Consejo Superior de Investigaciones Científicas · Universidad de Sevilla
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An efficient transformer modeling approach for mm-wave circuit design
F. Passos, E. Roca, J. Sieiro, R. Castro-Lopez and F.V. Fernandez
Journal Paper - AEU - International Journal of Electronics and Communications, vol. 128, article 153496, 2021
ELSEVIER    DOI: 10.1016/j.aeue.2020.153496    ISSN: 1434-8411    » doi
In this paper, a Gaussian-process surrogate modeling methodology is used to accurately and efficiently model transformers, which are still a bottleneck in radio-frequency and millimeter-wave circuit design. The proposed model is useful for a wide range of frequencies from DC up to the millimeter-wave range (over 100 GHz). The technique is statistically validated against full-wave electromagnetic simulations. The efficient model evaluation enables its exploitation in iterative user-driven design approaches, as well as automated design exploration involving thousands of simulations. As experimental results, the model is used in several scenarios, such as the design of an inter-stage amplifier operating at 60 GHz, where the model assisted in the simulation of the transformers and baluns used, and the design of individual transformers and a matching network.

Characterization and Monitoring of Titanium Bone Implants with Impedance Spectroscopy
A. Olmo, M. Hernandez, E. Chicardi and Y. Torres
Journal Paper - Sensors, vol. 20, no. 19, article 4358, 2020
MDPI    DOI: 10.3390/s20164358    ISSN: 1424-8220    » doi
Porous titanium is a metallic biomaterial with good properties for the clinical repair of cortical bone tissue, although the presence of pores can compromise its mechanical behavior and clinical use. It is therefore necessary to characterize the implant pore size and distribution in a suitable way. In this work, we explore the new use of electrical impedance spectroscopy for the characterization and monitoring of titanium bone implants. Electrical impedance spectroscopy has been used as a non-invasive route to characterize the volumetric porosity percentage (30%, 40%, 50% and 60%) and the range of pore size (100-200 and 355-500 mm) of porous titanium samples obtained with the space-holder technique. Impedance spectroscopy is proved to be an appropriate technique to characterize the level of porosity of the titanium samples and pore size, in an affordable and non-invasive way. The technique could also be used in smart implants to detect changes in the service life of the material, such as the appearance of fractures, the adhesion of osteoblasts and bacteria, or the formation of bone tissue.

VersaTile Convolutional Neural Network Mapping on FPGAs
A. Muñío-Gracia, J. Fernández-Berni, R. Carmona-Galán and A. Rodríguez-Vázquez
Conference - IEEE International Symposium on Circuits and Systems ISCAS 2020
Convolutional Neural Networks (ConvNets) are directed acyclic graphs with node transitions determined by a set of configuration parameters. In this paper, we describe a dynamically configurable hardware architecture that enables data allocation strategy adjustment according to ConvNets layer characteristics. The proposed flexible scheduling solution allows the accelerator design to be portable across various scenarios of computation and memory resources availability. For instance, FPGA block-RAM resources can be properly balanced for optimization of data distribution and minimization of off-chip memory accesses. We explore the selection of tailored scheduling policies that translate into efficient on-chip data reuse and hence lower energy consumption. The system can autonomously adapt its behavior with no need of platform reconfiguration nor user supervision. Experimental results are presented and compared with state-of-the-art accelerators.

3D-printed sensors and actuators in cell culture and tissue engineering: Framework and research challenges
P. Pérez, J.A. Serrano and A. Olmo
Journal Paper - Sensors, vol. 20, no. 19, article 5617, 2020
MDPI    DOI: 10.3390/s20195617    ISSN: 1424-8220    » doi
Three-dimensional printing technologies have been recently proposed to monitor cell cultures and implement cell bioreactors for different biological applications. In tissue engineering, the control of tissue formation is crucial to form tissue constructs of clinical relevance, and 3D printing technologies can also play an important role for this purpose. In this work, we study 3D-printed sensors that have been recently used in cell culture and tissue engineering applications in biological laboratories, with a special focus on the technique of electrical impedance spectroscopy. Furthermore, we study new 3D-printed actuators used for the stimulation of stem cells cultures, which is of high importance in the process of tissue formation and regenerative medicine. Key challenges and open issues, such as the use of 3D printing techniques in implantable devices for regenerative medicine, are also discussed.

