Diseño de sistema electrónico para HMI basado en reconocimiento de gestos manuales

EL OBJETIVO PRINCIPAL DE ESTE PROYECTO ES DISEÑAR UN SISTEMA ELECTRÓNICO QUE ESTABLEZCA UNA COMUNICACIÓN NO VERBAL BASADA EN GESTOS MANUALES ENTRE USUARIO Y MÁQUINA, CON EL PROPÓSITO DE SERVIR COMO INTERFAZ DE USUARIO EN APLICACIONES DE COMPUTADOR Y/O SMARTPHONE. PARA ELLO, EN PRIMER LUGAR, SE LLEVA A CABO UNA REVISIÓN DE LOS DIFERENTES TIPOS DE INTERFACES USUARIO-MÁQUINA EXISTENTES, JUNTO CON UNA REVISIÓN DE DIFERENTES PERIFÉRICOS PARA PC, VIDEOCONSOLAS Y OTROS DISPOSITIVOS ELECTRÓNICOS RELACIONADOS CON MOVIMIENTOS MANUALES. CON EL FIN DE MARCAR UN PUNTO DE INICIO PARA EL PROYECTO, ADEMÁS DE CONOCER LA TECNOLOGÍA RELACIONADA CON EL ÁREA DEL PROYECTO. DESPUÉS DE LA REVISIÓN DEL ESTADO DEL ARTE, SE INICIA UN ANÁLISIS DE LOS GESTOS MANUALES A UTILIZAR EN EL PROYECTO PARA CONOCER LA CARACTERÍSTICAS NECESARIAS, MAGNITUDES FÍSICAS, PARA SU IDENTIFICACIÓN. REALIZADA ESTA FASE, SE CREA UN PROTOTIPO CABLEADO PARA LA INSTRUMENTACIÓN DE LAS MAGNITUDES FÍSICAS NECESARIAS PARA INICIAR EL DESARROLLO DE SOFTWARE DE RECONOCIMIENTO GESTUAL. EN LA FASE DE RECONOCIMIENTO GESTUAL, SE CREA SOFTWARE EN MATLAB PARA DICHA TAREA. EL SOFTWARE SE CONFORMA DE VARIOS SCRIPTS EN MATLAB QUE CONTIENEN, PRINCIPALMENTE, IMPLEMENTADO EL RECONOCIMIENTO PARA GESTOS ESTÁTICOS Y GESTOS DINÁMICOS, ADEMÁS DE OTRAS FUNCIONES ÚTILES EN LOS ALGORITMOS DE IDENTIFICACIÓN GESTUAL. FINALIZADO EL SOFTWARE DE RECONOCIMIENTO GESTUAL, SE LLEVA A CABO UN PROTOTIPO EN PLACA DE CIRCUITO IMPRESO (PCB) DEL HARDWARE ANTERIORMENTE IMPLEMENTADO, CON EL FIN DE CONSEGUIR UN PROTOTIPO MÁS MANEJABLE Y CÓMODO PARA EL USUARIO. PARA CONCLUIR EL PROYECTO, SE REALIZA UNA PEQUEÑA APLICACIÓN MULTIMEDIA EN PYTHON BASADA EN EL REPRODUCTOR DE CÓDIGO ABIERTO VLC MEDIA, QUE JUNTO CON LA IDENTIFICACIÓN GESTUAL DESARROLLADA EN EL PROYECTO, SIRVE PARA CREAR EL TIPO DE INTERFAZ USUARIO-MÁQUINA QUE SE BUSCABA, CUMPLIENDO EL OBJETIVO PRINCIPAL DEL PROYECTO

A General Model for the Design of Efficient Sign-Coding Tools for Wavelet-Based Encoders

