Exploration of RVC applications using an ARM multicore processor = Exploración de aplicaciones RVC empleando un procesador ARM multinúcleo

Single core capabilities have reached their maximum clock speed; new multicore architectures provide an alternative way to tackle this issue instead. The design of decoding applications running on top of these multicore platforms and their optimization to exploit all system computational power is crucial to obtain best results. Since the development at the integration level of printed circuit boards are increasingly difficult to optimize due to physical constraints and the inherent increase in power consumption, development of multiprocessor architectures is becoming the new Holy Grail. In this sense, it is crucial to develop applications that can run on the new multi-core architectures and find out distributions to maximize the potential use of the system. Today most of commercial electronic devices, available in the market, are composed of embedded systems. These devices incorporate recently multi-core processors. Task management onto multiple core/processors is not a trivial issue, and a good task/actor scheduling can yield to significant improvements in terms of efficiency gains and also processor power consumption. Scheduling of data flows between the actors that implement the applications aims to harness multi-core architectures to more types of applications, with an explicit expression of parallelism into the application. On the other hand, the recent development of the MPEG Reconfigurable Video Coding (RVC) standard allows the reconfiguration of the video decoders. RVC is a flexible standard compatible with MPEG developed codecs, making it the ideal tool to integrate into the new multimedia terminals to decode video sequences. With the new versions of the Open RVC-CAL Compiler (Orcc), a static mapping of the actors that implement the functionality of the application can be done once the application executable has been generated. This static mapping must be done for each of the different cores available on the working platform. It has been chosen an embedded system with a processor with two ARMv7 cores. This platform allows us to obtain the desired tests, get as much improvement results from the execution on a single core, and contrast both with a PC-based multiprocessor system. Las posibilidades ofrecidas por el aumento de la velocidad de la frecuencia de reloj de sistemas de un solo procesador están siendo agotadas. Las nuevas arquitecturas multiprocesador proporcionan una vía de desarrollo alternativa en este sentido. El diseño y optimización de aplicaciones de descodificación de video que se ejecuten sobre las nuevas arquitecturas permiten un mejor aprovechamiento y favorecen la obtención de mayores rendimientos. Hoy en día muchos de los dispositivos comerciales que se están lanzando al mercado están integrados por sistemas embebidos, que recientemente están basados en arquitecturas multinúcleo. El manejo de las tareas de ejecución sobre este tipo de arquitecturas no es una tarea trivial, y una buena planificación de los actores que implementan las funcionalidades puede proporcionar importantes mejoras en términos de eficiencia en el uso de la capacidad de los procesadores y, por ende, del consumo de energía. Por otro lado, el reciente desarrollo del estándar de Codificación de Video Reconfigurable (RVC), permite la reconfiguración de los descodificadores de video. RVC es un estándar flexible y compatible con anteriores codecs desarrollados por MPEG. Esto hace de RVC el estándar ideal para ser incorporado en los nuevos terminales multimedia que se están comercializando. Con el desarrollo de las nuevas versiones del compilador específico para el desarrollo de lenguaje RVC-CAL (Orcc), en el que se basa MPEG RVC, el mapeo estático, para entornos basados en multiprocesador, de los actores que integran un descodificador es posible. Se ha elegido un sistema embebido con un procesador con dos núcleos ARMv7. Esta plataforma nos permitirá llevar a cabo las pruebas de verificación y contraste de los conceptos estudiados en este trabajo, en el sentido del desarrollo de descodificadores de video basados en MPEG RVC y del estudio de la planificación y mapeo estático de los mismos.

A Description Framework and Event-Driven Architecture for the Semantic Web and Semantic Grid

In this introductory chapter we put in context and give a brief outline of the work that we thoroughly present in the rest of the dissertation. We consider this work divided in two main parts. The first part is the Firenze Framework, a knowledge level description framework rich enough to express the semantics required for describing both semantic Web services and semantic Grid services. We start by defining what the Semantic Grid is and its relation with the Semantic Web; and the possibility of their convergence since both initiatives have become mainly service-oriented. We also introduce the main motivators of the creation of this framework, one is to provide a valid description framework that works at knowledge level; the other to provide a description framework that takes into account the characteristics of Grid services in order to be able to describe them properly. The other part of the dissertation is devoted to Vega, an event-driven architecture that, by means of proposed knowledge level description framework, is able to achieve high scale provisioning of knowledge-intensive services. In this introductory chapter we portrait the anatomy of a generic event-driven architecture, and we briefly enumerate their main characteristics, which are the reason that make them our choice.

