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Industrial robots have mainly been programmed by operators using teach pendants in a point-to-point scheme with limited sensing capabilities. New developments in robotics have attracted a lot of attention to robot motor skill learning via human interaction using Learning from Demonstration (LfD) techniques. Robot skill acquisition using LfD techniques is characterised by a high-level stage in charge of learning connected actions and a low-level stage concerned with motor coordination and reproduction of an observed path. In this paper, we present an approach to acquire a path-following skill by a robot in the low-level stage which deals with the correspondence of mapping links and joints from a human operator to a robot so that the robot can actually follow a path. We present the design of an Inertial Measurement Unit (IMU) device that is primarily used as an input to acquire the robot skill. The approach is validated using a motion capture system as ground truth to assess the spatial deviation from the human-taught path to the robot’s final trajectory.

In this work, conducted by three partners (UFAM/CETELI, ICTS and ENVISION/TPV), we developed practical experiment scenarios, showing the viability of creating QoE assessment scenarios for 4k videos, using off-the-shelf computers equipped with GPU, software free and transmission over WiFi networks. We evaluated a set of 4 unreferenced QoE metrics, noting that videos transmitted via WiFi have QoE similar to the original, untranslated video.

In recent years, the number of Wi-fi networks has been growing and the coexistence of Wi-fi networks can produce interference causing connection difficulties. Light communication is getting more popular with a large numbers of studies. In this work conducted by three partners (UFAM/CETELI, ICTS and ENVISION/TPV), we propose a multimedia model for wireless communication using light. This propose is based in off-the-shelf devices in the current market to establish an operational model of multimedia transmission for videos in 4k . In addition, modeling for the communication channel is addressed.

In this work, conducted by three partners (UFAM/CETELI, ICTS and ENVISION/TPV), we created practical experiment scenarios, showing the viability of creating 4k video QoE assessment scenarios, using off-the-shelf computers equipped with GPU, software free and transmission in WiFi networks. In the evaluation, we used a set of 7 metrics of QoE verifying that videos transmitted via WiFi have QoE similar to the original video, not transmitted.

The acquisition of sophisticated vector signal analyzer (VSA) may be a limiting factor for the execution of RD (ii) spectral flatness; (iii) transmitter constellation error; (iv) transmitter modulation accuracy (EVM). The results indicates that this approach is a feasible VSA solution for R&D projects with budget limitations.

Este trabalho propoe a realizacao de tecnicas de controle baseada na formulacao de LMIs para a estabilizacao de sistemas de distribuicao alimentados por fontes com nivel de tensao flutuante e conectados a cargas de potencia constante (constant power load-CPL). O projeto dos controladores sao baseado na estrutura de realimentacao de estados calculados atraves da solucao da equacao de Lyapunov (SEL) e da minimizacao das normas ${{\mathcal{H}}_2}$ e ${{\mathcal{H}}_{\infty} }$. O desempenho dos controladores sao avaliados atraves do calculo de indices de desempenho como ISE, ITAE e ISSC.

Wind turbines can be a replacement for coal as an energy source. However, the conventional wind turbines are expensive and are very complicated due to many mechanical components translating to high manufacturing and maintenance costs. This study aims to help improve the efficiency and design of bladeless wind power generators through generation of power using vortex induced vibration. A bladeless wind power generator was designed using Autodesk Fusion 360 wherein the prototype was modeled to be approximately 1.35 m x 0.5m x 0.5m (overall height, width, and length). A Nonlinear Static Simulation, using ANSYS®Academic Student MechanicalTM, was performed to determine the effect of two different wind velocities, 4.5 m/s and 6.5 m/s, acting on the mast. The design of the bladeless wind turbine was focused on simplifying its manufacturability by using a helical spring to connect the mast to the base while also attaining maximum vortex shedding at a low velocity. The researchers of this study used a static simulation to simplify the study. The predetermined wind velocities were converted into a pressure value, allowing the researchers to obtain the total deformation, directional deformation, and maximum principal and shear stresses (in the spring). It has been determined that the maximum deformation experienced by the bladeless wind power generator was 131.800 mm and 253.270 mm for wind velocities of 4.5 m/s and 6.5 m/s resulting to a theoretical power output of 9.765W and 29.428W, respectively.

