Enhancing skills in solving open-ended problems using game-based exercises

Some requirements for engineering programmes, such as an ability to use the techniques, skills and modern engineering tools necessary for engineering practice, as well as an understanding of professional and ethical responsibility or an ability to communicate effectively, need new activities designed for measuring students’ progress. Negotiations take place continuously at any stage of a project and, so, the ability of engineers and managers to effectively carry out a negotiation is crucial for the success or failure of projects and businesses. Since it involves communication between individuals motivated to come together in an agreement for mutual benefit, it can be used to enhance these personal abilities. The main objective of this study was to evaluate the adequacy of mixing playing sessions and theory to maximise the students’ strategic vision in combination with negotiating skills. Results show that the combination of playing with theoretical training teaches students to strategise through analysis and discussion of alternatives. The outcome is then more optimised.

Automatic Understanding of ATC Speech: Study of Prospectives and Field Experiments for Several Controller Positions

Although there has been a lot of interest in recognizing and understanding air traffic control (ATC) speech, none of the published works have obtained detailed field data results. We have developed a system able to identify the language spoken and recognize and understand sentences in both Spanish and English. We also present field results for several in-tower controller positions. To the best of our knowledge, this is the first time that field ATC speech (not simulated) is captured, processed, and analyzed. The use of stochastic grammars allows variations in the standard phraseology that appear in field data. The robust understanding algorithm developed has 95% concept accuracy from ATC text input. It also allows changes in the presentation order of the concepts and the correction of errors created by the speech recognition engine improving it by 17% and 25%, respectively, absolute in the percentage of fully correctly understood sentences for English and Spanish in relation to the percentages of fully correctly recognized sentences. The analysis of errors due to the spontaneity of the speech and its comparison to read speech is also carried out. A 96% word accuracy for read speech is reduced to 86% word accuracy for field ATC data for Spanish for the "clearances" task confirming that field data is needed to estimate the performance of a system. A literature review and a critical discussion on the possibilities of speech recognition and understanding technology applied to ATC speech are also given.

Pond head level control in a run-of-river hydro power plant using fuzzy controller

The run-of-river hydro power plant usually have low or nil water storage capacity, and therefore an adequate control strategy is required to keep the water level constant in pond. This paper presents a novel technique based on TSK fuzzy controller to maintain the pond head constant. The performance is investigated over a wide range of hill curve of hydro turbine. The results are compared with PI controller as discussed in [1].

ITER fast plant system controller prototype based on PXIe platform

The ITER CODAC design identifies slow and fast plant system controllers (PSC). The gast OSCs are based on embedded technologies, permit sampling rates greater than 1 KHz, meet stringent real-time requirements, and will be devoted to data acquisition tasks and control purposes. CIEMAT and UPM have implemented a prototype of a fast PSC based on commercial off-the-shelf (COTS) technologies with PXI hardware and software based on EPICS

ITER Fast Plant System Controller Prototype Based on Commercial PXI Platform

The ITER CODAC design identifies slow and fast plant system controllers (PSC). The gast OSCs are based on embedded technologies, permit sampling rates greater than 1 KHz, meet stringent real-time requirements, and will be devoted to data acquisition tasks and control purposes. CIEMAT and UPM have implemented a prototype of a fast PSC based on commercial off-the-shelf (COTS) technologies with PXI hardware and software based on EPICS

Game Theory Models for Multi-Robot Patrolling of Infraestructures

Abstract This work is focused on the problem of performing multi‐robot patrolling for infrastructure security applications in order to protect a known environment at critical facilities. Thus, given a set of robots and a set of points of interest, the patrolling task consists of constantly visiting these points at irregular time intervals for security purposes. Current existing solutions for these types of applications are predictable and inflexible. Moreover, most of the previous centralized and deterministic solutions and only few efforts have been made to integrate dynamic methods. Therefore, the development of new dynamic and decentralized collaborative approaches in order to solve the aforementioned problem by implementing learning models from Game Theory. The model selected in this work that includes belief‐based and reinforcement models as special cases is called Experience‐Weighted Attraction. The problem has been defined using concepts of Graph Theory to represent the environment in order to work with such Game Theory techniques. Finally, the proposed methods have been evaluated experimentally by using a patrolling simulator. The results obtained have been compared with previous available

Crowdsourcing malaria parasite quantification: an online game for analyzing images of infected thick blood smears

