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MoBILAB: an open source toolbox for analysis and visualization of mobile brain/body imaging data

Alejandro Ojeda, Nima Bigdely-Shamlo, Scott Makeig
2014 Frontiers in Human Neuroscience  
MoBILAB can serve as a pre-processing environment for adding behavioral and other event markers to EEG data for further processing, and/or as a development platform for expanded analysis of simultaneously  ...  in 3-D environments (Makeig et al., 2009) .  ...  Other approaches to MoBI data analysis might follow more data-driven approaches including those used in the field of BCI design (Makeig et al., 2012) , whereby informative body and/or eye movement-defined  ... 
doi:10.3389/fnhum.2014.00121 pmid:24634649 pmcid:PMC3942646 fatcat:qqhvjwsa5ra3jcf7kwroxjdnvm

IBRIDIA: A hybrid solution for processing big logistics data

Mohammed AlShaer, Yehia Taher, Rafiqul Haque, Mohand-Saïd Hacid, Mohamed Dbouk
2019 Future generations computer systems  
Correlating data from different sensors and social media and performing analysis in real-time provide opportunities to predict events and prevent unexpected delivery delay at run-time.  ...  Additionally, they use external data that contain critical information about events such as traffic, accidents, and natural disasters.  ...  In other words, realtime analysis of data to extract information of events which may lead to delivery delay.  ... 
doi:10.1016/j.future.2019.02.044 fatcat:otv3ood5djgbjhfm62j6y4a7hi

In-Memory Big Data Management and Processing: A Survey

Hao Zhang, Gang Chen, Beng Chin Ooi, Kian-Lee Tan, Meihui Zhang
2015 IEEE Transactions on Knowledge and Data Engineering  
We also give a comprehensive presentation of important technology in memory management, and some key factors that need to be considered in order to achieve efficient in-memory data management and processing  ...  Some issues such as fault-tolerance and consistency are also more challenging to handle in in-memory environment.  ...  We would like to thank the anonymous reviewers, and also Bingsheng He, Eric Lo and Bogdan Marius Tudor, for their insightful comments and suggestions.  ... 
doi:10.1109/tkde.2015.2427795 fatcat:u7r3rtvhxbainfeazfduxcdwrm

An Improved Stream Processing Access

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
Many real time streaming approaches are emerging to utilize or process large real-time data by replacing legacy centralized scenarios which are causing more memory utilization, delay and fault tolerance  ...  In this paper we are focusing on improving stream processing techniques, limitations and future research directions for real-time stream processing  ...  Cloud data lab adopts machine learning approach useful for data analysis which is the last and final stage.  ... 
doi:10.35940/ijitee.k1147.09811s19 fatcat:hxbafhbeabbxpigf3mystx4h6m

Sentiment Analysis System in Big Data Environment

Wint Nyein Chan, Thandar Thein
2018 Computer systems science and engineering  
Twitter stream data is used for system evaluation as the Twitter is widespread Social Media and a good source of information in the sense of snapshots of moods and feelings as well as up-to-date events  ...  In this paper, Sentiment Analysis system on Big Data Analytics platform is proposed to provide valuable information by analyzing large scale social data in an efficient and timely manner since they have  ...  In this system, cloudera Twittersource is used as a data source. Data is limited by key words. The source comes as an event-driven source.  ... 
doi:10.32604/csse.2018.33.187 fatcat:fr47e6btknfvdkus62kwdvqrci

Big data stream analysis: a systematic literature review

Taiwo Kolajo, Olawande Daramola, Ayodele Adebiyi
2019 Journal of Big Data  
Introduction Advances in information technology have facilitated large volume, high-velocity of data, and the ability to store data continuously leading to several computational challenges.  ...  In this paper, a systematic review of big data streams analysis which employed a rigorous and methodical approach to look at the trends of big data stream tools and technologies as well as methods and  ...  In-memory Upstream backup Low High Exactly once Linux Java Disaster discovery, text analysis, com- plex event process- ing, visualisation Microsoft StreamInsight SQL Server Streaming  ... 
doi:10.1186/s40537-019-0210-7 fatcat:6llv2yxdwrdl5chehm7lxm2yru

Mental chronometry: Beyond onset latencies in the lexical decision task

David A. Balota, Richard A. Abrams
1995 Journal of Experimental Psychology. Learning, Memory and Cognition  
In Experiments 3 and 4, participants made the same arbitrary speech response in a modified lexical decision task for both high-and low-frequency words.  ...  In Experiment 1, participants made an arm movement in one direction for word trials and pressed a button with the other hand for nonword trials.  ...  into earlier processes in the information stream.  ... 
doi:10.1037//0278-7393.21.5.1289 pmid:8744966 fatcat:ceaf32fwxbarxh2nxql5gzohfu

Data Mining and Fusion Techniques for WSNs as a Source of the Big Data

Mohamed Mostafa Fouad, Nour E. Oweis, Tarek Gaber, Maamoun Ahmed, Vaclav Snasel
2015 Procedia Computer Science  
This has emerged the need to the use of in-network data processing techniques which are very crucial for the success of the big data framework.  ...  The wide adoption of the Wireless Senor Networks (WSNs) applications around the world has increased the amount of the sensor data which contribute to the complexity of Big Data.  ...  of large number of records. • Velocity: This denotes to the rate of data stream in unprecedented speed (or complex event processing) till the response to that data. • Variety: This is a characteristic  ... 
doi:10.1016/j.procs.2015.09.023 fatcat:xy7rsrzarfdvlolfxzjmg56q3u