Mura on LCD displays are challenging visual defects to detect, due to uneven brightness of the panel. So, automatic detection of mura defects on TVs and monitors is an important application to ensure the quality of LCDs manufactured in electronic product factories. In this work, conducted by three partners, called UFAM/CETELI, Envision (TPV Group) and ICTS, we propose an automated mura defect detection system on LCD displays that are based on similarities of the histograms and a machine learning (ML) algorithm called random forest. For comparison with the proposed method, we use one of the most popular methods of ML called k-Nearest Neighbors (k-NN). The experimental results show a detection rate above 99%, and processing time of 27 milliseconds per image, highlighting as contributions of our proposal, the high accuracy and reduced processing time, which allows the use of our solution in real production processes of LCD monitors.

Bright pixel defect occurs in LCDs when a transistor of a subpixel remains bright. Bright pixels reduce the quality of manufactured devices, negatively impacting companies looking to meet an increasingly demanding market. In this wokr, conducted by three partners, called UFAM/CETELI, Envision (TPV Group) and ICTS, we propose an automated bright pixel defect detection system on LCD displays, which works in conjunction with two proposed methods, the quartile-based method and the standard-based method to identify bright pixels in LCDs. The proposals obtained as best result 100% of accuracy and between 0.397s and 0.193s of average processing time per image. The results of high accuracy and reduced processing time demonstrate the contribution of our proposal, being possible to use it in the detection of bright pixels in real production lines that use LCDs on TVs or monitors.

For the first time, we report a short channel high performance, gate-all-around strained Si 0.4 Ge 0.6 nanosheet PMOSFET with aggressively scaled dimensions. We demonstrate realization of s-Si 0.4 Ge 0.6 nanosheet with 5nm thickness and device with L G =25nm featuring record high I ON =508 µA/µm at I OFF =100nA/µm and V DS = -0.5V. This result is obtained with the combination of (a) novel Si-cap-free gate oxide solution featuring thin EOT=9.1A, low D IT and N IT for s-Si 0.4 Ge 0.6 channel, (b) record high hole mobility= 450 cm2/Vs owing to compressive strain imparted by Si 0.7 Ge 0.3 strain relaxed buffer (SRB), (c) low R EXT =150 Ω-µm due to highly active, strained source/drain SiGe process and novel p++ cap layer, (d) optimized source/drain tip and junction to minimize GIDL impact to I OFF . Additionally, the impact of operating temperature on GIDL and I OFF is comprehensively studied to prescribe optimal V CC range of operation for this technology.

We present a smart and stand-alone surface thought to wirelessly charge consumer electronic products without precise alignment between the transmitter and receiver coils. The system has two stages, an inductive sensing stage, working at 688 kHz, and a power stage based on the propagation of magnetoinductive waves throughout metamaterials. The power stage is identified as a two-dimensional (2D) magnetoinductive wave (MIW) device whose coupled, inductive-capacitive resonating cells have been optimized in previous work to provide efficient power transmission to a load of 5 Ω. The work presented here addresses standing waves inside the device that cause zones completely deprived of energy, the power nulls. We present in detail the inexpensive and simple circuitry used to detect the location of a receiver in real-time and consequently adjust the number of active cells of the 2D MIW device, avoiding in this way a receiver standing above a po wer null. The proposed system enables a charging surface of 22x22 cm2 without power nulls along the X-direction.

Manufacturing TVs and monitors requires an effective method to detect the dead pixels. These defects are usually identified by operators manually. However, manual inspection is susceptible to failure due to human fatigue and generate a high cost for production process. In this work, conducted by three partners (UFAM/CETELI, ICTS and ENVISION/TPV), we propose three methods for automated detection of dead pixels. Two proposed methods were based on machine learning (ML) techniques, random forest (RF) and support vector machine (SVM) algorithms. The third method was based in digital image processing (DIP), Harris algorithm. As result, the SVM obtained the better performance with 92.1% of precision in two of three used image database.