Background: There are 600,000 new malaria cases daily worldwide. The gold standard for estimating the parasite burden and the corresponding severity of the disease consists in manually counting the number of parasites in blood smears through a microscope, a process that can take more than 20 minutes of an expert microscopist’s time. Objective: This research tests the feasibility of a crowdsourced approach to malaria image analysis. In particular, we investigated whether anonymous volunteers with no prior experience would be able to count malaria parasites in digitized images of thick blood smears by playing a Web-based game. Methods: The experimental system consisted of a Web-based game where online volunteers were tasked with detecting parasites in digitized blood sample images coupled with a decision algorithm that combined the analyses from several players to produce an improved collective detection outcome. Data were collected through the MalariaSpot website. Random images of thick blood films containing Plasmodium falciparum at medium to low parasitemias, acquired by conventional optical microscopy, were presented to players. In the game, players had to find and tag as many parasites as possible in 1 minute. In the event that players found all the parasites present in the image, they were presented with a new image. In order to combine the choices of different players into a single crowd decision, we implemented an image processing pipeline and a quorum algorithm that judged a parasite tagged when a group of players agreed on its position. Results: Over 1 month, anonymous players from 95 countries played more than 12,000 games and generated a database of more than 270,000 clicks on the test images. Results revealed that combining 22 games from nonexpert players achieved a parasite counting accuracy higher than 99%. This performance could be obtained also by combining 13 games from players trained for 1 minute. Exhaustive computations measured the parasite counting accuracy for all players as a function of the number of games considered and the experience of the players. In addition, we propose a mathematical equation that accurately models the collective parasite counting performance. Conclusions: This research validates the online gaming approach for crowdsourced counting of malaria parasites in images of thick blood films. The findings support the conclusion that nonexperts are able to rapidly learn how to identify the typical features of malaria parasites in digitized thick blood samples and that combining the analyses of several users provides similar parasite counting accuracy rates as those of expert microscopists. This experiment illustrates the potential of the crowdsourced gaming approach for performing routine malaria parasite quantification, and more generally for solving biomedical image analysis problems, with future potential for telediagnosis related to global health challenges.

Neural network controller for active demand side management with PV energy in the residential sector

In this paper, we describe the development of a control system for Demand-Side Management in the residential sector with Distributed Generation. The electrical system under study incorporates local PV energy generation, an electricity storage system, connection to the grid and a home automation system. The distributed control system is composed of two modules: a scheduler and a coordinator, both implemented with neural networks. The control system enhances the local energy performance, scheduling the tasks demanded by the user and maximizing the use of local generation.

Cross-entropy optimization for scaling factors of a fuzzy controller: a see-and-avoid approach for unmanned aerial systems

The Cross-Entropy (CE) is an efficient method for the estimation of rare-event probabilities and combinatorial optimization. This work presents a novel approach of the CE for optimization of a Soft-Computing controller. A Fuzzy controller was designed to command an unmanned aerial system (UAS) for avoiding collision task. The only sensor used to accomplish this task was a forward camera. The CE is used to reach a near-optimal controller by modifying the scaling factors of the controller inputs. The optimization was realized using the ROS-Gazebo simulation system. In order to evaluate the optimization a big amount of tests were carried out with a real quadcopter.

Data Fusion based on Game Theory for Speaker Diarization

A novel algorithm based on bimatrix game theory has been developed to improve the accuracy and reliability of a speaker diarization system. This algorithm fuses the output data of two open-source speaker diarization programs, LIUM and SHoUT, taking advantage of the best properties of each one. The performance of this new system has been tested by means of audio streams from several movies. From preliminary results on fragments of five movies, improvements of 63% in false alarms and missed speech mistakes have been achieved with respect to LIUM and SHoUT systems working alone. Moreover, we also improve in a 20% the number of recognized speakers, getting close to the real number of speakers in the audio stream

Quadcopter see and avoid using a fuzzy controller

Unmanned Aerial Vehicles (UAVs) industry is a fast growing sector. Nowadays, the market offers numerous possibilities for off-the-shelf UAVs such as quadrotors or fixed-wings. Until UAVs demonstrate advance capabilities such as autonomous collision avoidance they will be segregated and restricted to flight in controlled environments. This work presents a visual fuzzy servoing system for obstacle avoidance using UAVs. To accomplish this task we used the visual information from the front camera. Images are processed off-board and the result send to the Fuzzy Logic controller which then send commands to modify the orientation of the aircraft. Results from flight test are presented with a commercial off-the-shelf platform.

Genetic fuzzy-based steering wheel controller using a mass-produced car

Intelligent Transportation Systems (ITS) cover a broad range of methods and technologies that provide answers to many problems of transportation. Unmanned control of the steering wheel is one of the most important challenges facing researchers in this area. This paper presents a method to adjust automatically a fuzzy controller to manage the steering wheel of a mass-produced vehicle to reproduce the steering of a human driver. To this end, information is recorded about the car's state while being driven by human drivers and used to obtain, via genetic algorithms, appropriate fuzzy controllers that can drive the car in the way that humans do. These controllers have satisfy two main objectives: to reproduce the human behavior, and to provide smooth actions to ensure comfortable driving. Finally, the results of automated driving on a test circuit are presented, showing both good route tracking (similar to the performance obtained by persons in the same task) and smooth driving.

