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A Concerted Appeal for International Cooperation in Preclinical Stroke Research

U. Dirnagl, A. Hakim, M. Macleod, M. Fisher, D. Howells, S. M. Alan, G. Steinberg, A. Planas, J. Boltze, S. Savitz, C. Iadecola, S. Meairs
2013 Stroke  
Acknowledgments We gratefully acknowledge the input of Dr Gregory del Zoppo (University of Washington, Seattle) throughout this process. Disclosures None.  ...  both sides of the Atlantic SIRIUS: Sustained Investigation of Recovery and Immunologic response after stroke Using neural Stem cells The Department of Neurosurgery of the  ...  from Table 3 . 3 Examples of Already Existing Large-Scale/Transnational Cooperations in Preclinical Stroke and Stroke-Related ResearchEuropean Stroke Network A collaborative effort of the European  ... 
doi:10.1161/strokeaha.113.000734 pmid:23598526 pmcid:PMC3933930 fatcat:3hjgl5etuncr5lmf5sau7dfcqy

Radiomics: from qualitative to quantitative imaging

William Rogers, Sithin Thulasi Seetha, Turkey A. G. Refaee, Relinde I. Y. Lieverse, Renée W. Y. Granzier, Abdalla Ibrahim, Simon A. Keek, Sebastian Sanduleanu, Sergey P. Primakov, Manon P. L. Beuque, Damiënne Marcus, Alexander M. A. van der Wiel (+5 others)
2020 British Journal of Radiology  
to make predictions, such as survival, or for detection and classification used in diagnostics.  ...  Historically, medical imaging has been a qualitative or semi-quantitative modality. It is difficult to quantify what can be seen in an image, and to turn it into valuable predictive outcomes.  ...  types of data sets, making them more difficult for neural networks to master. 69, 71 According to Basu et al, 71 a redesign of neural network architectures is required to extract features in a similar  ... 
doi:10.1259/bjr.20190948 pmid:32101448 fatcat:mnhaur7dyrhanio63v6kdbdthm

Overcoming human trafficking via operations research and analytics: Opportunities for methods, models, and applications

Renata A. Konrad, Andrew C. Trapp, Timothy M. Palmbach, Jeffrey S. Blom
2017 European Journal of Operational Research  
Human trafficking is a transnational complex societal and economic issue.  ...  This paper highlights how operations research and analytics techniques can be used to address the growing issue of human trafficking.  ...  Many sex advertisers also use general Web sites such as Twitter and Instagram, while others use chat, social networking, dating, or community Web sites like Facebook, Tinder, or (Dubrawski  ... 
doi:10.1016/j.ejor.2016.10.049 fatcat:7a2nkc3luvhtnlttogtaxav7iu

Long-term satellite-based estimates of air quality and premature mortality in Equatorial Asia through Deep Neural Networks

Nicola Bruni Zani, Giovanni Lonati, Mohammed Iqbal Mead, Mohd Talib Latif, Paola Crippa
2020 Environmental Research Letters  
stations, are used to develop a machine learning approach for continuous PM 10 monitoring.  ...  Atmospheric pollution of particulate matter (PM) is a major concern for its deleterious effects on human health and climate.  ...  of  ... 
doi:10.1088/1748-9326/abb733 fatcat:mbe5tabjwfejxplgcz64q5nphi

On the Risk Assessment of Terrorist Attacks Coupled with Multi-Source Factors

Xun Zhang, Min Jin, Jingying Fu, Mengmeng Hao, Chongchong Yu, Xiaolan Xie
2018 ISPRS International Journal of Geo-Information  
The improved recommendation algorithm is used to build a spatial risk assessment model of terrorist attacks, and the effectiveness is tested.  ...  We used the data of terrorist attacks in Southeast Asia from 1970 to 2016, and comprehensively considered 17 influencing factors, including socioeconomic and natural resource factors.  ...  Acknowledgments: We would like to acknowledge Beijing Key Laboratory of Big Data Technology for Food Safety and Key Laboratory of Resources utilization and Environmental Remediation for providing a research  ... 
doi:10.3390/ijgi7090354 fatcat:b65pmzcwyrd2llfq6lsqqnuppy