We report a short channel high performance Ge PMOS integrated with Si NMOS in sequential monolithic 3D stacking. A layer transfer Ge PMOS with record I ON = 497 μA/μm at I OFF = 8nA/μm and I ON = 630 μA/μm at I OFF = 100nA/μm and V DS = -0.5V is achieved for the first time. Optimized design of metal gate and contact on bottom Si NMOS device layer, along with a low process thermal budget developed for Ge layer transfer and top Ge PMOS device fabrication, allow for sequential stacking with no degradation on each MOS device characteristics. Heterogeneous 3D stacked Ge-Si CMOS inverter is also successfully demonstrated with drive performance maintained on Ge PMOS and Si NMOS.

Perhaps the greatest challenge facing quantum computing hardware development is the lack of a high throughput electrical characterization infrastructure at the cryogenic temperatures required for qubit measurements. In this article, we discuss our efforts to develop such a line to guide 300mm spin qubit process development. This includes (i) working with our supply chain to create the required cryogenic high volume testing ecosystem, (ii) driving full wafer cryogenic testing for both transistor and quantum dot statistics, and (iii) utilizing this line to develop a quantum dot process resulting in key electrical data comparable to that from leading devices in literature, but with unprecedented yield and reproducibility.

The Advanced Technology Demonstrator (ATD) is an S-band planar polarimetric phased array radar (PPAR) at the National Severe Storms Laboratory (NSSL) in Norman, OK. It serves as a testbed for evaluating the suitability of PPAR technology for weather observations. The major challenge to PPAR weather observations is the calibration needed to produce polarimetric measurements comparable to radars using parabolic reflectors. This is due to the existence of significant cross-polar patterns, as well as the scan-dependent measurement biases inherent to PPAR. To address the former, a pulse-to-pulse phase coding technique has been proposed. However, it does not affect the scan-dependent system biases. The effects of these variations must be addressed via corrections using appropriate values at each boresight location. In this work, an overview of weather calibration for the Advanced Technology Demonstrator is presented.

Several subfields in symbolic AI can be useful in game agents: dynamic epistemic logic, epistemic planning, belief revision and natural language processing. Furthermore, there is a sizeable number of papers exploring their interactions, but very few practical implementations. We present WemblAI, a toolbox that aims at collecting algorithms from these fields using a common framework. WemblAI is still largely a work in progress.

Analog-to-Information Converter (AIC) is the physical implementation of Compressed Sensing (CS) systems to digitize signals directly from the analog domain. Due to non-idealities of components AIC hardware needs a calibration step to adjust parameters before its utilization. In this paper, we consider a theoretical linear model of an AIC architecture composed by parallel channels that suffers from synchronization problems between the input signal and the internal signals used to perform the measurement. Using a radar inspired technique we propose a method to estimate the delay between these signals. Obtained results show the accuracy of the proposed method and its potential to be used in AIC calibration techniques.

Quantum computing's value proposition of an exponential speedup in computing power for certain applications has propelled a vast array of research across the globe. While several different physical implementations of device level qubits are being investigated, semiconductor spin qubits have many similarities to scaled transistors. In this article, we discuss the device/integration of full 300mm based spin qubit devices. This includes the development of (i) a 28 Si epitaxial module ecosystem for growing isotopically pure substrates with among the best Hall mobility at these oxide thicknesses, (ii) a custom 300mm qubit testchip and integration/device line, and (iii) a novel dual nested gate integration process for creating quantum dots.

