Frontiers in Big Data最新文献_第8页

impresso Text Reuse at Scale. An interface for the exploration of text reuse data in semantically enriched historical newspapers 大规模的文本重用。在语义丰富的历史报纸中探索文本重用数据的接口

Frontiers in Big Data Pub Date : 2023-11-03 DOI: 10.3389/fdata.2023.1249469

Marten Düring, Matteo Romanello, Maud Ehrmann, Kaspar Beelen, Daniele Guido, Brecht Deseure, Estelle Bunout, Jana Keck, Petros Apostolopoulos

{"title":"impresso Text Reuse at Scale. An interface for the exploration of text reuse data in semantically enriched historical newspapers","authors":"Marten Düring, Matteo Romanello, Maud Ehrmann, Kaspar Beelen, Daniele Guido, Brecht Deseure, Estelle Bunout, Jana Keck, Petros Apostolopoulos","doi":"10.3389/fdata.2023.1249469","DOIUrl":"https://doi.org/10.3389/fdata.2023.1249469","url":null,"abstract":"Text Reuse reveals meaningful reiterations of text in large corpora. Humanities researchers use text reuse to study, e.g., the posterior reception of influential texts or to reveal evolving publication practices of historical media. This research is often supported by interactive visualizations which highlight relations and differences between text segments. In this paper, we build on earlier work in this domain. We present impresso Text Reuse at Scale, the to our knowledge first interface which integrates text reuse data with other forms of semantic enrichment to enable a versatile and scalable exploration of intertextual relations in historical newspaper corpora. The Text Reuse at Scale interface was developed as part of the impresso project and combines powerful search and filter operations with close and distant reading perspectives. We integrate text reuse data with enrichments derived from topic modeling, named entity recognition and classification, language and document type detection as well as a rich set of newspaper metadata. We report on historical research objectives and common user tasks for the analysis of historical text reuse data and present the prototype interface together with the results of a user evaluation.","PeriodicalId":52859,"journal":{"name":"Frontiers in Big Data","volume":"9 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135820990","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

Non-invasive detection of anemia using lip mucosa images transfer learning convolutional neural networks 利用唇黏膜图像转移学习卷积神经网络进行无创贫血检测

Frontiers in Big Data Pub Date : 2023-11-03 DOI: 10.3389/fdata.2023.1291329

Mohammed Mansour, Turker Berk Donmez, Mustafa Kutlu, Shekhar Mahmud

{"title":"Non-invasive detection of anemia using lip mucosa images transfer learning convolutional neural networks","authors":"Mohammed Mansour, Turker Berk Donmez, Mustafa Kutlu, Shekhar Mahmud","doi":"10.3389/fdata.2023.1291329","DOIUrl":"https://doi.org/10.3389/fdata.2023.1291329","url":null,"abstract":"Anemia is defined as a drop in the number of erythrocytes or hemoglobin concentration below normal levels in healthy people. The increase in paleness of the skin might vary based on the color of the skin, although there is currently no quantifiable measurement. The pallor of the skin is best visible in locations where the cuticle is thin, such as the interior of the mouth, lips, or conjunctiva. This work focuses on anemia-related pallors and their relationship to blood count values and artificial intelligence. In this study, a deep learning approach using transfer learning and Convolutional Neural Networks (CNN) was implemented in which VGG16, Xception, MobileNet, and ResNet50 architectures, were pre-trained to predict anemia using lip mucous images. A total of 138 volunteers (100 women and 38 men) participated in the work to develop the dataset that contains two image classes: healthy and anemic. Image processing was first performed on a single frame with only the mouth area visible, data argumentation was preformed, and then CNN models were applied to classify the dataset lip images. Statistical metrics were employed to discriminate the performance of the models in terms of Accuracy, Precision, Recal, and F1 Score. Among the CNN algorithms used, Xception was found to categorize the lip images with 99.28% accuracy, providing the best results. The other CNN architectures had accuracies of 96.38% for MobileNet, 95.65% for ResNet %, and 92.39% for VGG16. Our findings show that anemia may be diagnosed using deep learning approaches from a single lip image. This data set will be enhanced in the future to allow for real-time classification.","PeriodicalId":52859,"journal":{"name":"Frontiers in Big Data","volume":"28 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135819639","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

