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https://mobile-systems.cl.cam.ac.uk/publications.html17 May 2024: A Place-focused Model for Social Networks in Cities. Chloë Brown, Anastasios Noulas, Cecilia Mascolo, Vincent Blondel. ... In Proceeding of ACM International Workshop on Mobile Systems for Computational Social Science (MCSS 2013). -
EmotionSense: A Mobile Phones based Adaptive Platform for…
https://mobile-systems.cl.cam.ac.uk/papers/Ubicomp10.pdf29 Jun 2010: In this paper we illustrate EmotionSense, a mobile sens-ing platform for social psychology studies based on mobilephones. ... We design, implement, deploy, and evaluate a completesystem for experimental sociology and psychology that isable to provide -
2 PERVASIVE computing Published by the IEEE CS n ...
https://mobile-systems.cl.cam.ac.uk/papers/ieeepervasive2013.pdf12 Jun 2013: sociablesenseWe designed SociableSense,12 a smart-phone-based platform for providing real-time feedback to users to foster and improve social interactions. ... 6. K.K. Rachuri et al., “EmotionSense: A Mobile Phones Based Adaptive Platform for -
METIS: Exploring mobile phone sensing offloading for efficiently…
https://mobile-systems.cl.cam.ac.uk/papers/percom2013.pdf24 Jan 2013: In this paper, we present the design,implementation, and evaluation of METIS: an adaptive mobilesensing platform that efficiently supports social sensing applica-tions. ... Mascolo, P. J. Rentfrow, C. Long-worth, and A. Aucinas. EmotionSense: A Mobile -
Exploring Automatic Diagnosis of COVID-19 from Crowdsourced…
https://mobile-systems.cl.cam.ac.uk/papers/KDD_covid_19.pdf4 Aug 2020: 5.1 Experimental setupClassification tasks. Based on the data collection (Section 3) wefocus on three clinically meaningful binary classification tasks:. • ... 2010. EmotionSense: A mobile phones based adap-tive platform for experimental social -
Sense and Sensibility in a Pervasive World Christos Efstratiou1, ...
https://mobile-systems.cl.cam.ac.uk/papers/pervasive12.pdf1 Mar 2012: We seethe deployment of passive social sensing technologies as such a disruptive technology.In our experimental study our primary aim was to explore the main tensions betweencompeting needs that can affect ... P14: “I liked the ranking games. Itwas an -
YONO: Modeling Multiple Heterogeneous Neural Networks on…
https://mobile-systems.cl.cam.ac.uk/papers/ipsn22.pdf7 Mar 2022: 4.1describes our experimental setup. We evaluate the effectivenessof our system in the offline phase regarding the performance (i.e.,accuracy) and compression rate of the compressed models in anMTL scenario. ... 4.1 Experimental Setup4.1.1 Task. Our -
UbiComp17_camera
https://mobile-systems.cl.cam.ac.uk/papers/Ubicomp17-Georgiev.pdf1 Aug 2017: 2.5 Optimizing the Multi-task ConfigurationPrior to placing a multi-task conguration on the embedded platform, we perform an oine optimization stepthat aims to decide the level of integration of ... An audio sample in our case consists of 5 seconds of -
ZOE: A Cloud-less Dialog-enabled Continuous SensingWearable…
https://mobile-systems.cl.cam.ac.uk/papers/mobisys2015.pdf29 Apr 2015: 3.2 Social SensingZOE leverages two microphone pipelines, namely speech detec-tion and speaker identification, as the basis for gathering a set ofconversation-related metadata and inferences. ... It has the dual role of both providing social infer-ences
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