This work gives a detailed description of the automation process carried out in the expanded equipment in the casing inspection line of the Tenaris Company. This automated process was carried out since in the production process there were defects in the termination of the pipeline which caused delays for the process. The control design was made with software and sequential programming methods RSLogix and programmable logic controller (PLC.) Compact Logix; (1769-L32E CompactLogix 5332E controller.) For which, a communication network was created that incorporates new elements for the control of powers and actions by means of elements of field (sensors). In the automation process, software and components were integrated which allow a better and optimum performance of the industrial process for the reduction of times in productive cycles. Before the automation of the process, 378,000 pieces were threaded per year and after the automation process, 425,250 were threaded. Showing a significant improvement in the automation process which results in improvements to the process in terms of time reduction and resources optimization.

Analog-to-information converters (AIC) are physical implementations of Compressed Sensing that have been proposed to overcome the technological limitations of the analog-to-digital converters (ADC) in terms of bandwidth and quantity of data produced after conversion. The AIC hardware suffers from non-idealities of components and subsystems, which reduces the quality of the measured signal reconstruction. Such effects can be compensated by calibration that normally have been implemented in the signal recovery methods. In this paper, we analyze a calibration method for AIC that takes into account only the measurements produced by the AIC. Results show that the hardware calibration improves the signal reconstruction with regard to signal-to-noise and distortion ratio (SINAD), independent of the reconstruction algorithm.

This work describes the simulation and data-analysis frameworks developed in support of the SENSR R&D program. Simulations are used to evaluate and illustrate the potential operational impact of relaxing cost-driving radar requirements and/or of using different multi-function concepts of operations.

Meteorological information is important for decision making when related to natural phenomena, research in meteorology and climatology, etc. Considering that the cost of implementing monitoring stations can be high, studies have been carried out using low-cost equipment for meteorological monitoring. However, the information is unreliable because it does not follow a regulated standard and rises the uncertainty of how accurate the measurements are. This article studies the implementation of the Bosch BME280 integrated environmental unit which includes referential meteorological monitoring sensors for the estimation of temperature, relative humidity, and barometric pressure; used in mobile applications within the internet of things (IoT). The measurements produced by the Bosch unit are compared with those delivered by an automatic meteorological station (AWS) to determine the accuracy and reliability of the generated data. The outcomes show that the records present a constant phase shift, which, when determined and corrected, results in a similarity between measurements greater than 95%.

Analog to Information Converters (AIC) acquires a discrete representation of a signal from the analog domain in Compressed Sensing. One of the crucial point in the AIC design is the configuration of the measurement matrix. Depending of its characteristics, this matrix can degrade the AIC performance. In this paper we analyze the influence of the primitive polynomial choice to configure a Linear Feedback Shift Register, that generates the measurement matrix values, in the performance of a configurable AIC. It is shown that, depending of the chosen primitive polynomial with a certain degree, the performance of the AIC can be completely degraded.

Currently, Mexico City is facing a growing concern about the production and treatment of urban waste (RSU of its acronym in Spanish), also known as municipal solid waste (MSW), due to the lack of long-term planning and because many landfills (RESA in Spanish) have exceeded their capacity. In addition, finding new sites for landfilling waste is difficult because many studies and analyses from specialists are required. Landfill sites should comply with technical requirements that guarantee environmental protection and public health. These requirements are established in the Mexican environmental standard NOM-083-SEMARNAT- 2003. Additionally, it is desirable that new landfills have the necessary infrastructure to capture and use the biogas generated over the following year because there is an international trend in waste management called the Waste to Energy (WtE) approach in which biogas can be used for electricity or heat generation. This research proposes a methodology to make a system that performs geographic analyses to show potential landfill locations, and the calculation of potential biogas generation to support the municipalities in building a landfill that has the necessary infrastructure to capture, treat and take advantage of the biogas produced by the MSW. The result is a system that displays maps showing potential landfill locations (according to NOM-083- SEMARNAT-2003), through semantic processing, showing the results in a Web system and a mobile application (Android app).

