2013 IEEE 9th International Conference on e-Science最新文献_第5页

Consensus Sigma-70 Promoter Prediction Using Hadoop 基于Hadoop的共识Sigma-70启动子预测

2013 IEEE 9th International Conference on e-Science Pub Date : 2013-10-22 DOI: 10.1109/eScience.2013.42

J. Hogan, W. Kelly, Felicity Newell

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引用次数: 2

Cabinet: Managing Data Efficiently in the Global Federated File System 内阁:在全球联邦文件系统中有效地管理数据

2013 IEEE 9th International Conference on e-Science Pub Date : 2013-10-22 DOI: 10.1109/eScience.2013.36

Avinash Kalyanaraman, A. Grimshaw

引用次数: 0

Bird-SDPS: A Migratory Birds' Spatial Distribution Prediction System 候鸟空间分布预测系统- sdps

2013 IEEE 9th International Conference on e-Science Pub Date : 2013-10-22 DOI: 10.1109/eScience.2013.12

Yuanchun Zhou, Jing Shao, Xuezhi Wang, Ze Luo, Jianhui Li, Baoping Yan

引用次数: 0

Wildlife@Home: Combining Crowd Sourcing and Volunteer Computing to Analyze Avian Nesting Video Wildlife@Home:结合众包和志愿者计算来分析鸟类筑巢视频

2013 IEEE 9th International Conference on e-Science Pub Date : 2013-10-01 DOI: 10.1109/ESCIENCE.2013.50

Travis Desell, Robert Bergman, K. Goehner, R. Marsh, Rebecca VanderClute, Susan N. Ellis‐Felege

{"title":"Wildlife@Home: Combining Crowd Sourcing and Volunteer Computing to Analyze Avian Nesting Video","authors":"Travis Desell, Robert Bergman, K. Goehner, R. Marsh, Rebecca VanderClute, Susan N. Ellis‐Felege","doi":"10.1109/ESCIENCE.2013.50","DOIUrl":"https://doi.org/10.1109/ESCIENCE.2013.50","url":null,"abstract":"New camera technology is allowing avian ecologists to perform detailed studies of avian behavior, nesting strategies and predation in areas where it was previously impossible to gather data. Unfortunately, studies have shown mechanical triggers and a variety of sensors to be inadequate in capturing footage of small predators (e.g., snakes, rodents) or events in dense vegetation. Because of this, continuous camera recording is currently the most robust solution for avian monitoring, especially in ground nesting species. However, continuous video footage results in a data deluge, as monitoring enough nests to make biologically significant inferences results in massive amounts of data which is unclassifiable by humans alone. In the summer of 2012, Dr. Ellis-Felege gathered video footage from 63 sharp-tailed grouse (Tympanuchus phasianellus) nests, as well as preliminary interior least tern (Sternula antillarum) and piping plover (Charadrius melodus) nests, resulting in over 20,000 hours of video footage. In order to effectively analyze this video, a project combining both crowd sourcing and volunteer computing was developed, where volunteers can stream nesting video and report their observations, as well as have their computers download video for analysis by computer vision techniques. This provides a robust way to analyze the video, as user observations are validated by multiple views as well as the results of the computer vision techniques. This work provides initial results analyzing the effectiveness of the crowd sourced observations and computer vision techniques.","PeriodicalId":325272,"journal":{"name":"2013 IEEE 9th International Conference on e-Science","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131368829","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: 10

Rapid Scanning of Spectrograms for Efficient Identification of Bioacoustic Events in Big Data 快速扫描谱图用于大数据中生物声学事件的有效识别

2013 IEEE 9th International Conference on e-Science Pub Date : 2013-10-01 DOI: 10.1109/eScience.2013.25

A. Truskinger, Mark Cottman-Fields, Daniel M. Johnson, P. Roe

引用次数: 24