No longer hype, not yet mainstream? Recalibrating city digital twins' expectations and reality: a case study perspective 不再炒作，还不是主流?重新校准城市数字孪生的期望和现实:一个案例研究的视角

Frontiers in Big Data Pub Date : 2023-11-02 DOI: 10.3389/fdata.2023.1236397

Stefano Calzati

{"title":"No longer hype, not yet mainstream? Recalibrating city digital twins' expectations and reality: a case study perspective","authors":"Stefano Calzati","doi":"10.3389/fdata.2023.1236397","DOIUrl":"https://doi.org/10.3389/fdata.2023.1236397","url":null,"abstract":"While the concept of digital twin has already consolidated in industry, its spinoff in the urban environment—in the form of a City Digital Twin (CDT)—is more recent. A CDT is a dynamic digital model of the physical city whereby the physical and the digital are integrated in both directions, thus mutually affecting each other in real time. Replicating the path of smart cities, literature remarks that agendas and discourses around CDTs remain (1) tech-centered, that is, focused on overcoming technical limitations and lacking a proper sociotechnical contextualization of digital twin technologies; (2) practice-first, entailing hands-on applications without a long-term strategic governance for the management of these same technologies. Building on that, the goal of this article is to move beyond high-level conceptualizations of CDT to (a) get a cognizant understanding of what a CDT can do, how, and for whom; (b) map the current state of development and implementation of CDTs in Europe. This will be done by looking at three case studies—Dublin, Helsinki, and Rotterdam—often considered as successful examples of CDTs in Europe. Through exiting literature and official documents, as well as by relying on primary interviews with tech experts and local officials, the article explores the maturity of these CDTs, along the Gartner's hype-mainstream curve of technological innovations. Findings show that, while all three municipalities have long-term plans to deliver an integrated, cyber-physical real-time modeling of the city, currently their CDTs are still at an early stage of development. The focus remains on technical barriers—e.g., integration of different data sources—overlooking the societal dimension, such as the systematic involvement of citizens. As for the governance, all cases embrace a multistakeholder approach; yet CDTs are still not used for policymaking and it remains to see how the power across stakeholders will be distributed in terms of access to, control of, and decisions about CDTs.","PeriodicalId":52859,"journal":{"name":"Frontiers in Big Data","volume":"10 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135936136","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 fast parallelized DBSCAN algorithm based on OpenMp for detection of criminals on streaming services 一种基于OpenMp的快速并行DBSCAN算法用于流媒体服务中的犯罪分子检测

