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Interactive Machine Learning for Laboratory Data Integration

Nathanael Fillmore, Nhan Do, Mary Brophy, Andrew Zimolzak
2019 Studies in Health Technology and Informatics  
In this work, we develop an interactive machine learning tool to "extend the reach" of expert laboratory test adjudicators.  ...  For example, the US Department of Veterans Affairs maintains a data warehouse covering over 20 million individuals and 6.6 billion lab tests.  ...  Fillmore et al. / Interactive Machine Learning for Laboratory Data Integration  ... 
doi:10.3233/shti190198 pmid:31437900 fatcat:q4pdhajuavf35a5etvyfl2pwm4

exp.at 19 2019 Conference Topics

2019 2019 5th Experiment International Conference (exp.at'19)  
Data Acquisition methods • Data Augmentation • Model deployment • Data labelling • Label assessment • Models for unbalanced data • Hardware acceleration for machine learning • Performance assessment  ...  , Skills and Competencies in Engineering Laboratories • Command of technology as learning objective for preparing students for future challenges • Integrating Novel Modes and pedagogical Topics into  ... 
doi:10.1109/expat.2019.8876502 fatcat:j3ojvkq77bdohc3wgu4daur3ya

Developing Tele-Operated Laboratories for Manufacturing Engineering Education. Platform for E-Learning and Telemetric Experimentation (PeTEX)

Claudius Terkowsky, Isa Jahnke, Christian Pleul né: Burkhardt, Roberto Licari, Per Johannssen, Gianluca Buffa, Matthias Heiner, Livan Fratini, Ernesto LoValvo, Mihai Nicolescu, Johannes Wildt, A. Erman Tekkaya
2010 International Journal of Online Engineering (iJOE)  
User interfaces are deployed for remote access to instruments, data analysis and multiplexed data access via network protocols.  ...  online learning community.  ...  LernBar can be used without fees for academic purposes. LernBar is a system for producing and publishing interactive learning content.  ... 
doi:10.3991/ijoe.v6s1.1378 fatcat:c7qjuwms2rfcrcpaphpdcjfxzq

A methodology to virtualize technical engineering laboratories: MastrLAB-VR

Ivana Scidà, Department of Structural, Geotechnical and Building Engineering, Polytechnic of Turin, Turin, TO 10129 ITALY, Francesco Alotto, Anna Osello, Department of Structural, Geotechnical and Building Engineering, Polytechnic of Turin, Turin, TO 10129 ITALY, Department of Structural, Geotechnical and Building Engineering, Polytechnic of Turin, Turin, TO 10129 ITALY
2021 Journal of Construction Materials  
The results have shown that MastrLAB-VR is suitable for both beginners and experts and will be adopted experimentally for other laboratories of the University departments.  ...  Starting from the objective of strengthening the innovative teaching offer and the learning processes, the case study of the research concerns the digitalization of MastrLAB, High Quality Laboratory (HQL  ...  to processes, list of materials • Machines Data: Data related to machines The link between this data and the 3D model is guaranteed by the use of unique TAG for every design.  ... 
doi:10.36756/jcm.v2.3.3 fatcat:vxdnvir3onhpdjvdlfee6qkrji

Technology and Foreign Languages

Walter Tuman
1987 IALLT Journal of Language Learning Technologies  
New ways to present voice, image, and data are discussed, together with their implications for the development of language curricula.  ...  , which for the most pari, remain embryonic.  ...  Applications in this about a decade. area revolve around learning theories and models of man-machine interaction. Artificial Intelligence.  ... 
doi:10.17161/iallt.v20i3-4.9273 fatcat:hlnnyqbiezahxlbnp7ewqh4xmm

The Manufacturing Data and Machine Learning Platform: Enabling Real-time Monitoring and Control of Scientific Experiments via IoT [article]

Jakob R. Elias, Ryan Chard, Joseph A. Libera, Ian Foster, Santanu Chaudhuri
2020 arXiv   pre-print
Indeed, synergizing diverse IoT data streams in near-real time can require the use of machine learning (ML).  ...  Here we will demonstrate how the use of the Argonne-developed Manufacturing Data and Machine Learning (MDML) platform can analyze and use IoT devices in a manufacturing experiment.  ...  Machine Learning (ML) has been shown to be an effective tool for analyzing big IoT data streams [3] .  ... 
arXiv:2005.13669v1 fatcat:z25snzwxbfejxdnclsyp3pa7ly

Computer-based learning in psychology using interactive laboratories

Stephen Richards
2011 Research in Learning Technology  
The interactive-laboratory approach, however, aims to limit the quantity of information presented, and instead to provide a highly interactive learning environment.  ...  Traditional approaches to computer-based learning often focus on the delivery of information.  ...  Acknowledgements I acknowledge the University of Newcastle for funding through the Teaching Initiatives Fund; Charles Hulme for permission to integrate the Short-Term Memory Experimenter which has been  ... 
doi:10.3402/rlt.v2i2.9579 fatcat:pedkapq26vb5tjbtutfqxvyzha

