Robust symmetric multiplication for programmable analog VLSI array processing

This paper presents an electrically programmable analog multiplier. The circuit performs the multiplication between an input variable and an electrically selectable scaling factor. The multiplier is divided in several blocks: a linearized transconductor, binary weighted current mirrors and a differential to single-ended current adder. This paper shows the advantages introduced using a linearized OTA-based multiplier. The circuit presented renders higher linearity and symmetry in the output current than a previously reported single-transistor multiplier. Its inclusion in an array processor based on CNN allows for a more accurate implementation of the processing model and a more robust weight distribution scheme than those found in previous designs.Office of Naval Research (USA) N-00014- 02-1-0884Ministerio de Ciencia y Tecnología TIC2003-09817-C02-0

A Focal-Plane Image Processor for Low Power Adaptive Capture and Analysis of the Visual Stimulus

Portable applications of artificial vision are limited by the fact that conventional processing schemes fail to meet the specifications under a tight power budget. A bio-inspired approach, based in the goal-directed organization of sensory organs found in nature, has been employed to implement a focal-plane image processor for low power vision applications. The prototype contains a multi-layered CNN structure concurrent with 32times32 photosensors with locally programmable integration time for adaptive image capture with on-chip local and global adaptation mechanisms. A more robust and linear multiplier block has been employed to reduce irregular analog wave propagation ought to asymmetric synapses. The predicted computing power per power consumption, 142MOPS/mW, is orders of magnitude above what rendered by conventional architectures

Nonlinear time-domain macromodeling of OTA circuits

The authors present an accurate nonlinear macromodel of the operational transconductance amplifier (OTA) which is suitable for the transient simulation of OTA-based CMOS analog integrated circuits. As compared to device-level OTA models, the proposed macromodel is advantageous in terms of CPU time. Also, in circuits with many OTAs, it does not have the problems of convergence that the device-level MODEL has. All the macromodel parameters can be calculated from measurements made at the OTA terminals. Experimental results from a 3-μm CMOS OTA prototype as well as simulation results from device-level models are included and compared to simulation results from the macromodel

3-Layer CNN Chip for Focal-Plane Complex Dynamics with Adaptive Image Capture

This paper presents a CMOS implementation of a layered CNN concurrent with 32times32 photosensors with locally programmable integration time for adaptive image capture. The network is arranged in two layers containing feedback and control templates, inter-layer connections and programmable ratio of time constants. There are also feedforward connections to a third layer, which is faster, and devoted exclusively for combining the outputs of the other two. A more robust and linear multiplier block has been employed to reduce irregular analog wave propagation ought to asymmetric synapses. Global and local adaptation circuits are included on-chip. The predicted computing power per power consumption, 240MOPS/mW, is amongst the largest reported, what renders this kind of devices as especially adequate for portable applications of artificial visionMinisterio de Ciencia y Tecnología TIC2003-09817-C02-01Office of Naval (USA) N-00014-02-1-088

Extending a dashboard meta-model to account for users’ characteristics and goals for enhancing personalization

[EN]Information dashboards are useful tools for exploiting datasets and support decision-making processes. However, these tools are not trivial to design and build. Information dashboards not only involve a set of visualizations and handlers to manage the presented data, but also a set of users that will potentially benefit from the knowledge generated by interacting with the data. It is important to know and understand the requirements of the final users of a dashboard because they will influence the design processes. But several user profiles can be involved, making these processes even more complicated. This paper identifies and discusses why it is essential to include the final users when modeling a dashboard. Through meta-modeling, different characteristics of potential users are structured, thus obtaining a meta-model that dissects not only technical and functional features of a dashboard (from an abstract point of view) but also the different aspects of the final users that will make use of it. By identifying these user characteristics and by arranging them into a meta-model, software engineering paradigms such as model-driven development or software product lines can employ it as an input for generating concrete dashboard products. This approach could be useful for generating Learning Analytics dashboards that take into account the users' motivations, beliefs, and knowledge

Representing Data Visualization Goals and Tasks through Meta-Modeling to Tailor Information Dashboards

[EN] Information dashboards are everywhere. They support knowledge discovery in a huge variety of contexts and domains. Although powerful, these tools can be complex, not only for the end-users but also for developers and designers. Information dashboards encode complex datasets into different visual marks to ease knowledge discovery. Choosing a wrong design could compromise the entire dashboard’s effectiveness, selecting the appropriate encoding or configuration for each potential context, user, or data domain is a crucial task. For these reasons, there is a necessity to automatize the recommendation of visualizations and dashboard configurations to deliver tools adapted to their context. Recommendations can be based on different aspects, such as user characteristics, the data domain, or the goals and tasks that will be achieved or carried out through the visualizations. This work presents a dashboard meta-model that abstracts all these factors and the integration of a visualization task taxonomy to account for the different actions that can be performed with information dashboards. This meta-model has been used to design a domain specific language to specify dashboards requirements in a structured way. The ultimate goal is to obtain a dashboard generation pipeline to deliver dashboards adapted to any context, such as the educational context, in which a lot of data are generated, and there are several actors involved (students, teachers, managers, etc.) that would want to reach different insights regarding their learning performance or learning methodologies.SIMinisterio de Economía y Competitividad (TIN2016-80172-R)Ministrio de Educación, Cultura y Deporte (FPU17/03276

Representing Data Visualization Goals and Tasks through Meta-Modeling to Tailor Information Dashboards