[EN] Traditionally, it has been assumed that the compression of the sign of wavelet coefficients is not worth the effort because they form a zero-mean process. However, several image encoders such as JPEG 2000 include sign-coding capabilities. In this paper, we analyze the convenience of including sign-coding techniques into wavelet-based image encoders and propose a methodology that allows the design of sign-prediction tools for whatever kind of wavelet-based encoder. The proposed methodology is based on the use of metaheuristic algorithms to find the best sign prediction with the most appropriate context distribution that maximizes the resulting sign-compression rate of a particular wavelet encoder. Following our proposal, we have designed and implemented a sign-coding module for the LTW wavelet encoder, to evaluate the benefits of the sign-coding tool provided by our proposed methodology. The experimental results show that sign compression can save up to 18.91% of bit-rate when enabling sign-coding capabilities. Also, we have observed two general behaviors when coding the sign of wavelet coefficients: (a) the best results are provided from moderate to high compression rates; and (b) the sign redundancy may be better exploited when working with high-textured images.This research was supported by the Spanish Ministry of Economy and Competitiveness under Grant RTI2018-098156-B-C54, co-financed by FEDER funds (MINECO/FEDER/UE).López-Granado, OM.; Martínez-Rach, MO.; Martí-Campoy, A.; Cruz-Chávez, MA.; Pérez Malumbres, M. (2020). A General Model for the Design of Efficient Sign-Coding Tools for Wavelet-Based Encoders. Electronics. 9(11):1-17. https://doi.org/10.3390/electronics9111899S117911Said, A., & Pearlman, W. A. (1996). A new, fast, and efficient image codec based on set partitioning in hierarchical trees. IEEE Transactions on Circuits and Systems for Video Technology, 6(3), 243-250. doi:10.1109/76.499834ISO/IEC 15444-1:2019. Information technology—JPEG 2000 Image Coding System—Part 1: Core Coding Systemhttps://www.iso.org/standard/78321.htmlTaubman, D. (2000). High performance scalable image compression with EBCOT. IEEE Transactions on Image Processing, 9(7), 1158-1170. doi:10.1109/83.847830Bilgin, A., Sementilli, P. J., & Marcellin, M. W. (1999). Progressive image coding using trellis coded quantization. IEEE Transactions on Image Processing, 8(11), 1638-1643. doi:10.1109/83.799891Oliver, J., & Malumbres, M. P. (2006). Low-Complexity Multiresolution Image Compression Using Wavelet Lower Trees. IEEE Transactions on Circuits and Systems for Video Technology, 16(11), 1437-1444. doi:10.1109/tcsvt.2006.883505Cho, Y., & Pearlman, W. A. (2007). Hierarchical Dynamic Range Coding of Wavelet Subbands for Fast and Efficient Image Decompression. IEEE Transactions on Image Processing, 16(8), 2005-2015. doi:10.1109/tip.2007.901247Deever, A. T., & Hemami, S. S. (2003). Efficient sign coding and estimation of zero-quantized coefficients in embedded wavelet image codecs. IEEE Transactions on Image Processing, 12(4), 420-430. doi:10.1109/tip.2003.811499Mallat, S., & Zhong, S. (1992). Characterization of signals from multiscale edges. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(7), 710-732. doi:10.1109/34.142909López-Granado, O., Galiano, V., Martí, A., Migallón, H., Martínez-Rach, M., Piñol, P., & Malumbres, M. P. (2013). Improving image compression through the use of evolutionary computing algorithms. Data Management and Security. doi:10.2495/data130041Kodak Lossless True Color Image Suitehttp://r0k.us/graphics/kodak/Rawzor—Lossless Compression Software for Camera Raw Imageshttp://imagecompression.info/test_images

Rate-control algorithms for non-embedded wavelet-based image coding

During the last decade, there has been an increasing interest in the design of very fast wavelet image encoders focused on specific applications like interactive real-time image and video systems, running on power-constrained devices such as digital cameras, mobile phones where coding delay and/or available computing resources (working memory and power processing) are critical for proper operation. In order to reduce complexity, most of these fast wavelet image encoders are non-(SNR)-embedded and as a consequence, precise rate control is not supported. In this work, we propose some simple rate control algorithms for these kind of encoders and we analyze their impact to determine if, despite their inclusion, the global encoder is still competitive with respect to popular embedded encoders like SPIHT and JPEG2000. In this study we focus on the non-embedded LTW encoder, showing that the increase in complexity due to the rate control algorithm inclusion, maintains LTW competitive with respect to SPIHT and JPEG2000 in terms of R/D performance, coding delay and memory consumption. © Springer Science+Business Media, LLC 2011This work was funded by Spanish Ministry of education and Science under grant DPI2007-66796-C03-03.Lopez Granado, OM.; Onofre Martinez-Rach, M.; Pinol Peral, P.; Oliver Gil, JS.; Perez Malumbres, MJ. (2012). Rate-control algorithms for non-embedded wavelet-based image coding. Journal of Signal Processing Systems. 68(2):203-216. https://doi.org/10.1007/s11265-011-0598-6S203216682Antonini, M., Barlaud, M., Mathieu, P., & Daubechies, I. (1992). Image coding using wavelet transform. IEEE Transaction on Image Processing, 1(2), 205–220.Cho, Y., & Pearlman, W.A. (2007). Hierarchical dynamic range coding of wavelet subbands for fast and efficient image compression. IEEE Transactions on Image Processing, 16, 2005–2015.Chrysafis, C., Said, A., Drukarev, A., Islam, A., & Pearlman, W. (2000). SBHP—A low complexity wavelet coder. In IEEE international conference on acoustics, speech and signal processing.CIPR: http://www.cipr.rpi.edu/resource/stills/kodak.html . Center for Image Processing Research.Davis, P. J. (1975) Interpolation and approximation. Dover Publications.Grottke, S., Richter, T., & Seiler, R. (2006). Apriori rate allocation in wavelet-based image compression. In Second international conference on automated production of cross media content for multi-channel distribution, 2006. AXMEDIS ’06 (pp. 329–336). doi: 10.1109/AXMEDIS.2006.12 .Guo, J., Mitra, S., Nutter, B., & Karp, T. (2006). Backward coding of wavelet trees with fine-grained bitrate control. Journal of Computers, 1(4), 1–7. doi: 10.4304/jcp.1.4.1-7 .ISO/IEC 10918-1/ITU-T Recommendation T.81 (1992). Digital compression and coding of continuous-tone still image.ISO/IEC 15444-1 (2000). JPEG2000 image coding system.Kakadu, S. (2006). http://www.kakadusoftware.com .Kasner, J., Marcellin, M., & Hunt, B. (1999). Universal trellis coded quantization. IEEE Transactions on Image Processing, 8(12), 1677–1687. doi: 10.1109/83.806615 .Lancaster, P. (1986). Curve and surface fitting: An introduction. Academic Press.Oliver, J., & Malumbres, M. (2001). A new fast lower-tree wavelet image encoder. In Proceedings of international conference on image processing, 2001 (Vol. 3, pp. 780–783). doi: 10.1109/ICIP.2001.958236 .Oliver, J., & Malumbres, M. P. (2006). Low-complexity multiresolution image compression using wavelet lower trees. IEEE Transactions on Circuits and Systems for Video Technology, 16(11), 1437–1444.Pearlman, W. A. (2001). Trends of tree-based, set partitioning compression techniques in still and moving image systems. In Picture coding symposium.Said, A., & Pearlman, A. (1996). A new, fast and efficient image codec based on set partitioning in hierarchical trees. IEEE Transactions on Circuits, Systems and Video Technology, 6(3), 243–250.Table Curve 3D 3.0 (1998). http://www.systat.com. Systat Software Inc.Wu, X. (2001). The transform and data compression handbook, chap. Compression of wavelet transform coefficients, (pp. 347–378). CRC Press.Zhidkov, N., & Kobelkov, G. (1987). Numerical methods. Moscow: Nauka

