Experimenting With Algorithms and Memory-Making: Lived Experience and Future-Oriented Ethics in Critical Data Science [0.03%]
批判性数据科学中的生活体验和面向未来伦理：算法与记忆制作的实验
Annette N Markham,Gabriel Pereira
Annette N Markham
In this paper, we focus on one specific participatory installation developed for an exhibition in Aarhus (Denmark) by the Museum of Random Memory, a series of arts-based, public-facing workshops and interventions. The multichannel video ins...
Variable Rate Irrigation of Maize and Soybean in West-Central Nebraska Under Full and Deficit Irrigation [0.03%]
全程和亏缺灌溉下美国内布拉斯加州西部中央地区玉米和大豆的变量灌溉率试验研究
J Burdette Barker,Sandeep Bhatti,Derek M Heeren et al.
J Burdette Barker et al.
Variable rate irrigation (VRI) may improve center pivot irrigation management, including deficit irrigation. A remote-sensing-based evapotranspiration model was implemented with Landsat imagery to manage irrigations for a VRI equipped cente...
Accelerating Physics-Based Simulations Using End-to-End Neural Network Proxies: An Application in Oil Reservoir Modeling [0.03%]
基于端到端神经网络代理的物理仿真加速方法及其在油气藏建模中的应用
Jiří Navrátil,Alan King,Jesus Rios et al.
Jiří Navrátil et al.
We develop a proxy model based on deep learning methods to accelerate the simulations of oil reservoirs-by three orders of magnitude-compared to industry-strength physics-based PDE solvers. This paper describes a new architectural approach ...
AI for Not Bad [0.03%]
不错的AI
Jared Moore
Jared Moore
Hype surrounds the promotions, aspirations, and notions of "artificial intelligence (AI) for social good" and its related permutations. These terms, as used in data science and particularly in public discourse, are vague. Far from being irr...
Identifying Dynamic Memory Effects on Vegetation State Using Recurrent Neural Networks [0.03%]
利用循环神经网络识别动态内存效应对植被状态的影响
Basil Kraft,Martin Jung,Marco Körner et al.
Basil Kraft et al.
Vegetation state is largely driven by climate and the complexity of involved processes leads to non-linear interactions over multiple time-scales. Recently, the role of temporally lagged dependencies, so-called memory effects, has been emph...
Significant EHR Feature-Driven T2D Inference: Predictive Machine Learning and Networks [0.03%]
基于EHR特征驱动的2型糖尿病预测：机器学习与网络模型方法研究
Nicolo&#x; Preo,Enrico Capobianco
Nicolo&#x; Preo
Background: Electronic health records (EHR) play an important role for the redefinition of phenotypes in view of the wealth and heterogeneity of information now available from disparate data sources. A recent cross-sectional retrospective s...
Helena Mihaljević,Marco Tullney,Lucía Santamaría et al.
Helena Mihaljević et al.
The interplay between an academic's gender and their scholarly output is a riveting topic at the intersection of scientometrics, data science, gender studies, and sociology. Its effects can be studied to analyze the role of gender in resear...
Use of Machine Learning to Detect Wildlife Product Promotion and Sales on Twitter [0.03%]
利用机器学习检测Twitter上的野生动物产品促销和销售行为
Qing Xu,Jiawei Li,Mingxiang Cai et al.
Qing Xu et al.
Social media is an important channel for communication, information dissemination, and social interaction, but also provides opportunities to illicitly sell goods online, including the trade of wildlife products. In this study, we use the T...
Simultaneous Parameter Learning and Bi-clustering for Multi-Response Models [0.03%]
多响应模型的参数学习和双聚类同时进行
Ming Yu,Karthikeyan Natesan Ramamurthy,Addie Thompson et al.
Ming Yu et al.
We consider multi-response and multi-task regression models, where the parameter matrix to be estimated is expected to have an unknown grouping structure. The groupings can be along tasks, or features, or both, the last one indicating a bi-...
Kuansan Wang
Kuansan Wang
Bolstered by ever affordable computational power and open big datasets, artificial intelligence (AI) technologies are bringing revolutionary changes to our lives. This article examines the current trends and elaborates the future potentials...