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17 May 2024: Tong Xia , Jing Han and Cecilia Mascolo. In Experimental Biology and Medicine.

22 Apr 2022: 3, pp. 332–339, 2005. [12] J. R. Stroop, “Studies of interference in serial verbal reactions,”Journal of Experimental Psychology, vol.

29 Jun 2010: EmotionSense: A Mobile Phones based Adaptive Platformfor Experimental Social Psychology Research. ... We design, implement, deploy, and evaluate a completesystem for experimental sociology and psychology that isable to provide information about social

17 May 2012: Tothis end, a number of experimental systems attempt to de-tect user context and activity through the fusion of sensingmodalities that are available on the users’ mobile devices:accelerometer, RF traces ... Aucinas,“Emotionsense: a mobile phones

12 Jun 2013: 6. K.K. Rachuri et al., “EmotionSense: A Mobile Phones Based Adaptive Platform for Experimental Social Psychology Research,” Proc. ... Per-sonality and Social Psychology, vol. 54, no. 2, 1988, pp. 296–308.

24 Jan 2013: Rentfrow‡†Computer Laboratory, ‡Department of Psychology, University of Cambridge, UK. Abstract—Mobile phones play a pivotal role in supportingubiquitous and unobtrusive sensing of human activities. ... Mascolo, P. J. Rentfrow, C. Long-worth, and

4 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

1 Jul 2013: Rachuri1, Cecilia Mascolo1, Peter J. Rentfrow21Computer Laboratory, 2Department of Social and Developmental Psychology. ... The Independence of Positive and NegativeAffect. Journal of Personality and Social Psychology 47 (1984).

1 Mar 2012: Recently, a number of experimental systems exploit the sensing capabilities of mo-bile phones in order to further enrich user experience. ... We seethe deployment of passive social sensing technologies as such a disruptive technology.In our experimental

7 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

1 Aug 2017: Table 3. Audio analysis tasks investigated. Experimental Setup. We train our Deep Belief Networks with a xed learning rate of 0.05 and train the DNNswith a learning rate of ... An audio sample in our case consists of 5 seconds of speech from a speaker,

29 Apr 2015: ZOE: A Cloud-less Dialog-enabled Continuous SensingWearable Exploiting Heterogeneous Computation. Nicholas D. Lane†, Petko Georgiev, Cecilia Mascolo, Ying Gao‡†Bell Labs, University of Cambridge, ‡Intel Research. ABSTRACTThe wearable