Conceptual framework for the design, implementation and validation of psychomotor skills’ assessment systems in minimally invasive surgery

Las técnicas de cirugía de mínima invasión (CMI) se están consolidando hoy en día como alternativa a la cirugía tradicional, debido a sus numerosos beneficios para los pacientes. Este cambio de paradigma implica que los cirujanos deben aprender una serie de habilidades distintas de aquellas requeridas en cirugía abierta. El entrenamiento y evaluación de estas habilidades se ha convertido en una de las mayores preocupaciones en los programas de formación de cirujanos, debido en gran parte a la presión de una sociedad que exige cirujanos bien preparados y una reducción en el número de errores médicos. Por tanto, se está prestando especial atención a la definición de nuevos programas que permitan el entrenamiento y la evaluación de las habilidades psicomotoras en entornos seguros antes de que los nuevos cirujanos puedan operar sobre pacientes reales. Para tal fin, hospitales y centros de formación están gradualmente incorporando instalaciones de entrenamiento donde los residentes puedan practicar y aprender sin riesgos. Es cada vez más común que estos laboratorios dispongan de simuladores virtuales o simuladores físicos capaces de registrar los movimientos del instrumental de cada residente. Estos simuladores ofrecen una gran variedad de tareas de entrenamiento y evaluación, así como la posibilidad de obtener información objetiva de los ejercicios. Los diferentes estudios de validación llevados a cabo dan muestra de su utilidad; pese a todo, los niveles de evidencia presentados son en muchas ocasiones insuficientes. Lo que es más importante, no existe un consenso claro a la hora de definir qué métricas son más útiles para caracterizar la pericia quirúrgica. El objetivo de esta tesis doctoral es diseñar y validar un marco de trabajo conceptual para la definición y validación de entornos para la evaluación de habilidades en CMI, en base a un modelo en tres fases: pedagógica (tareas y métricas a emplear), tecnológica (tecnologías de adquisición de métricas) y analítica (interpretación de la competencia en base a las métricas). Para tal fin, se describe la implementación práctica de un entorno basado en (1) un sistema de seguimiento de instrumental fundamentado en el análisis del vídeo laparoscópico; y (2) la determinación de la pericia en base a métricas de movimiento del instrumental. Para la fase pedagógica se diseñó e implementó un conjunto de tareas para la evaluación de habilidades psicomotoras básicas, así como una serie de métricas de movimiento. La validación de construcción llevada a cabo sobre ellas mostró buenos resultados para tiempo, camino recorrido, profundidad, velocidad media, aceleración media, economía de área y economía de volumen. Adicionalmente, los resultados obtenidos en la validación de apariencia fueron en general positivos en todos los grupos considerados (noveles, residentes, expertos). Para la fase tecnológica, se introdujo el EVA Tracking System, una solución para el seguimiento del instrumental quirúrgico basado en el análisis del vídeo endoscópico. La precisión del sistema se evaluó a 16,33ppRMS para el seguimiento 2D de la herramienta en la imagen; y a 13mmRMS para el seguimiento espacial de la misma. La validación de construcción con una de las tareas de evaluación mostró buenos resultados para tiempo, camino recorrido, profundidad, velocidad media, aceleración media, economía de área y economía de volumen. La validación concurrente con el TrEndo® Tracking System por su parte presentó valores altos de correlación para 8 de las 9 métricas analizadas. Finalmente, para la fase analítica se comparó el comportamiento de tres clasificadores supervisados a la hora de determinar automáticamente la pericia quirúrgica en base a la información de movimiento del instrumental, basados en aproximaciones lineales (análisis lineal discriminante, LDA), no lineales (máquinas de soporte vectorial, SVM) y difusas (sistemas adaptativos de inferencia neurodifusa, ANFIS). Los resultados muestran que en media SVM presenta un comportamiento ligeramente superior: 78,2% frente a los 71% y 71,7% obtenidos por ANFIS y LDA respectivamente. Sin embargo las diferencias estadísticas medidas entre los tres no fueron demostradas significativas. En general, esta tesis doctoral corrobora las hipótesis de investigación postuladas relativas a la definición de sistemas de evaluación de habilidades para cirugía de mínima invasión, a la utilidad del análisis de vídeo como fuente de información y a la importancia de la información de movimiento de instrumental a la hora de caracterizar la pericia quirúrgica. Basándose en estos cimientos, se han de abrir nuevos campos de investigación que contribuyan a la definición de programas de formación estructurados y objetivos, que puedan garantizar la acreditación