Frontiers in Big Data Pub Date : 2023-10-31 DOI: 10.3389/fdata.2023.1292923

Lesia Mochurad, Andrii Sydor, Oleh Ratinskiy

{"title":"A fast parallelized DBSCAN algorithm based on OpenMp for detection of criminals on streaming services","authors":"Lesia Mochurad, Andrii Sydor, Oleh Ratinskiy","doi":"10.3389/fdata.2023.1292923","DOIUrl":"https://doi.org/10.3389/fdata.2023.1292923","url":null,"abstract":"Introduction Streaming services are highly popular today. Millions of people watch live streams or videos and listen to music. Methods One of the most popular streaming platforms is Twitch, and data from this type of service can be a good example for applying the parallel DBSCAN algorithm proposed in this paper. Unlike the classical approach to neighbor search, the proposed one avoids redundancy, i.e., the repetition of the same calculations. At the same time, this algorithm is based on the classical DBSCAN method with a full search for all neighbors, parallelization by subtasks, and OpenMP parallel computing technology. Results In this work, without reducing the accuracy, we managed to speed up the solution based on the DBSCAN algorithm when analyzing medium-sized data. As a result, the acceleration rate tends to the number of cores of a multicore computer system and the efficiency to one. Discussion Before conducting numerical experiments, theoretical estimates of speed-up and efficiency were obtained, and they aligned with the results obtained, confirming their validity. The quality of the performed clustering was verified using the silhouette value. All experiments were conducted using different percentages of medium-sized datasets. The prospects of applying the proposed algorithm can be obtained in various fields such as advertising, marketing, cybersecurity, and sociology. It is worth mentioning that datasets of this kind are often used for detecting fraud on the Internet, making an algorithm capable of considering all neighbors a useful tool for such research.","PeriodicalId":52859,"journal":{"name":"Frontiers in Big Data","volume":"2020 27","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135814023","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

An overview of video recommender systems: state-of-the-art and research issues. 视频推荐系统综述:最新技术和研究问题。

IF 3.1

Frontiers in Big Data Pub Date : 2023-10-30 eCollection Date: 2023-01-01 DOI: 10.3389/fdata.2023.1281614

Sebastian Lubos, Alexander Felfernig, Markus Tautschnig

{"title":"An overview of video recommender systems: state-of-the-art and research issues.","authors":"Sebastian Lubos, Alexander Felfernig, Markus Tautschnig","doi":"10.3389/fdata.2023.1281614","DOIUrl":"10.3389/fdata.2023.1281614","url":null,"abstract":"Video platforms have become indispensable components within a diverse range of applications, serving various purposes in entertainment, e-learning, corporate training, online documentation, and news provision. As the volume and complexity of video content continue to grow, the need for personalized access features becomes an inevitable requirement to ensure efficient content consumption. To address this need, recommender systems have emerged as helpful tools providing personalized video access. By leveraging past user-specific video consumption data and the preferences of similar users, these systems excel in recommending videos that are highly relevant to individual users. This article presents a comprehensive overview of the current state of video recommender systems (VRS), exploring the algorithms used, their applications, and related aspects. In addition to an in-depth analysis of existing approaches, this review also addresses unresolved research challenges within this domain. These unexplored areas offer exciting opportunities for advancements and innovations, aiming to enhance the accuracy and effectiveness of personalized video recommendations. Overall, this article serves as a valuable resource for researchers, practitioners, and stakeholders in the video domain. It offers insights into cutting-edge algorithms, successful applications, and areas that merit further exploration to advance the field of video recommendation.","PeriodicalId":52859,"journal":{"name":"Frontiers in Big Data","volume":"6 ","pages":"1281614"},"PeriodicalIF":3.1,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10642507/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"107592784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Recommender systems for sustainability: overview and research issues. 可持续发展的推荐系统:概述和研究问题。

IF 2.4

Frontiers in Big Data Pub Date : 2023-10-30 eCollection Date: 2023-01-01 DOI: 10.3389/fdata.2023.1284511

Alexander Felfernig, Manfred Wundara, Thi Ngoc Trang Tran, Seda Polat-Erdeniz, Sebastian Lubos, Merfat El Mansi, Damian Garber, Viet-Man Le

引用次数: 0

A stream processing abstraction framework. 一个流处理抽象框架。

IF 3.1

Frontiers in Big Data Pub Date : 2023-10-25 eCollection Date: 2023-01-01 DOI: 10.3389/fdata.2023.1227156

Ilaria Bartolini, Marco Patella

引用次数: 0

Erratum: Evaluation of methods for assigning causes of death from verbal autopsies in India. 勘误表：对印度语言尸检死因分配方法的评估。

IF 3.1

Frontiers in Big Data Pub Date : 2023-10-24 eCollection Date: 2023-01-01 DOI: 10.3389/fdata.2023.1319729