Yield-aware multi-objective optimization of a MEMS accelerometer system using QMC-based methodologies
M. Pak, F.V. Fernandez and G. Dundar
Journal Paper - Microelectronics Journal, vol. 103, article 104876, 2020
ELSEVIER    DOI: 10.1016/j.mejo.2020.104876    ISSN: 0026-2692    » doi
This paper proposes a novel yield-aware optimization methodology that can be used for mixed-domain synthesis of robust micro-electro-mechanical systems (MEMS). The robust Pareto front optimization of a MEMS accelerometer system, which includes a capacitive MEMS sensor and an analog read-out circuitry, is realized by co-optimization of the mixed-domain system where the sensor performances are evaluated using highly accurate analytical models and the circuit level simulations are carried out by an electrical simulator. Two different approaches for yield-aware optimization have been implemented in the synthesis loop. The Quasi Monte Carlo (QMC) technique has been used to embed the variation effects into the optimization loop. The results for both two- and three-dimensional yield-aware optimization are quite promising for robust MEMS accelerometer synthesis.

An adaptive simulation framework for AMS-RF test quality
V. Gutierrez ang G. Leger
Journal Paper - Integration, vol. 73, pp 10-17, 2020
SPRINGER    DOI: 10.1016/j.vlsi.2020.03.003    ISSN: 0167-9260    » doi
Ensuring the quality of a circuit implies ensuring the quality of test. Despite the fact that performance-based testing has been the golden standard for Analog, Mixed-Signal and RF test for decades, high-reliability markets like automotive have found that functional test leaves some potential defects undetected that can produce in-field failure. There is thus a push towards defect-oriented testing which, in turn, calls for an efficient defect simulation framework. This paper presents a statistical adaptive defect simulation based on likelihood-weighted random sampling to evaluate the quality of AMS-RF tests in terms of defect coverage and fault escape. The adaptive loop takes a decision at each new defect simulation on whether it is more efficient to assess the defect coverage or the fault escape rate of the test under evaluation, as a function of the desired targets for these two metrics. Several decision criteria are proposed and validated by simulation of a complete IC for different tests.

Fixed Pattern Noise Analysis for Feature Descriptors in CMOS APS Images
J. Zapata-Pérez, G. Domenech-Asensi, R. Ruiz-Merino, J.J. Martínez-Álvarez, J. Fernández-Berni and R. Carmona-Galán
Journal Paper - Sensing and Imaging, vol. 21, article 14, 2020
SPRINGER    DOI: 10.1007/s11220-020-0278-3    ISSN: 1557-2072    » doi
This paper provides a comparative performance evaluation of local features for images from CMOS APS sensors affected by fixed pattern noise for different combinations of common detectors and descriptors. Although numerous studies report comparisons of local features designed for ordinary visual images, their performance on images with fixed pattern noise is far less assessed. The goal of this work is to develop a tool that allows to evaluate the performance of computer vision algorithms and their implementations subject to deviations of the physical parameters of the CMOS sensor. This tool will facilitate the quantification of the high-level effects produced by circuit random noise, enabling the optimization of the sensor during the design flow with specifications much closer to the application scope. Likewise, this tool will provide the electronic designer with a relationship between high-level algorithm accuracy and maximum fixed pattern noise. Thus the contribution is double: (1) to evaluate the performance of both local float type and more recent binary type detectors and descriptors when combined under a variety of image transformations, and (2) to extract relevant information from circuit-level simulation and to develop a basic noise model to be employed in the design of the feature descriptor evaluation. The utility of this approach is illustrated by the evaluation of the effect of column-wise and pixel-wise fixed pattern noise at the sensor on the performance of different local feature descriptors.