de cirujanos sobradamente preparados y promocionen la seguridad del paciente en el quirófano. Abstract Minimally invasive surgery (MIS) techniques have become a standard in many surgical sub-specialties, due to their many benefits for patients. However, this shift in paradigm implies that surgeons must acquire a complete different set of skills than those normally attributed to open surgery. Training and assessment of these skills has become a major concern in surgical learning programmes, especially considering the social demand for better-prepared professionals and for the decrease of medical errors. Therefore, much effort is being put in the definition of structured MIS learning programmes, where practice with real patients in the operating room (OR) can be delayed until the resident can attest for a minimum level of psychomotor competence. To this end, skills’ laboratory settings are being introduced in hospitals and training centres where residents may practice and be assessed on their psychomotor skills. Technological advances in the field of tracking technologies and virtual reality (VR) have enabled the creation of new learning systems such as VR simulators or enhanced box trainers. These systems offer a wide range of tasks, as well as the capability of registering objective data on the trainees’ performance. Validation studies give proof of their usefulness; however, levels of evidence reported are in many cases low. More importantly, there is still no clear consensus on topics such as the optimal metrics that must be used to assess competence, the validity of VR simulation, the portability of tracking technologies into real surgeries (for advanced assessment) or the degree to which the skills measured and obtained in laboratory environments transfer to the OR. The purpose of this PhD is to design and validate a conceptual framework for the definition and validation of MIS assessment environments based on a three-pillared model defining three main stages: pedagogical (tasks and metrics to employ), technological (metric acquisition technologies) and analytical (interpretation of competence based on metrics). To this end, a practical implementation of the framework is presented, focused on (1) a video-based tracking system and (2) the determination of surgical competence based on the laparoscopic instruments’ motionrelated data. The pedagogical stage’s results led to the design and implementation of a set of basic tasks for MIS psychomotor skills’ assessment, as well as the definition of motion analysis parameters (MAPs) to measure performance on said tasks. Validation yielded good construct results for parameters such as time, path length, depth, average speed, average acceleration, economy of area and economy of volume. Additionally, face validation results showed positive acceptance on behalf of the experts, residents and novices. For the technological stage the EVA Tracking System is introduced. EVA provides a solution for tracking laparoscopic instruments from the analysis of the monoscopic video image. Accuracy tests for the system are presented, which yielded an average RMSE of 16.33pp for 2D tracking of the instrument on the image and of 13mm for 3D spatial tracking. A validation experiment was conducted using one of the tasks and the most relevant MAPs. Construct validation showed significant differences for time, path length, depth, average speed, average acceleration, economy of area and economy of volume; especially between novices and residents/experts. More importantly, concurrent validation with the TrEndo® Tracking System presented high correlation values (>0.7) for 8 of the 9 MAPs proposed. Finally, the analytical stage allowed comparing the performance of three different supervised classification strategies in the determination of surgical competence based on motion-related information. The three classifiers were based on linear (linear discriminant analysis, LDA), non-linear (support vector machines, SVM) and fuzzy (adaptive neuro fuzzy inference systems, ANFIS) approaches. Results for SVM show slightly better performance than the other two classifiers: on average, accuracy for LDA, SVM and ANFIS was of 71.7%, 78.2% and 71% respectively. However, when confronted, no statistical significance was found between any of the three. Overall, this PhD corroborates the investigated research hypotheses regarding the definition of MIS assessment systems, the use of endoscopic video analysis as the main source of information and the relevance of motion analysis in the determination of surgical competence. New research fields in the training and assessment of MIS surgeons can be proposed based on these foundations, in order to contribute to the definition of structured and objective learning programmes that guarantee the accreditation of well-prepared professionals and the promotion of patient safety in the OR.