Computer-based learning in psychology using interactive laboratories

Stephen Richards
1994 Research in Learning Technology  
The interactive-laboratory approach, however, aims to limit the quantity of information presented, and instead to provide a highly interactive learning environment.  ...  Traditional approaches to computer-based learning often focus on the delivery of information.  ...  Acknowledgements I acknowledge the University of Newcastle for funding through the Teaching Initiatives Fund; Charles Hulme for permission to integrate the Short-Term Memory Experimenter which has been  ... 
doi:10.1080/0968776940020203 fatcat:py3xpfgefngmbcvti7hs3irnbm

A Survey of Current Resources to Study lncRNA-Protein Interactions

Melcy Philip, Tyrone Chen, Sonika Tyagi
2021 Non-Coding RNA  
Recently, machine learning has become the strategy of choice in LPI prediction, likely due to the rapid growth in machine learning infrastructure and expertise.  ...  While many of these methods have notable limitations, machine learning is expected to be the basis of modern LPI prediction algorithms.  ...  Acknowledgments: We thank Yashpal Ramakrishnaiah for his proofreading and feedback on this article. The authors thank the HPC team at Monash eResearch Centre for their continuous personnel support.  ... 
doi:10.3390/ncrna7020033 pmid:34201302 fatcat:psr5mlwzlzgyvdbpsdnzzj6lvq

Design on Personalized Teaching Platform Based on Virtual Desktop

Jiang-Hui LIU, Wei-Bo HUANG, Ling-Xi RUAN, Zhi-Feng CHEN
2018 DEStech Transactions on Social Science Education and Human Science  
Under the highly interactive platform, it provides continuously optimized personalized learning services for students.  ...  As long as the administrators don't log off the virtual machines, the virtual machines can be used by students for a long time.  ... 
doi:10.12783/dtssehs/icaem2017/19106 fatcat:lz7liflq55f2hb3juz3i4uchua

Tele-Operated Laboratories for Online Production Engineering Education - Platform for E-Learning and Telemetric Experimentation (PeTEX)

Claudius Terkowsky, Christian Pleul, Isa Jahnke, A. Erman Tekkaya
2011 International Journal of Online Engineering (iJOE)  
Hence, an educational model was designed which integrates the tele-operated experimentation platform with teaching content and learning activities in order to support a successful learning walkthrough  ...  The finalized EU-funded project PeTEX-Platform for e-Learning and Telemetric Experimentation has developed a prototype of an e-learning platform based on the learning and content management system Moodle  ...  of Instruction, integrating the interactive learning modules.  ... 
doi:10.3991/ijoe.v7is1.1725 fatcat:3kddkqidtzbsjcxcapelfovuuu

A boundary-crossing approach to support students' integration of statistical and work-related knowledge

Arthur Bakker, Sanne F. Akkerman
2013 Educational Studies in Mathematics  
To explore how such an integration process could be supported, we conducted an intervention in secondary vocational laboratory education.  ...  Vocational students and beginning professionals typically find it hard to integrate the mathematics and statistics that they have learned at school with work-related knowledge.  ...  Thanks also to Xaviera van Mierlo for assisting in the data collection and to Bert Nijdam and Michiel Veldhuis for their statistical advice.  ... 
doi:10.1007/s10649-013-9517-z fatcat:zyjxs673fbfivpqc5f2xfbdary

Impact of remote experimentation, interactivity and platform effectiveness on laboratory learning outcomes

Krishnashree Achuthan, Dhananjay Raghavan, Balakrishnan Shankar, Saneesh P. Francis, Vysakh Kani Kolil
2021 International Journal of Educational Technology in Higher Education  
Characterization of interactivity between remote learners and instructors disclose indicative parameters that affect transactional distances and aid in conceptual understanding in remote laboratory learning  ...  By comparing physical (PL-UTM) and remotely triggerable (RT-UTM) laboratory platforms, the structure and interactions as per TDT are analysed.  ...  Authors would like to thank the VALUE Virtual Labs team and CREATE team at Amrita Vishwa Vidyapeetham in developing and deploying virtual laboratories.  ... 
doi:10.1186/s41239-021-00272-z pmid:34778531 pmcid:PMC8263093 fatcat:2jjlkm67xvcnfdlsaex2em2ejq

A Primer on Data Analytics in Functional Genomics: How to Move from Data to Insight?

Piotr Grabowski, Juri Rappsilber
2019 TIBS -Trends in Biochemical Sciences. Regular ed  
Moreover, we highlight how machine learning is transforming the field and how it can help make sense of biological data.  ...  Unfortunately, performing such integrative analyses has traditionally been reserved for bioinformaticians.  ...  Acknowledgments We would like to thank Francis O'Reilly and Sven Giese for critically reading the manuscript and their helpful suggestions.  ... 
doi:10.1016/j.tibs.2018.10.010 pmid:30522862 pmcid:PMC6318833 fatcat:6sbywhr27zcvfjbr7cmyjxy7hq

Challenges in Predicting Disease State with Apache Spark

Saratkar Nilesh
2016 MOJ Proteomics & Bioinformatics  
Machine Learning is also known as domestication of machine where human to machine interaction is critical to complete feedback loop.  ...  Performance of every machine learning algorithm is different and requires data in specific format. Choosing right machine learning algorithm is one of the big challenge and critical for the success.  ... 
doi:10.15406/mojpb.2016.03.00076 fatcat:knncdxap5rhqbexg6ofeboaaui
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