Comparison between Digital Tone-Mapping Operators and a Focal-Plane Pixel-Parallel Circuit
G.M.S. Nunes, F.D.V.R. Oliveira, M.C.Q. Farias, J.G. Gomes, A. Petraglia, J. Fernández-Berni, R. Carmona-Galán and A. Rodríguez-Vázquez
Journal Paper - Signal Processing: Image Communication, vol. 88, article 115937, 2020
IEEE    DOI: 10.1016/j.image.2020.115937    ISSN: 0923-5965    » doi
In a previous work, we proposed a color extension of an existing focal-plane tone-mapping operator (FPTMO) and introduced circuit modifications that led to smaller sensing array area and simpler off-chip white-balance operations. The proposed FPTMO chip was fabricated and its experimental test setup is under development. In the present work, we systematically compare the previously proposed FPTMOs with conventional digital tone-mapping operators (DTMOs), both in terms of overall image quality and execution time. To assess the image quality, we use the Tone-Mapped image Quality Index (TMQI) metric, the Blind Tone-Mapped Quality Index (BTMQI) metric, and an image colorfulness metric. By statistically comparing the results given by both metrics, we verify that the proposed FPTMOs achieve results similar to those obtained with DTMOs, occasionally outperforming them. To compare the tone-mapping operators execution times, we perform a detailed complexity analysis. Results show that system-level software FPTMO descriptions (FPTMO functionality described in software) rank among the fastest DTMOs and that the hardware FPTMO (described in software) speed-up depends on the target frame rate. For 30-frames-per-second color image generation, the fastest FPTMO is 15 times faster than the DTMO with highest TMQI and BTMQI metric scores, and 170 times faster than the DTMO with best colorfulness metric score.

PreVIous: A Methodology for Prediction of Visual Inference Performance on IoT Devices
D. Velasco-Montero, J. Fernández-Berni, R. Carmona-Galan and A. Rodríguez-Vázquez
Journal Paper - IEEE Internet of Things Journal, vol. 7, no. 10, pp 9227-9240, 2020
IEEE    DOI: 10.1109/JIOT.2020.2981684    ISSN: 2327-4662    » doi
This paper presents PreVIous, a methodology to predict the performance of convolutional neural networks (CNNs) in terms of throughput and energy consumption on vision-enabled devices for the Internet of Things. CNNs typically constitute a massive computational load for such devices, which are characterized by scarce hardware resources to be shared among multiple concurrent tasks. Therefore, it is critical to select the optimal CNN architecture for a particular hardware platform according to prescribed application requirements. However, the zoo of CNN models is already vast and rapidly growing. To facilitate a suitable selection, we introduce a prediction framework that allows to evaluate the performance of CNNs prior to their actual implementation. The proposed methodology is based on PreVIousNet, a neural network specifically designed to build accurate per-layer performance predictive models. PreVIousNet incorporates the most usual parameters found in state-of-the-art network architectures. The resulting predictive models for inference time and energy have been tested against comprehensive characterizations of seven well-known CNN models running on two different software frameworks and two different embedded platforms. To the best of our knowledge, this is the most extensive study in the literature concerning CNN performance prediction on low-power low-cost devices. The average deviation between predictions and real measurements is remarkably low, ranging from 3% to 10%. This means state-of-the-art modeling accuracy. As an additional asset, the fine-grained a priori analysis provided by PreVIous could also be exploited by neural architecture search engines.

Use of Impedance Spectroscopy for the Characterization of In-Vitro Osteoblast Cell Response in Porous Titanium Bone Implants
M. Giner, A. Olmo, M. Hernandez, P. Trueba, E. Chicardi, A. Civantos, M.A. Vazquez, M.J. Montoya-Garcia and Y. Torres
Journal Paper - Metals, vol. 10, no. 8, article 1077, 2020
MDPI    DOI: 10.3390/met10081077    ISSN: 2075-4701    » doi
The use of titanium implants with adequate porosity (content, size and morphology) could solve the stress shielding limitations that occur in conventional titanium implants. Experiments to assess the cellular response (adhesion, proliferation and differentiation of osteoblasts) on implants are expensive, time-consuming and delicate. In this work, we propose the use of impedance spectroscopy to evaluate the growth of osteoblasts on porous titanium implants. Osteoblasts cells were cultured on fully-dense and 40 vol.% porous discs with two ranges of pore size (100-200 mu m and 355-500 mu m) to study cell viability, proliferation, differentiation (Alkaline phosphatase activity) and cell morphology. The porous substrates 40 vol.% (100-200 mu m) showed improved osseointegration response as achieved more than 80% of cell viability and higher levels of Cell Differentiation by Alkaline Phosphatase (ALP) at 21 days. This cell behavior was further evaluated observing an increase in the impedance modulus for all study conditions when cells were attached. However, impedance levels were higher on fully-dense due to its surface properties (flat surface) than porous substrates (flat and pore walls). Surface parameters play an important role on the global measured impedance. Impedance is useful for characterizing cell cultures in different sample types.

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