Mental chronometry: Beyond onset latencies in the lexical decision task

David A. Balota, Richard A. Abrams
1995 Journal of Experimental Psychology. Learning, Memory and Cognition  
In Experiments 3 and 4, participants made the same arbitrary speech response in a modified lexical decision task for both high-and low-frequency words.  ...  In Experiment 1, participants made an arm movement in one direction for word trials and pressed a button with the other hand for nonword trials.  ...  into earlier processes in the information stream.  ... 
doi:10.1037/0278-7393.21.5.1289 fatcat:vwguxcolqrhjdirf6ybvfem6ve

Forecasting Significant Societal Events Using The Embers Streaming Predictive Analytics System

Andy Doyle, Graham Katz, Kristen Summers, Chris Ackermann, Ilya Zavorin, Zunsik Lim, Sathappan Muthiah, Patrick Butler, Nathan Self, Liang Zhao, Chang-Tien Lu, Rupinder Paul Khandpur (+2 others)
2014 Big Data  
It is deployed on Amazon Web Services using an entirely automated deployment process.  ...  We also present a detailed prospective evaluation of EMBERS in forecasting significant societal events in the past 2 years.  ...  Government is authorized to reproduce and distribute reprints of this work for governmental purposes notwithstanding any copyright annotation thereon.  ... 
doi:10.1089/big.2014.0046 pmid:25553271 pmcid:PMC4276118 fatcat:ig5o6g6m75ahpokgf2psu5wctq

Intelligent Urban Data Monitoring for Smart Cities [chapter]

Nikolaos Panagiotou, Nikolas Zygouras, Ioannis Katakis, Dimitrios Gunopulos, Nikos Zacheilas, Ioannis Boutsis, Vana Kalogeraki, Stephen Lynch, Brendan O'Brien
2016 Lecture Notes in Computer Science  
Urban data management is already an essential element of modern cities.  ...  To do this, we collaborated with the city of Dublin and worked on real problems and data. Our solutions were integrated in a system that was evaluated and is currently utilized by the city.  ...  velocity data streams, and information uncertainty.  ... 
doi:10.1007/978-3-319-46131-1_23 fatcat:jykq6jskmnbzppp3eita7wvvzi

Open challenges for data stream mining research

Georg Krempl, Myra Spiliopoulou, Jerzy Stefanowski, Indre Žliobaite, Dariusz Brzeziński, Eyke Hüllermeier, Mark Last, Vincent Lemaire, Tino Noack, Ammar Shaker, Sonja Sievi
2014 SIGKDD Explorations  
., predicting patients at high risk of being admitted to intensive care unit in the healthcare sector or predicting malicious SMSs in the telecommunication sector.  ...  The resulting analysis is illustrated by practical applications and provides general suggestions concerning lines of future research in data stream mining.  ...  on the challenges in stream mining.  ... 
doi:10.1145/2674026.2674028 fatcat:y3bozzeohveibgxb5wmiwfcogm

Research Challenges and Technology Progress of Data Mining with Bigdata

Pushpa Mannava
2019 International Journal of Scientific Research in Computer Science Engineering and Information Technology  
We have to highlight that Big Data does not simply imply huge volumes of data but likewise the requirement for scalability, i.e., to make sure a response in an acceptable elapsed time.  ...  ciently resolved making use of the common computing resources that we currently have.  ...  In order to manage the constant stream of data, an algorithm that can manage high-throughput data will be required. Extremely Fast Decision Tree (VFDT) was used for this purpose.  ... 
doi:10.32628/cseit206274 fatcat:czeyl23uq5dl3m4ddcpnu3nnlu

Modeling and Mitigating Human Annotation Errors to Design Efficient Stream Processing Systems with Human-in-the-loop Machine Learning [article]

Rahul Pandey, Hemant Purohit, Carlos Castillo, Valerie L. Shalin
2020 arXiv   pre-print
High-quality human annotations are necessary for creating effective machine learning-driven stream processing systems.  ...  Considering human annotation as a psychological process allows us to address these limitations.  ...  National Science Foundation grant awards IIS-1657379 and 1815459 for partial support to this research.  ... 
arXiv:2007.03177v1 fatcat:vubs7kjrd5gdlhz63upetrs56y

Online Incremental Machine Learning Platform for Big Data-Driven Smart Traffic Management

Dinithi Nallaperuma, Rashmika Nawaratne, Tharindu Bandaragoda, Achini Adikari, Su Nguyen, Thimal Kempitiya, Daswin De Silva, Damminda Alahakoon, Dakshan Pothuhera
2019 IEEE transactions on intelligent transportation systems (Print)  
The existing AI techniques that function in isolation exhibit clear limitations in developing a comprehensive platform due to the dynamicity of big data streams, highfrequency unlabeled data generation  ...  It is timely and pertinent that ITS harness the potential of an artificial intelligence (AI) to develop the big data-driven smart traffic management solutions for effective decision-making.  ...  As such, online learning is utilized to handle large volumes of streaming data arriving at high velocity.  ... 
doi:10.1109/tits.2019.2924883 fatcat:enaochz3vverdhfeg2poazc6ai
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