Towards the edge intelligence: Robot assistant for the detection and classification of human emotions

[EN] Deep learning is being introduced more and more in our society. Nowadays, there are very few applications that do not use deep learning as a classification tool. One of the main application areas is focused on improving people¿s life quality, allowing to create personal assistants with canned benefits. More recently, with the proliferation of mobile computing and the emergence of the Internet of Things (IoT), billions of mobile and IoT devices are connected to the Internet. This allows the generation of millions of bytes of information about sensors, images, sounds, etc. Driven by this trend, there is an urgent need to push the IoT frontiers to the edge of the network, in order to decrease this massive sending of information to large exchanges for analysis. As a result of this trend, a new discipline has emerged: edge intelligence or edge AI, a widely recognised and promising solution that attracts with special interest to the community of researchers in artificial intelligence. We adapted edge AI to classify human emotions. Results show how edge AI-based emotion classification can greatly benefit in the field of cognitive assistants for the elderly or people living alone.This work was partly supported by the Generalitat Valenciana (PROMETEO/2018/002) and by the Spanish Government (RTI2018-095390-B-C31). Universitat Politecnica de Valencia Research Grant PAID-10-19.Rincón Arango, JA.; Julian Inglada, VJ.; Carrascosa Casamayor, C. (2020). Towards the edge intelligence: Robot assistant for the detection and classification of human emotions. Springer. 31-41. https://doi.org/10.1007/978-3-030-51999-5_3S3141Chang, A.: The role of artificial intelligence in digital health. In: Wulfovich, S., Meyers, A. (eds.) Digital Health Entrepreneurship. HI, pp. 71–81. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-12719-0_7Yang, L., Henthorne, T.L., George, B.: Artificial intelligence and robotics technology in the hospitality industry: current applications and future trends. In: George, B., Paul, J. (eds.) Digital Transformation in Business and Society, pp. 211–228. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-08277-2_13Khayyam, H., Javadi, B., Jalili, M., Jazar, R.N.: Artificial intelligence and Internet of Things for autonomous vehicles. In: Jazar, R.N., Dai, L. (eds.) Nonlinear Approaches in Engineering Applications, pp. 39–68. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-18963-1_2Liang, F., Yu, W., Liu, X., Griffith, D., Golmie, N.: Towards edge-based deep learning in industrial Internet of Things. IEEE Internet of Things J. 7, 4329–4341 (2020)Nagaraju, P.B., Oliner, A.J., Gilmore, B.M., Dean, E.A., Wang, J.: Data analytics in edge devices. US Patent App. 16/573,745, 9 January 2020Eskandari, M., Janjua, Z.H., Vecchio, M., Antonelli, F.: Passban IDS: an intelligent anomaly based intrusion detection system for IoT edge devices. IEEE Internet of Things J. (2020)Harish, A., Jhawar, S., Anisha, B.S., Ramakanth Kumar, P.: Implementing machine learning on edge devices with limited working memory. In: Ranganathan, G., Chen, J., Rocha, Á. (eds.) Inventive Communication and Computational Technologies. LNNS, vol. 89, pp. 1255–1261. Springer, Singapore (2020). https://doi.org/10.1007/978-981-15-0146-3_123Rincon, J.A., Martin, A., Costa, Â., Novais, P., Julián, V., Carrascosa, C.: EmIR: an emotional intelligent robot assistant. In: AfCAI (2018)Ke, R., Zhuang, Y., Pu, Z., Wang, Y.: A smart, efficient, and reliable parking surveillance system with edge artificial intelligence on IoT devices. arXiv preprint arXiv:2001.00269 (2020)Mazzia, V., Khaliq, A., Salvetti, F., Chiaberge, M.: Real-time apple detection system using embedded systems with hardware accelerators: an edge AI application. IEEE Access 8, 9102–9114 (2020)Chollet, F., et al.: Keras (2015). https://github.com/fchollet/kerasHoward, A.G., et al.: MobileNets: efficient convolutional neural networks for mobile vision applications. arXiv preprint arXiv:1704.04861 (2017

A global method for coupling transport with chemistry in heterogeneous porous media

Modeling reactive transport in porous media, using a local chemical equilibrium assumption, leads to a system of advection-diffusion PDE's coupled with algebraic equations. When solving this coupled system, the algebraic equations have to be solved at each grid point for each chemical species and at each time step. This leads to a coupled non-linear system. In this paper a global solution approach that enables to keep the software codes for transport and chemistry distinct is proposed. The method applies the Newton-Krylov framework to the formulation for reactive transport used in operator splitting. The method is formulated in terms of total mobile and total fixed concentrations and uses the chemical solver as a black box, as it only requires that on be able to solve chemical equilibrium problems (and compute derivatives), without having to know the solution method. An additional advantage of the Newton-Krylov method is that the Jacobian is only needed as an operator in a Jacobian matrix times vector product. The proposed method is tested on the MoMaS reactive transport benchmark.Comment: Computational Geosciences (2009) http://www.springerlink.com/content/933p55085742m203/?p=db14bb8c399b49979ba8389a3cae1b0f&pi=1

The spatial structure of lithic landscapes : the late holocene record of east-central Argentina as a case study

Fil: Barrientos, Gustavo. División Antropología. Facultad de Ciencias Naturales y Museo. Universidad Nacional de La Plata; ArgentinaFil: Catella, Luciana. División Arqueología. Facultad de Ciencias Naturales y Museo. Universidad Nacional de La Plata; ArgentinaFil: Oliva, Fernando. Centro Estudios Arqueológicos Regionales. Facultad de Humanidades y Artes. Universidad Nacional de Rosario; Argentin

Variable step boundary value methods based on reverse Adams schemes and their grid redistribution

The variable-step boundary value methods based on reverse k-step Adams schemes are defined for the solution of initial value problems. The paper discusses attainable convergence orders, conditioning of resulting discretization matrices and introduces a grid redistribution strategy based on equidistribution of the local truncation error. An adaptive algorithm is tested on several linear and nonlinear examples and the results strongly support the theory. The method is suitable for a parallel solution of stiff initial value problems

Use of the MicroRespTM method to assess Pollution-Induced Community Tolerance to metals and ecophysiological traits for soil microbial communities.

International audienc

La respiration du sol et le comportement des vers de terre comme indicateurs d’impacts écotoxiques, Travaux Pratiques de Master (UAPV).

National audienc

Shell colouration and antioxidant defence capacity in Theba pisana (OF Muller, 1774).

International audienc

Temperature and density dependent cooling function for H2 with updated H2/H collisional rates

The energy transfer among the components in a gas determines its fate. Especially at low temperatures, inelastic collisions drive the cooling and the heating mechanisms. In the early Universe as well as in zero- or low-metallicity environments the major contribution comes from the collisions among atomic and molecular hydrogen, also in its deuterated version. This work shows some updated calculations of the H2 cooling function based on novel collisional data which explicitly take into account the reactive pathway at low temperatures. Deviations from previous calculations are discussed and a multivariate data analysis is performed to provide a fit depending on both the gas temperature and the density of the gas