[EN]Information dashboards are everywhere. They support knowledge discovery in a huge variety of contexts and domains. Although powerful, these tools can be complex, not only for the end-users but also for developers and designers. Information dashboards encode complex datasets into different visual marks to ease knowledge discovery. Choosing a wrong design could compromise the entire dashboard’s effectiveness, selecting the appropriate encoding or configuration for each potential context, user, or data domain is a crucial task. For these reasons, there is a necessity to automatize the recommendation of visualizations and dashboard configurations to deliver tools adapted to their context. Recommendations can be based on different aspects, such as user characteristics, the data domain, or the goals and tasks that will be achieved or carried out through the visualizations. This work presents a dashboard meta-model that abstracts all these factors and the integration of a visualization task taxonomy to account for the different actions that can be performed with information dashboards. This meta-model has been used to design a domain specific language to specify dashboards requirements in a structured way. The ultimate goal is to obtain a dashboard generation pipeline to deliver dashboards adapted to any context, such as the educational context, in which a lot of data are generated, and there are several actors involved (students, teachers, managers, etc.) that would want to reach different insights regarding their learning performance or learning methodologies

Demo: Results of 'iCaveats', a Project on the Integration of Architectures and Components for Embedded Vision

iCaveats is a Project on the integration of components and architectures for embedded vision in transport and security applications. A compact and efficient implementation of autonomous vision systems is difficult to be accomplished by using the conventional image processing chain. In this project we have targeted alternative approaches, that exploit the inherent parallelism in the visual stimulus, and hierarchical multilevel optimization. A set of demos showcase the advances at sensor level, in adapted architectures for signal processing and in power management and energy harvesting.Ministerio de Economia, Industria y Competitividad de España (MINECO) y el Fondo Europeo de Desarrollo de las Regiones (FEDER)-‘iCaveats’ TEC2015-66878-C3-1-R, TEC2015-66878-C3-2-R y TEC2015-66878-C3-3-RJunta de Andalucía-‘SmartCIS3D’ TIC 2338-2013FEDER- 2016-2019, ED431G/08 y 2017-2020, ED431C 2017/69Agencia Ejecutiva Europea de Investigación (EU-REA)-‘Achieve’ H2020 MSCAITN 2017 N° 76586

Desarrollo de chile amashito (Capsicum annuum var. glabriusculum) bajo diferentes dosis de vermicomposta en condiciones controladas

Objective: To compare the growth and crop yield of amashito chili Capsicum annuum var. glabriusculum under different doses of vermicompost. Design/methodology/aproximation: To evaluate crop yield we design five treatment consisting on ground with different proportions of vermicompost (VC) and loamy soil (SF), all treatments were replicate by five and planted randomly in 25 kg pots. After 12 week, biologic data was retrieve. Results: Higher crop yield was obtain on treatments with ground composition with at least 75% of VC. The only treatment without VC (100% SF) presented statistically lower values on all measures. Limitations of the study/implications: Amashito chili seed high germination difficulty limits the efforts for cultivation by farmers, and a major commercialization of this regional chili variety. Findings/conclusions: Use of organic fertilizers (vermicompost) supposes better field conditions for seed germination, growth and crop yield for this species.Objetivo: Comparar el desarrollo de chile amashito Capsicum annuum var. glabriusculum y su rendimiento en diferentes dosis de vermicomposta en condiciones controladas. Diseño/metodología/aproximación: Para evaluar los rendimientos de las plantas, se generaron cinco tratamientos que consistieron en diferentes proporciones entre la vermicomposta (VC) y el suelo franco (SF), se replicaron cinco veces cada uno y se colocaron en macetas de 25 kg de forma aleatoria. A las 12 semanas se tomaron los datos biológicos a evaluar. Resultados: Se obtuvieron los mejores rendimientos en los tratamientos sembrados en sustratos con 75% o más de VC. El único sustrato sin VC (100% SF) presentó estadísticamente los valores más bajos en las variables evaluadas. Limitaciones del estudio/implicaciones: La dificultad de germinación de la semilla de chile amashito es una limitante para que los productores se inclinen hacia mayor comercialización de esta variedad de chile regional. Hallazgos/conclusiones: Utilizar abonos orgánicos (vermicompostas) supone mejores condiciones de campo para la germinación de semillas, desarrollo y rendimiento de este cultivo

The addition of albumin improves Schwann cells viability in nerve cryopreservation

[Abstract] The purpose of the current study was to establish a valid protocol for nerve cryopreservation, and to evaluate if the addition of albumin supposed any advantage in the procedure. We compared a traditional cryopreservation method that uses dimethyl sulfoxide (DMSO) as cryoprotectant, to an alternative method that uses DMSO and albumin. Six Wistar Lewis rats were used to obtain twelve 20 mm fragments of sciatic nerve. In the first group, six fragments were cryopreserved in 199 media with 10% DMSO, with a temperature decreasing rate of 1 °C per minute. In the second group, six fragments were cryopreserved adding 4% human albumin. The unfreezing process consisted of sequential washings with saline in the first group, and saline and 20% albumin in the second group at 37 °C until the crioprotectant was removed. Structural evaluation was performed through histological analysis and electronic microscopy. The viability was assessed with the calcein-AM (CAM) and 4′,6-diamino-2-fenilindol (DAPI) staining. Histological results showed a correct preservation of peripheral nerve architecture and no significant differences were found between the two groups. However, Schwann cells viability showed in the CAM-DAPI staining was significantly superior in the albumin group. The viability of Schwann cells was significantly increased when albumin was added to the nerve cryopreservation protocol. However, no significant structural differences were found between groups. Further studies need to be performed to assess the cryopreserved nerve functionality using this new method