Data-based Computational Approaches to Forecasting Political Violence [chapter]

Philip A. Schrodt, James Yonamine, Benjamin E. Bagozzi
2012 Handbook of Computational Approaches to Counterterrorism  
Acknowledgements This research was supported in part by a grant from the U.S.  ...  National Science Foundation, SES-1004414, and by a Fulbright-Hays Research Fellowship for work by Schrodt at the Peace Research Institute, Oslo (  ...  Although most work with neural networks seems far removed from terrorism, [12] articulately explain how supervised neural networks are not only an appropriate algorithmic approach to predicting violence  ... 
doi:10.1007/978-1-4614-5311-6_7 fatcat:46qo3xlopzhkjgs4sipqzukf5u

DeepSeedling: deep convolutional network and Kalman filter for plant seedling detection and counting in the field

Yu Jiang, Changying Li, Andrew H. Paterson, Jon S. Robertson
2019 Plant Methods  
The goal of this study was to develop a deep-learning-based approach to count plant seedlings in the field.  ...  Traditionally, plant population density is estimated by using either field assessment or a germination-test-based approach. These approaches can be laborious and inaccurate.  ...  Lin Qi for annotating images used in the present study.  ... 
doi:10.1186/s13007-019-0528-3 pmid:31768186 pmcid:PMC6874826 fatcat:epblordwqzcnvaz2vpv7pxh4pe

Construction of Amharic-arabic Parallel Text Corpus for Neural Machine Translation

Ibrahim Gashaw, Shashirekha
2020 International Journal of Artificial Intelligence & Applications  
Experiments are carried out on Two Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) based Neural Machine Translation (NMT) using Attention-based Encoder-Decoder architecture which is adapted  ...  Therefore, a small parallel Quranic text corpus is constructed by modifying the existing monolingual Arabic text and its equivalent translation of Amharic language text corpora available on Tanzile.  ...  Deep learning is part of a broader family of ML methods based on Artificial Neural Networks (ANN) [7] .  ... 
doi:10.5121/ijaia.2020.11107 fatcat:5udwbpcbvrah5imcxuzppwpts4

Short Term Electric Load Forecasting Based on Data Transformation and Statistical Machine Learning

Nikos Andriopoulos, Aristeidis Magklaras, Alexios Birbas, Alex Papalexopoulos, Christos Valouxis, Sophia Daskalaki, Michael Birbas, Efthymios Housos, George P. Papaioannou
2020 Applied Sciences  
The main feature of the proposed methodology is the exploitation of the statistical properties of each time series dataset, so as to optimize the hyper-parameters of the neural network and in addition  ...  Predicting the electric load is a challenging task due to its high volatility and uncertainty, either when it refers to the distribution system or to a single household.  ...  The forecast of a "regular" node was proportional to that of the parent node, while the "irregular" nodes were forecasted individually using neural networks.  ... 
doi:10.3390/app11010158 fatcat:gvfzsouejjbgvpxmghnvytlflq

From Symbols to Embeddings: A Tale of Two Representations in Computational Social Science [article]

Huimin Chen, Cheng Yang, Xuanming Zhang, Zhiyuan Liu, Maosong Sun, Jianbin Jin
2021 arXiv   pre-print
To explore the answer, we give a thorough review of data representations in CSS for both text and network.  ...  The study of CSS is data-driven and significantly benefits from the availability of online user-generated contents and social networks, which contain rich text and network data for investigation.  ...  In addition, the privacy issue is a hot topic where researchers use the symbol-based text features to prevent privacy disclosure across multiple online sites [141, 181] .  ... 
arXiv:2106.14198v1 fatcat:dvy5awnfuvbnnkzusjl5wbhfki