An Introductory Course on Constraint Logic Programming

The purpose of this document is to serve as the printed material for the seminar "An Introductory Course on Constraint Logic Programming". The intended audience of this seminar are industrial programmers with a degree in Computer Science but little previous experience with constraint programming. The seminar itself has been field tested, prior to the writing of this document, with a group of the application programmers of Esprit project P23182, "VOCAL", aimed at developing an application in scheduling of field maintenance tasks in the context of an electric utility company. The contents of this paper follow essentially the flow of the seminar slides. However, there are some differences. These differences stem from our perception from the experience of teaching the seminar, that the technical aspects are the ones which need more attention and clearer explanations in the written version. Thus, this document includes more examples than those in the slides, more exercises (and the solutions to them), as well as four additional programming projects, with which we hope the reader will obtain a clearer view of the process of development and tuning of programs using CLP. On the other hand, several parts of the seminar have been taken out: those related with the account of fields and applications in which C(L)P is useful, and the enumerations of C(L)P tools available. We feel that the slides are clear enough, and that for more information on available tools, the interested reader will find more up-to-date information by browsing the Web or asking the vendors directly. More details in this direction will actually boil down to summarizing a user manual, which is not the aim of this document.

Response threshold models, stochastic learning automata and ant colony optimization-based decentralized self-coordination algorithms for heterogeneous multi-tasks distribution in multi-robot systems

In recent decades, there has been an increasing interest in systems comprised of several autonomous mobile robots, and as a result, there has been a substantial amount of development in the eld of Articial Intelligence, especially in Robotics. There are several studies in the literature by some researchers from the scientic community that focus on the creation of intelligent machines and devices capable to imitate the functions and movements of living beings. Multi-Robot Systems (MRS) can often deal with tasks that are dicult, if not impossible, to be accomplished by a single robot. In the context of MRS, one of the main challenges is the need to control, coordinate and synchronize the operation of multiple robots to perform a specic task. This requires the development of new strategies and methods which allow us to obtain the desired system behavior in a formal and concise way. This PhD thesis aims to study the coordination of multi-robot systems, in particular, addresses the problem of the distribution of heterogeneous multi-tasks. The main interest in these systems is to understand how from simple rules inspired by the division of labor in social insects, a group of robots can perform tasks in an organized and coordinated way. We are mainly interested on truly distributed or decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all tasks are optimally distributed. In general, to perform the multi-tasks distribution among a team of robots, they have to synchronize their actions and exchange information. Under this approach we can speak of multi-tasks selection instead of multi-tasks assignment, which means, that the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation ix of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. In addition, it is very interesting the evaluation of the results in function in each approach, comparing the results obtained by the introducing noise in the number of pending loads, with the purpose of simulate the robot's error in estimating the real number of pending tasks. The main contribution of this thesis can be found in the approach based on self-organization and division of labor in social insects. An experimental scenario for the coordination problem among multiple robots, the robustness of the approaches and the generation of dynamic tasks have been presented and discussed. The particular issues studied are: Threshold models: It presents the experiments conducted to test the response threshold model with the objective to analyze the system performance index, for the problem of the distribution of heterogeneous multitasks in multi-robot systems; also has been introduced additive noise in the number of pending loads and has been generated dynamic tasks over time. Learning automata methods: It describes the experiments to test the learning automata-based probabilistic algorithms. The approach was tested to evaluate the system performance index with additive noise and with dynamic tasks generation for the same problem of the distribution of heterogeneous multi-tasks in multi-robot systems. Ant colony optimization: The goal of the experiments presented is to test the ant colony optimization-based deterministic algorithms, to achieve the distribution of heterogeneous multi-tasks in multi-robot systems. In the experiments performed, the system performance index is evaluated by introducing additive noise and dynamic tasks generation over time.