Technological advances have allowed us to have increasingly portable and efficient glucose measuring systems in the blood, but it has been shown that problems of loss of information are present in the measuring sensors, these failures usually are associated with activities performed by the patient such as exercise, climbing stairs, among others. These failures where the sensor position is affected may cause wrong measurement and in this case the loss of information may occur, as described above we propose a work in which we use the patient sensor to take continuous time samples of the glucose level in the blood of the patient, Those samples are the inputs for the neural network (this neural network will emulate the intelligent sensor) which takes those values and relate them with the past values of glucose and with the insulin dosing. Once the failure of the sensor is detected the prediction mode of the neural network is activated in order to minimize or reduce the loss of information because the neural network will take the place of the sensor temporally.

A key aspect for the teaching of the photovoltaic technology is that the student perform experimental practices of measure the characteristic Current-Voltage (I-V) under natural sunlight of a photovoltaic cell, module or generator and, later, being able to extrapolate the extracted results into Standard Test Conditions (STC). This paper presents a software tool (gotoSTC) to facilitate the acquisition of this knowledge and support the learning process of our students. gotoSTC allows processing experimental data from I-V curves and applies some of the accepted methods by the scientific community. The program has two functional options: on the first one, the characteristic parameters of one curve will be obtained from its I-V curve and STC extrapolation methods are applied to it; in the second option, a set of I-V curves of the same module are necessary to obtain the characteristic parameters and then applies the extrapolation methods. Graphical representations of the data are showed in order to present some of the existing relations between the parameters characterizing the device behavior.

Lab-on-a-disc allows a large variety of microfluidic assays, in research, and lately also in industry. Standard lab discs are purely passive devices with off disc read-out, therefore efforts in electrically accessing the disc have been implemented with rather complicated setups via slip rings or generators. Here, we present a universal platform that not only transfers wireless energy to the disc, but has the ability to control variety of sensors and actuators as well, permitting on-disc experiments results to be transferred concurrently to the end-user.

To lower interconnect signal delay, the industry continues to work on the integration of low-k interlayer dielectrics (ILD). Porosity is often added to further reduce dielectric constant and significantly impact capacitance. These porous dielectric films are most commonly deposited via Chemical Vapor Deposition (CVD), delivering a random order to the pore structure. Disordered films suffer from a reduction in mechanical properties, which ultimately limits the maximum porosity obtained due to film collapse. Control of porosity, pore size distribution and pore geometry is needed to extend the porosity beyond conventional percolation thresholds. Here we present the case study of a periodic mesoporous organosilica (PMO) film. We optimize solution processing to obtain an ordered film and characterize the film porosity, pore size distribution, geometry and mechanical properties. The PMO film is tested in both a dual damascene and replacement back end integration flow.

We present the design and fabrication of a double-spiral coil used as the inductive element of a two-layer coupled resonator array for wireless power transfer applications. The waveguide presents an in-plane coupling coefficient of 0.92 and LC resonators with Q-factors of 97 at 13.56 MHz. Wireless monitoring of the power supply voltage enabled live modulation of the terminating impedance in the array. With load modulation and the low attenuation of our device we demonstrate how to power-up a receiver device with a system efficiency of nearly 60% anywhere over the 30 cm length of our resonating array.

At present the increase in motor vehicles, has resulted in the clothing used for road safety are deficient, increasing the risk of accidents for pedestrians. In this context the agents responsible for directing the traffic, as well as cyclists and motorcyclists requiring safety equipment that allows reduce the risk to which they are exposed mainly during the hours of reduced visibility, inasmuch as the reflective vests used today need external light, and are indicative only items that are not allowed to exercise any control over mobility. For the above in this article a development proposal vest containing mobile computing to allow correct display and easily understood signals emitted mobility for them arises, as well as by using GPS and GSM devices displayed on Google maps user location.