Circuits, the everyday and international relations: Connecting the home to the international and transnational

Roger Mac Ginty
2019 Cooperation and Conflict  
It proposes circuitry as an analytical device -not a mere metaphor -as a way of connecting the everyday and the hyper-local to the national, international, transnational and all levels in between.  ...  The home can be regarded as a key part of everyday and ontological security for many people, but how do we connect this to the international and transnational.  ...  Acknowledgements The author is grateful to Pamina Firchow for comments and to the Carnegie Corporation of New York for its support for the Everyday Peace Indicators project.  ... 
doi:10.1177/0010836719832343 fatcat:y5zw3u6zlfeghdebrmwidr277i

Making Radiomics More Reproducible across Scanner and Imaging Protocol Variations: A Review of Harmonization Methods

Shruti Atul Mali, Abdalla Ibrahim, Henry C. Woodruff, Vincent Andrearczyk, Henning Müller, Sergey Primakov, Zohaib Salahuddin, Avishek Chatterjee, Philippe Lambin
2021 Journal of Personalized Medicine  
We also reflect upon the importance of deep learning solutions for addressing variability across multi-centric radiomic studies especially using generative adversarial networks (GANs), neural style transfer  ...  Radiomics converts medical images into mineable data via a high-throughput extraction of quantitative features used for clinical decision support.  ...  DL is also a data-driven method that is inspired by the biological neural networks in the human brain.  ... 
doi:10.3390/jpm11090842 pmid:34575619 fatcat:2ngorzmaw5alrpj7deecvvf4au

Defense Advanced Research Projects Agency (Darpa) Fiscal Year 2015 Budget Estimates

Department Of Defense Comptroller's Office
2014 Zenodo  
DARPA seeks to improve the analysis of large neural data sets by creating interfaces that will allow researchers to generate new models across multiple scales.  ...  Additionally, DARPA's investment would include the Prosthetic Hand Proprioception and Touch Interfaces (using Haptix sensors) to develop human implantable microsystems to give amputees the ability to have  ...  FY 2014 Plans: -Demonstrate the ability of non-human primates to perform a dexterous sensorimotor task through the use of a neural interface, without the use of neural spike recordings.  ... 
doi:10.5281/zenodo.1215345 fatcat:fjzhmynqjbaafk67q2ckcblj2m

Experiencing the Detection of Radicalized Criminals on Facebook Social Network and Data-related Issues

Andrea Tundis, Leon Böck, Victoria Stanilescu, Max Mühlhäuser
2020 Journal of Cyber Security and Mobility  
a model for the detection of terrorists on Facebook social network, and (ii) to highlight the current limits.  ...  Online social networks (OSNs) represent powerful digital tools to communicate and quickly disseminate information in a non-official way.  ...  Crime Detection Approaches on Social Networks A major approach to study social networks is called Social Network Analysis (SNA) [43] .  ... 
doi:10.13052/jcsm2245-1439.922 fatcat:5r45cpq2vnaq5bv47kygltj3si

Mutual Information Input Selector and Probabilistic Machine Learning Utilisation for Air Pollution Proxies

Martha A. Zaidan, Lubna Dada, Mansour A. Alghamdi, Hisham Al-Jeelani, Heikki Lihavainen, Antti Hyvärinen, Tareq Hussein
2019 Applied Sciences  
In particular, we use a Bayesian neural network that naturally prevents overfitting and provides confidence intervals around its output prediction.  ...  In this paper, we present a generic concept of pollutant proxy development based on an optimised data-driven approach.  ...  One of the most popular ML methods is neural networks [28] . The rise of deep learning and related methods have made neural network based approaches become even more popular [40, 41] .  ... 
doi:10.3390/app9204475 fatcat:glp252lqhjg53i4tqscj5pfvwe
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