Interactividad programada en el Game Engine de Blender

Con este proyecto se ha desarrollado una guía introductoria a uno de los aspectos más complejos y especializados de Blender, que es el control de su motor de videojuegos mediante programas escritos en Python. Está orientado a lectores que tienen un conocimiento amplio sobre el manejo de Blender, su interfaz y el funcionamiento de sus diferentes elementos, así como una mínima experiencia en cuanto a programación. Se ha organizado en una parte descriptiva, centrada en el lenguaje Python y en las bases de su uso para programar el motor de videojuegos (Game Engine) de Blender, y otra de práctica guiada, que constituye la mayoría del proyecto, donde se estudian de manera progresiva ejemplos concretos de uso del mismo. En la parte descriptiva se ha tratado tanto el funcionamiento más básico del lenguaje Python, especialmente las características que difieren de otros lenguajes de programación tradicionales, como su relación con Blender en particular, explicando las diferentes partes de la API de Blender para Python, y las posibles estrategias de uso. La parte práctica guiada, dado que esta interacción entre Blender y Python ofrece un rango de posibilidades muy amplio, se ha centrado en tres áreas concretas que han sido investigadas en profundidad: el control del objeto protagonista, de la cámara y la implementación de un mapa de orientación. Todas ellas se han centrado en torno a un ejemplo común, que consiste en un videojuego muy básico, y que, gracias a los ficheros de Blender que acompañan a esta memoria, sirve para apoyar las explicaciones y poder probar su efecto directamente. Por una parte, estos tres aspectos prácticos se han explicado exhaustivamente, y se han llevado hasta un nivel relativamente alto. Asimismo se han intentado minimizar las dependencias, tanto entre ellos como con la escena que se ha usado como ejemplo, de manera que sea sencillo usar los programas generados en otras aplicaciones. Por otra, la mayoría de los problemas que ha sido necesario resolver durante el desarrollo no son específicos de ninguna de las tres áreas, sino que son de carácter general, por lo que sus explicaciones podrán usarse al afrontar otras situaciones. ABSTRACT. This Thesis consists of an introductory guide to one of the most complex and specific parts of Blender, which is the control of its game engine by means of programs coded in Python. The dissertation is orientated towards readers who have a good knowledge of Blender, its interface and how its different systems work, as well as basic programming skills. The document is composed of two main sections, the first one containing a description of Python’s basics and its usage within Blender, and the second consisting of three practical examples of interaction between them, guided and explained step by step. On the first section, the fundamentals of Python have been covered in the first place, focusing on the characteristics that distinguish it from other programming languages. Then, Blender’s API for Python has also been introduced, explaining its different parts and the ways it can be used in. Since the interaction between Blender and Python offers a wide range of possibilities, the practical section has been centered on three particular areas. Each one of the following sections has been deeply covered: how to control the main character object, how to control the camera, and how to implement and control a mini-map. Furthermore, a demonstrative videogame has been generated for the reader to be able to directly test the effect of what is explained in each section. On the one hand, these three practical topics have been thoroughly explained, starting from the basis and gradually taking them to a relatively advanced level. The dependences among them, or between them and the demonstrative videogame, have been minimised so that the scripts or ideas can be easily used within other applications. On the other hand, most of the problems that have been addressed are not exclusively related to these areas, but will most likely appear in different situations, thus enlarging the field in which this Thesis can be used.

Game o la voluntad de romper el hielo

Creo que uno de los misterios más extraños que existen en nuestro país es el de las posibles causas por las que una especie de maleficio ha ido marcando el camino de la Microelectrónica. Pocos sectores de la tecnología han recibido un apoyo más constante y desde más entornos que ella y, al mismo tiempo, en pocos también se han obtenido menos frutos

Artificial pancreas using a personalized rule-based controller achieves overnight normoglycemia in patients with type 1 diabetes

Objective: This study assessed the efficacy of a closed-loop (CL) system consisting of a predictive rule-based algorithm (pRBA) on achieving nocturnal and postprandial normoglycemia in patients with type 1 diabetes mellitus (T1DM). The algorithm is personalized for each patient’s data using two different strategies to control nocturnal and postprandial periods. Research Design and Methods: We performed a randomized crossover clinical study in which 10 T1DM patients treated with continuous subcutaneous insulin infusion (CSII) spent two nonconsecutive nights in the research facility: one with their usual CSII pattern (open-loop [OL]) and one controlled by the pRBA (CL). The CL period lasted from 10 p.m. to 10 a.m., including overnight control, and control of breakfast. Venous samples for blood glucose (BG) measurement were collected every 20 min. Results: Time spent in normoglycemia (BG, 3.9–8.0 mmol/L) during the nocturnal period (12 a.m.–8 a.m.), expressed as median (interquartile range), increased from 66.6% (8.3–75%) with OL to 95.8% (73–100%) using the CL algorithm (P<0.05). Median time in hypoglycemia (BG, <3.9 mmol/L) was reduced from 4.2% (0–21%) in the OL night to 0.0% (0.0–0.0%) in the CL night (P<0.05). Nine hypoglycemic events (<3.9 mmol/L) were recorded with OL compared with one using CL. The postprandial glycemic excursion was not lower when the CL system was used in comparison with conventional preprandial bolus: time in target (3.9–10.0 mmol/L) 58.3% (29.1–87.5%) versus 50.0% (50–100%). Conclusions: A highly precise personalized pRBA obtains nocturnal normoglycemia, without significant hypoglycemia, in T1DM patients. There appears to be no clear benefit of CL over prandial bolus on the postprandial glycemia