This paper presents a methodology for assessing the vulnerability of power and energy systems and components to weapons effects, accidental explosions, and attacks by terrorists, saboteurs, and vandals. The functioning of these systems depends on such devices and equipment as fuel tanks, pumps, transformers, control panels, insulators, wiring and piping, and generators. Damage mechanisms for components such as these and the means to determine their occurrence for specific components and threats are described herein. The damage mechanisms considered include those associated with airblast, shock, cratering, ballistic impact, penetration, and fire threats, although the methodology could be extended to include a broader spectrum of threats including cyber, electromagnetic, hostile vehicle etc. To facilitate assessment of the sorts of infrastructure elements that are used by power generation and energy transmission utilities, a damage function for individual components is introduced. For example, the damage function can provide a means to estimate the level of damage incurred by various equipment as a function of their distance from the point of detonation, and the size and type of the explosive used. This function may be incorporated as part of an assessment code, or it may also be used as a standalone means to estimate damage for a specific utility component, such as described in [2].

This article an evolutionary robot is implemented with the aim to stand upright and level as possible. Evolutionary Robots are characterised by performing automated tasks trying to reach an objective function, which is the key to good performance. The evolution of the system is made possible by a genetic algorithm, which based on natural biological evolution process, achieved through several generations a possible solution. The evolutionary robot was physically implemented with sensors and actuators, also the genetic algorithm was embedded in a microcontroller.

The aim of the present research and development work, is to show how to implement a embedded Generation of Fuzzy Rules.

In an effort to investigate scattering characteristics of debris particles in tornadoes, a numerical polarimetric radar emulator was developed. Regions of negative differential reflectivity have commonly been observed but are still yet to be explained physically. There are hypotheses that suggest common debris alignment and/or dominant scattering from objects with high radar-cross-section (RCS) values, but they are extremely challenging to verify due to the danger within tornadoes. It is, however, possible to numerically construct the scenes through representative simulation to verify the plausible causes. This serves as our primary motivation to develop the radar emulator. The novel aspects of this work are the realistic trajectory derivation, which is based on physical air-drag model, and the representative diversity of RCS contributions from each debris particle, developed through a realistic polarimetric RCS modeling and anechoic chamber measurements.

Planar capacitors can quickly test material properties of metals and dielectrics for interconnects. A sidewall capacitor device is used to evaluate metal thin-film barriers. Etch stop planar capacitors in turn can test multi-layer etch stops, exposing differences between leaky and good etch stop films. Fillable planar capacitors are also fabricated and results presented for that class of fill materials.

A polarimetric radar time-series emulator that produces both meteorological and non-meteorological radar echoes was developed. There are two main constituents in the radar emulator: a set of quasi-randomly populated tracers to emulate meteorological echoes and another set of point scatterers to emulate individual tornadic debris objects. Based on previous work to emulate meteorological radar echoes, the concept was expanded to the new framework. Two key innovations of the framework are the physically consistent trajectories of individual debris objects and realistic polarimetric radar cross section modeling of the debris targets.

In the present article was implemented a maximum sensibility neural network in a reconfigurable logical electronic structure (cell) in which different basic logical functions and combinational logic circuits as comparators, multiplexers and encoders are obtained. This neural network has advantages like easy implementation and a quick learning based on manipulation of the information in place of a gradient algorithm. The reconfiguration of the cell it will realized by modifying one specific input that will change de logical function.

Using EMG signals as control signals has been a widely accepted option in the last decades. Using a wide array of techniques, EMG signals can be used in a variety of practical ways, from prostethics to exoesqueletons, however a concrete functional relationship between EMG signals and the dynamic and kinematic aspects of the upper limbs has not been established. Nowadays, almost every device that uses EMG signals uses them for classification purposes. In this work, we employ Fourier analysis in conjunction with other signal processing tools to treat the EMG signal, the treated signal is then used as an input of an artificial neural network in order to establish a simplified functional relationship between EMG and the upper limbs. We also employed other traditional signal processing methods for comparison purposes.

In this paper, a maximum sensibility neural network is proposed to make an online learning system of a inverse controller of a plant. This neural network is trained to learn the response of the plant to different random inputs. Once the network is trained, it can be used to control the plant to a desired output.