A review of the potential of renewable energy sources for the State of Jammu and Kashmir (India)

The future economic development trajectory for India is likely to result in rapid and accelerated growth in energy demand, with expected shortages. Many of its current policies and strategies are aimed at the improvement and possible maximization of energy production from the renewable sector. It is also clear that while energy-conservation and energy-efficiency can make an important contribution in the national energy strategy, renewable energies will be essential to the solution and are likely to play an increasingly important role for the growth of grid power, providing energy access, reducing consumption of fossil fuels, and helping India pursue its low carbon progressive pathway. However, most of the states in India, like the northernmost State of Jammu and Kashmir (J&K), have experienced an energy crisis over a sustained period of time. As India intends to be one of the emerging powers of the 21st century, it has to embark upon with these pressing issues in a more sustainable manner and accordingly initiate various renewable energy projects within these states. This paper will provide a broad-spectrum view about the energy situation within J&K and will highlight the current policies along with future strategies for the optimal utilization of renewable energy resources.

An integral model for natural regeneration of Pinus pinea L. in the Northern Plateau (Spain) = Modelo integral de regeneración natural para Pinus pinea L. en la Meseta Norte (España)

Natural regeneration is an ecological key-process that makes plant persistence possible and, consequently, it constitutes an essential element of sustainable forest management. In this respect, natural regeneration in even-aged stands of Pinus pinea L. located in the Spanish Northern Plateau has not always been successfully achieved despite over a century of pine nut-based management. As a result, natural regeneration has recently become a major concern for forest managers when we are living a moment of rationalization of investment in silviculture. The present dissertation is addressed to provide answers to forest managers on this topic through the development of an integral regeneration multistage model for P. pinea stands in the region. From this model, recommendations for natural regeneration-based silviculture can be derived under present and future climate scenarios. Also, the model structure makes it possible to detect the likely bottlenecks affecting the process. The integral model consists of five submodels corresponding to each of the subprocesses linking the stages involved in natural regeneration (seed production, seed dispersal, seed germination, seed predation and seedling survival). The outputs of the submodels represent the transitional probabilities between these stages as a function of climatic and stand variables, which in turn are representative of the ecological factors driving regeneration. At subprocess level, the findings of this dissertation should be interpreted as follows. The scheduling of the shelterwood system currently conducted over low density stands leads to situations of dispersal limitation since the initial stages of the regeneration period. Concerning predation, predator activity appears to be only limited by the occurrence of severe summer droughts and masting events, the summer resulting in a favourable period for seed survival. Out of this time interval, predators were found to almost totally deplete seed crops. Given that P. pinea dissemination occurs in summer (i.e. the safe period against predation), the likelihood of a seed to not be destroyed is conditional to germination occurrence prior to the intensification of predator activity. However, the optimal conditions for germination seldom take place, restraining emergence to few days during the fall. Thus, the window to reach the seedling stage is narrow. In addition, the seedling survival submodel predicts extremely high seedling mortality rates and therefore only some individuals from large cohorts will be able to persist. These facts, along with the strong climate-mediated masting habit exhibited by P. pinea, reveal that viii the overall probability of establishment is low. Given this background, current management –low final stand densities resulting from intense thinning and strict felling schedules– conditions the occurrence of enough favourable events to achieve natural regeneration during the current rotation time. Stochastic simulation and optimisation computed through the integral model confirm this circumstance, suggesting that more flexible and progressive regeneration fellings should be conducted. From an ecological standpoint, these results inform a reproductive strategy leading to uneven-aged stand structures, in full accordance with the medium shade-tolerant behaviour of the species. As a final remark, stochastic simulations performed under a climate-change scenario show that regeneration in the species will not be strongly hampered in the future. This resilient behaviour highlights the fundamental ecological role played by P. pinea in demanding areas where other tree species fail to persist.