引用次数: 0

Experimental study and clustering of operating staff of search systems in the sense of stress resistance. 实验研究和聚类搜索系统操作人员的抗压意识。

IF 3.1

Frontiers in Big Data Pub Date : 2023-10-23 eCollection Date: 2023-01-01 DOI: 10.3389/fdata.2023.1239017

Nataliya Shakhovska, Roman Kaminskyi, Bohdan Khudoba

{"title":"Experimental study and clustering of operating staff of search systems in the sense of stress resistance.","authors":"Nataliya Shakhovska, Roman Kaminskyi, Bohdan Khudoba","doi":"10.3389/fdata.2023.1239017","DOIUrl":"10.3389/fdata.2023.1239017","url":null,"abstract":"Introduction: The main goal of this study is to develop a methodology for the organization of experimental selection of operator personnel based on the analysis of their behavior under the influence of micro-stresses.Methods: A human-machine interface model has been developed, which considers the change in the functional state of the human operator. The presented concept of the difficulty of detecting the object of attention contributed to developing a particular sequence of ordinary test images with stressor images included in it and presented models of the flow of presenting test images to the recipient.Results: With the help of descriptive statistics, the parameters of individual box-plot diagrams were determined, and the recipient group was clustered.Discussion: Overall, the proposed approach based on the example of the conducted grouping makes it possible to ensure the objectivity and efficiency of the professional selection of applicants for operator specialties.","PeriodicalId":52859,"journal":{"name":"Frontiers in Big Data","volume":"6 ","pages":"1239017"},"PeriodicalIF":3.1,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10626476/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71488837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Anemia detection through non-invasive analysis of lip mucosa images. 通过无创分析唇粘膜图像检测贫血。

IF 3.1

Frontiers in Big Data Pub Date : 2023-10-19 eCollection Date: 2023-01-01 DOI: 10.3389/fdata.2023.1241899

Turker Berk Donmez, Mohammed Mansour, Mustafa Kutlu, Chris Freeman, Shekhar Mahmud

{"title":"Anemia detection through non-invasive analysis of lip mucosa images.","authors":"Turker Berk Donmez, Mohammed Mansour, Mustafa Kutlu, Chris Freeman, Shekhar Mahmud","doi":"10.3389/fdata.2023.1241899","DOIUrl":"10.3389/fdata.2023.1241899","url":null,"abstract":"This paper aims to detect anemia using images of the lip mucosa, where the skin tissue is thin, and to confirm the feasibility of detecting anemia noninvasively and in the home environment using machine learning (ML). Data were collected from 138 patients, including 100 women and 38 men. Six ML algorithms: artificial neural network (ANN), decision tree (DT), k-nearest neighbors (KNN), logistic regression (LR), naive bayes (NB), and support vector machine (SVM) which are widely used in medical applications, were used to classify the collected data. Two different data types were obtained from participants' images (RGB red color values and HSV saturation values) as features, with age, sex, and hemoglobin levels utilized to perform classification. The ML algorithm was used to analyze and classify images of the lip mucosa quickly and accurately, potentially increasing the efficiency of anemia screening programs. The accuracy, precision, recall, and F-measure were evaluated to assess how well ML models performed in predicting anemia. The results showed that NB reported the highest accuracy (96%) among the other ML models used. DT, KNN and ANN reported an accuracies of (93%), while LR and SVM had an accuracy of (79%) and (75%) receptively. This research suggests that employing ML approaches to identify anemia will help classify the diagnosis, which will then help to create efficient preventive measures. Compared to blood tests, this noninvasive procedure is more practical and accessible to patients. Furthermore, ML algorithms may be created and trained to assess lip mucosa photos at a minimal cost, making it an affordable screening method in regions with a shortage of healthcare resources.","PeriodicalId":52859,"journal":{"name":"Frontiers in Big Data","volume":"6 ","pages":"1241899"},"PeriodicalIF":3.1,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10620602/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71488836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0