Leveraging Big Data and Analytics to Improve Food, Energy, and Water System Sustainability [0.03%]
利用大数据和分析改进食品、能源和水系统的可持续性
Joshua Pitts,Sucharita Gopal,Yaxiong Ma et al.
Joshua Pitts et al.
With the world population projected to grow significantly over the next few decades, and in the presence of additional stress caused by climate change and urbanization, securing the essential resources of food, energy, and water is one of t...
FoodKG: A Tool to Enrich Knowledge Graphs Using Machine Learning Techniques [0.03%]
FoodKG：使用机器学习技术丰富知识图谱的工具
Mohamed Gharibi,Arun Zachariah,Praveen Rao
Mohamed Gharibi
While there exist a plethora of datasets on the Internet related to Food, Energy, and Water (FEW), there is a real lack of reliable methods and tools that can consume these resources. This hinders the development of novel decision-making ap...
Quantitatively Measuring Privacy in Interactive Query Settings Within RDBMS Framework [0.03%]
在关系型数据库管理系统框架下的交互查询环境中定量测量隐私属性
Muhammad Imran Khan,Simon N Foley,Barry O&#x;Sullivan
Muhammad Imran Khan
Little attention has been paid to the measurement of risk to privacy in Database Management Systems, despite their prevalence as a modality of data access. This paper proposes PriDe, a quantitative privacy metric that provides a measure (pr...
Agricultural Drought Monitoring via the Assimilation of SMAP Soil Moisture Retrievals Into a Global Soil Water Balance Model [0.03%]
通过SMAP土壤湿度同化进行全球农业干旱监测
Iliana E Mladenova,John D Bolten,Wade Crow et al.
Iliana E Mladenova et al.
From an agricultural perspective, drought refers to an unusual deficiency of plant available water in the root-zone of the soil profile. This paper focuses on evaluating the benefit of assimilating soil moisture retrievals from the Soil Moi...
Unsupervised Word Embedding Learning by Incorporating Local and Global Contexts [0.03%]
结合局部和全局上下文的无监督词嵌入学习方法
Yu Meng,Jiaxin Huang,Guangyuan Wang et al.
Yu Meng et al.
Word embedding has benefited a broad spectrum of text analysis tasks by learning distributed word representations to encode word semantics. Word representations are typically learned by modeling local contexts of words, assuming that words ...
Commentary: A robust data-driven approach identifies four personality types across four large data sets [0.03%]
评论：一种稳健的数据驱动方法在四大数据集中识别出四种人格类型
Kentaro Katahira,Yoshihiko Kunisato,Yuichi Yamashita et al.
Kentaro Katahira et al.
Types of Privacy Expectations [0.03%]
隐私期待的类型
Ashwini Rao,Juergen Pfeffer
Ashwini Rao
Understanding user privacy expectations is important and challenging. General Data Protection Regulation (GDPR) for instance requires companies to assess user privacy expectations. Existing privacy literature has largely considered privacy ...
Robust Machine Learning for Colorectal Cancer Risk Prediction and Stratification [0.03%]
稳健的机器学习方法在结直肠癌风险预测和分类中的应用
Bradley J Nartowt,Gregory R Hart,Wazir Muhammad et al.
Bradley J Nartowt et al.
While colorectal cancer (CRC) is third in prevalence and mortality among cancers in the United States, there is no effective method to screen the general public for CRC risk. In this study, to identify an effective mass screening method for...
Algorithmic Profiling of Job Seekers in Austria: How Austerity Politics Are Made Effective [0.03%]
奥地利求职者的算法画像：紧缩政策如何得以施行
Doris Allhutter,Florian Cech,Fabian Fischer et al.
Doris Allhutter et al.
As of 2020, the Public Employment Service Austria (AMS) makes use of algorithmic profiling of job seekers to increase the efficiency of its counseling process and the effectiveness of active labor market programs. Based on a statistical mod...
AI in Healthcare: Time-Series Forecasting Using Statistical, Neural, and Ensemble Architectures [0.03%]
基于统计、神经和集成架构的医疗保健时间序列预测人工智能研究
Shruti Kaushik,Abhinav Choudhury,Pankaj Kumar Sheron et al.
Shruti Kaushik et al.
Both statistical and neural methods have been proposed in the literature to predict healthcare expenditures. However, less attention has been given to comparing predictions from both these methods as well as ensemble approaches in the healt...