systems 2021 2021年数据科学、电子学习和信息系统国际会议

IF 2.6

Data Pub Date : 2021-01-01 DOI: 10.1145/3460620

引用次数: 2

Learning-Analytics based Intelligent Simulator for Personalised Learning 基于学习分析的个性化学习智能模拟器

IF 2.6

Data Pub Date : 2020-10-20 DOI: 10.1109/ICADEIS49811.2020.9276858

N. Sharef, M. A. Azmi Murad, E. Mansor, Nurul Amelina Nasharuddin, Muhd Khaizer Omar, Normalia Samian, N. Arshad, W. Ismail, F. Shahbodin

引用次数: 5

Age Group Based Document Classification in Bahasa Indonesia 基于年龄组的印尼语文献分类

IF 2.6

Data Pub Date : 2020-10-20 DOI: 10.1109/ICADEIS49811.2020.9277104

M. I. D. Putra, Budi Irmawati, W. Wedashwara, Dita Pramesti, Siti Oryza Khairunnisa

{"title":"Age Group Based Document Classification in Bahasa Indonesia","authors":"M. I. D. Putra, Budi Irmawati, W. Wedashwara, Dita Pramesti, Siti Oryza Khairunnisa","doi":"10.1109/ICADEIS49811.2020.9277104","DOIUrl":"https://doi.org/10.1109/ICADEIS49811.2020.9277104","url":null,"abstract":"Internet provides articles that may be categorized to various target readers based on genders, ages, hobbies, etc. To make sure that readers consume a proper article based on their age group, methods and training data were proposed and collected to classify the articles. This paper reported a document classification based on age groups using a binary classification method for Indonesian documents. The document classification used the term frequency and inverse document frequency (TF-IDF) features run on the Multinomial Naïve Bayes Classifier. The dataset was crowdsourced from three different sites: bobo.grid.id, hai.grid.id, and www.detik.com for three age group readers such as elementary school children, teenagers, and adults. The experimental results obtained 0.9406, 0.9341, and 0.9374 of precision, recall, and F-score respectively. This experiment also reported that for the datasets that were not stemmed performed better than those that were stemmed. It shows that the stemming process, which usually be done in the document classification, throws some information in the Indonesian texts. However, because this behavior was not happen on nouns, our future work is to elaborate further on the role of affixations in the lower age group documents.","PeriodicalId":36824,"journal":{"name":"Data","volume":"1 1","pages":"1-6"},"PeriodicalIF":2.6,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85477425","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

Classification of Building Cracks Image Using the Convolutional Neural Network Method 基于卷积神经网络的建筑裂缝图像分类

IF 2.6

Data Pub Date : 2020-10-20 DOI: 10.1109/ICADEIS49811.2020.9276962

I. S. Wijaya, Aditya Perwira Joan Dwitama, I. B. K. Widiartha, Seno Adi Putra

{"title":"Classification of Building Cracks Image Using the Convolutional Neural Network Method","authors":"I. S. Wijaya, Aditya Perwira Joan Dwitama, I. B. K. Widiartha, Seno Adi Putra","doi":"10.1109/ICADEIS49811.2020.9276962","DOIUrl":"https://doi.org/10.1109/ICADEIS49811.2020.9276962","url":null,"abstract":"Building crack images classification caused by the earthquake is commonly conducted manually by analyzing walls, beams, columns, and floors based on visual inspection of crack's diameter, depth, and length. Experts in structural engineering who have many experiences in building damage assessment usually handle the mentioned task. In order to speed up and simplify the assessment process a classification system based on pattern recognition is on demand. This paper proposes a crack image classification technique using CNN. This classification technique is proposed to improve the performance of two previous works: the crack classification systems using GLCM features and the SVM classifier and the crack classification systems using Zoning and Moment features and QDA classifier. The experimental results show that the CNN based crack image classification works properly indicated by 99.63% of accuracy, 99.65% of precision, and 99.64% of recall for METU dataset and 93.80% of accuracy, 93.49% of precision, and 93.94% of recall for CDLE dataset. In detail, the CNN based crack image classification provides significantly higher performance than that of the previous works. Furthermore, the proposed system also shows robust performance against large variability of cracks and non-crack images.","PeriodicalId":36824,"journal":{"name":"Data","volume":"61 1","pages":"1-6"},"PeriodicalIF":2.6,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84670856","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