Cerámicas de decoración arquitectónica en la Tarifa de finales del siglo XIX e inicios del XX: tradición y modernidad

The Spain of the second half of the nineteenth century lived the recovery of old fashions and ceramic techniques, coupled with the application of new industrial processes. This, along with the extension of concepts such as hygiene, made pottery in construction a new boom. In Tarifa we find, especially since the beginning of the 20th century, a representation of different techniques and styles, highlighting a motif that was widely disseminated at that time: Don Quixote tiles, made in the «cuerda seca» technique by the Seville factory Mensaque, Rodríguez & Cía , which also produces «arista» tiles.Resumen: La España de la segunda mitad del siglo XIX vivió la recuperación de antiguas modas y técnicas cerámicas, unida  a la aplicación de  nuevos procesos industriales. Ello, junto con la extensión de conceptos como la higiene, hizo que la cerámica en la construcción viviera un nuevo auge.  En Tarifa encontramos sobre todo desde principios del siglo XX una representación de diferentes técnicas y estilos, destacando un motivo que tuvo una amplia difusión entonces:  los azulejos de  Don Quijote, fabricados en la técnica de cuerda seca por la casa sevillana Mensaque, Rodríguez y Cía, que también producía azulejos de arista

Combinatorial effects of microRNAs to suppress the Myc oncogenic pathway

Many mammalian transcripts contain target sites for multiple miRNAs although it is not clear to what extent miRNAs may coordinately regulate single genes. We have mapped the interactions between downregulated miRNAs and overexpressed target protein-coding genes in murine and human lymphomas. Myc, one of the hallmark oncogenes in these lymphomas, stands out as the upregulated gene with the highest number of genetic interactions with downregulated miRNAs in mouse lymphomas. The regulation of Myc by several of these miRNAs is confirmed by cellular and reporter assays. The same approach indentifies MYC and multiple Myc targets as a preferential target of downregulated miRNAs in human Burkitt's lymphoma, a pathology characterized by translocated MYC oncogenes. These results indicate that several miRNAs must be coordinately downregulated in order to enhance critical oncogenes such as Myc. Some of these Myc-targeting miRNAs are repressed by Myc, suggesting that these tumors are a consequence of the unbalanced activity of Myc versus miRNAs.This work was supported by grants from the Association for International Cancer Research (AICR #08-0188), Fundación Ramón Areces, Fundación Mutua Madrileña Automovilista (to M.M.), and the MICINN (SAF2009-11426 to J.F.P.; SAF2007-64571 to I.P.C.; and SAF2009-07973 to M.M.). The CBM/UAM group is supported by the Centro de Investigaciones Biomédicas en Red de Enfermedades Raras (CIBERER) network from the MICINN. The Bioinformatics Unit of the CNIO is supported by the Spanish National Bioinformatics Institute (Genoma España). The Cell Division and Cancer Group of the CNIO is supported by the OncoCycle Programme (Comunidad de Madrid, S-BIO-0283-2006), the OncoBIO Consolider-Ingenio 2010 Programme (MICINN, CSD2007-00017) and the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement n° [HEALTH-F5-2010-241548]Peer reviewe