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Angel D. Sappa, Juan A. Carvajal, Cristhian A. Aguilera, Miguel Oliveira, Dennis G. Romero, & Boris X. Vintimilla. (2016). Wavelet-Based Visible and Infrared Image Fusion: A Comparative Study. Sensors Journal, Vol. 16, pp. 1–15.
Abstract: This paper evaluates different wavelet-based cross-spectral image fusion strategies adopted to merge visible and infrared images. The objective is to find the best setup independently of the evaluation metric used to measure the performance. Quantitative performance results are obtained with state of the art approaches together with adaptations proposed in the current work. The options evaluated in the current work result from the combination of different setups in the wavelet image decomposition stage together with different fusion strategies for the final merging stage that generates the resulting representation. Most of the approaches evaluate results according to the application for which they are intended for. Sometimes a human observer is selected to judge the quality of the obtained results. In the current work, quantitative values are considered in order to find correlations between setups and performance of obtained results; these correlations can be used to define a criteria for selecting the best fusion strategy for a given pair of cross-spectral images. The whole procedure is evaluated with a large set of correctly registered visible and infrared image pairs, including both Near InfraRed (NIR) and LongWave InfraRed (LWIR).
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Ricaurte P, Chilán C, Cristhian A. Aguilera, Boris X. Vintimilla, & Angel D. Sappa. (2014). Feature Point Descriptors: Infrared and Visible Spectra. Sensors Journal, Vol. 14, pp. 3690–3701.
Abstract: This manuscript evaluates the behavior of classical feature point descriptors when they are used in images from long-wave infrared spectral band and compare them with the results obtained in the visible spectrum. Robustness to changes in rotation, scaling, blur, and additive noise are analyzed using a state of the art framework. Experimental results using a cross-spectral outdoor image data set are presented and conclusions from these experiments are given.
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A. Amato, F. Lumbreras, & Angel D. Sappa. (2014). A general-purpose crowdsourcing platform for mobile devices. In Computer Vision Theory and Applications (VISAPP), 2014 International Conference on, Lisbon, Portugal, 2014 (Vol. 3, pp. 211–215). Lisbon, Portugal: IEEE.
Abstract: This paper presents details of a general purpose micro-taskon-demand platform based on the crowdsourcing philosophy. This platformwas specifically developed for mobile devices in order to exploit the strengths of such devices; namely: i) massivity, ii) ubiquityand iii) embedded sensors.The combined use of mobile platforms and the crowdsourcing model allows to tackle from the simplest to the most complex tasks.Users experience is the highlighted feature of this platform (this fact is extended to both task-proposer and task- solver).Proper tools according with a specific task are provided to a task-solver in order to perform his/her job in a simpler, faster and appealing way.Moreover, a task can be easily submitted by just selecting predefined templates, which cover a wide range of possible applications.Examples of its usage in computer vision and computer games are provided illustrating the potentiality of the platform.
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Dennis G. Romero, A. F. Neto, T. F. Bastos, & Boris X. Vintimilla. (2012). An approach to automatic assistance in physiotherapy based on on-line movement identification. In VI Andean Region International Conference – ANDESCON 2012. Andean Region International Conference (ANDESCON), 2012 VI: IEEE.
Abstract: This paper describes a method for on-line movement identification, oriented to patient’s movement evaluation during physiotherapy. An analysis based on Mahalanobis distance between temporal windows is performed to identify the “idle/motion” state, which defines the beginning and end of the patient’s movement, for posterior patterns extraction based on Relative Wavelet Energy from sequences of invariant moments.
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Monica Villavicencio, & Alain Abran. (2011). Educational Issues in the Teaching of Software Measurement in Software Engineering Undergraduate Programs. In Joint Conference of the International Workshop on Software Measurement and the International Conference on Software Process and Product Measurement (pp. 239–244). IEEE.
Abstract: In mature engineering disciplines and science, mathematics and measurement are considered as important subjects to be taught in university programs. This paper discusses about these subjects in terms of their respective meanings and complementarities. It also presents a discussion regarding their maturity, relevance and innovations in their teaching in engineering programs. This paper pays special attention to the teaching of software measurement in higher education, in particular with respect to mathematics and measurement in engineering in general. The findings from this analysis will be useful for researchers and educators interested in the enhancement of educational issues related to software measurement.
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Cristina L. Abad, Yi Lu, & Roy H. Campbell. (2011). DARE: Adaptive Data Replication for Efficient Cluster Scheduling. In IEEE International Conference on Cluster Computing, 2011 (pp. 159–168).
Abstract: Placing data as close as possible to computation is a common practice of data intensive systems, commonly referred to as the data locality problem. By analyzing existing production systems, we confirm the benefit of data locality and find that data have different popularity and varying correlation of accesses. We propose DARE, a distributed adaptive data replication algorithm that aids the scheduler to achieve better data locality. DARE solves two problems, how many replicas to allocate for each file and where to place them, using probabilistic sampling and a competitive aging algorithm independently at each node. It takes advantage of existing remote data accesses in the system and incurs no extra network usage. Using two mixed workload traces from Facebook, we show that DARE improves data locality by more than 7 times with the FIFO scheduler in Hadoop and achieves more than 85% data locality for the FAIR scheduler with delay scheduling. Turnaround time and job slowdown are reduced by 19% and 25%, respectively.
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Abel Rubio, W. A., Leandro Gonzalez, Maria Ramirez, Herman Pineda. (2023). A Critical Analysis of the Impact of the Pandemic on Sustainable Energy Scenarios. In 11th International Conference On Smart Grid ICSMARTGRID 2023, junio 4-7.
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Wilton Agila, J. A., Abel Rubio, Leandro Gonzalez. (2023). Approximate Reasoning Techniques in the Control of States of Operation of the PEM Fuel Cell. In 11th International Conference On Smart Grid ICSMARTGRID 2023, junio 4-7.
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Rubio Abel, Agila Wilton, González Leandro, & Aviles Jonathan. (2023). A Numerical Model for the Transport of Reactants in Proton Exchange Fuel Cells. In 12th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2023 Oshawa 29 August – 1 September 2023 (pp. 273–278).
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Wilton Agila, G. R., Raul M. del Toro, Livington Miranda. (2023). Qualitative model for an oxygen therapy system based on Renewable Energy. In 12th International Conference on Renewable Energy Research and Applications ICRERA 2023 (365–371).
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