Learning curves of basic laparoscopic psychomotor skills in SINERGIA VR simulator

Purpose: Surgical simulators are currently essential within any laparoscopic training program because they provide a low-stakes, reproducible and reliable environment to acquire basic skills. The purpose of this study is to determine the training learning curve based on different metrics corresponding to five tasks included in SINERGIA laparoscopic virtual reality simulator. Methods: Thirty medical students without surgical experience participated in the study. Five tasks of SINERGIA were included: Coordination, Navigation, Navigation and touch, Accurate grasping and Coordinated pulling. Each participant was trained in SINERGIA. This training consisted of eight sessions (R1–R8) of the five mentioned tasks and was carried out in two consecutive days with four sessions per day. A statistical analysis was made, and the results of R1, R4 and R8 were pair-wise compared with Wilcoxon signed-rank test. Significance is considered at P value <0.005. Results: In total, 84.38% of the metrics provided by SINERGIA and included in this study show significant differences when comparing R1 and R8. Metrics are mostly improved in the first session of training (75.00% when R1 and R4 are compared vs. 37.50% when R4 and R8 are compared). In tasks Coordination and Navigation and touch, all metrics are improved. On the other hand, Navigation just improves 60% of the analyzed metrics. Most learning curves show an improvement with better results in the fulfillment of the different tasks. Conclusions: Learning curves of metrics that assess the basic psychomotor laparoscopic skills acquired in SINERGIA virtual reality simulator show a faster learning rate during the first part of the training. Nevertheless, eight repetitions of the tasks are not enough to acquire all psychomotor skills that can be trained in SINERGIA. Therefore, and based on these results together with previous works, SINERGIA could be used as training tool with a properly designed training program.

Adaptive neuro-fuzzy inference systems (ANFIS) for supervised classification of competence in MIS based on psychomotor skills

INTRODUCTION: Objective assessment of motor skills has become an important challenge in minimally invasive surgery (MIS) training.Currently, there is no gold standard defining and determining the residents' surgical competence.To aid in the decision process, we analyze the validity of a supervised classifier to determine the degree of MIS competence based on assessment of psychomotor skills METHODOLOGY: The ANFIS is trained to classify performance in a box trainer peg transfer task performed by two groups (expert/non expert). There were 42 participants included in the study: the non-expert group consisted of 16 medical students and 8 residents (< 10 MIS procedures performed), whereas the expert group consisted of 14 residents (> 10 MIS procedures performed) and 4 experienced surgeons. Instrument movements were captured by means of the Endoscopic Video Analysis (EVA) tracking system. Nine motion analysis parameters (MAPs) were analyzed, including time, path length, depth, average speed, average acceleration, economy of area, economy of volume, idle time and motion smoothness. Data reduction was performed by means of principal component analysis, and then used to train the ANFIS net. Performance was measured by leave one out cross validation. RESULTS: The ANFIS presented an accuracy of 80.95%, where 13 experts and 21 non-experts were correctly classified. Total root mean square error was 0.88, while the area under the classifiers' ROC curve (AUC) was measured at 0.81. DISCUSSION: We have shown the usefulness of ANFIS for classification of MIS competence in a simple box trainer exercise. The main advantage of using ANFIS resides in its continuous output, which allows fine discrimination of surgical competence. There are, however, challenges that must be taken into account when considering use of ANFIS (e.g. training time, architecture modeling). Despite this, we have shown discriminative power of ANFIS for a low-difficulty box trainer task, regardless of the individual significances between MAPs. Future studies are required to confirm the findings, inclusion of new tasks, conditions and sample population.

Response threshold models and stochastic learning automata for self-coordination of heterogeneous multi-task distribution in multi-robot systems.

This paper focuses on the general problem of coordinating multiple robots. More specifically, it addresses the self-selection of heterogeneous specialized tasks by autonomous robots. In this paper we focus on a specifically distributed or decentralized approach as we are particularly interested in a decentralized solution where the robots themselves autonomously and in an individual manner, are responsible for selecting a particular task so that all the existing tasks are optimally distributed and executed. In this regard, we have established an experimental scenario to solve the corresponding multi-task distribution problem and we propose a solution using two different approaches by applying Response Threshold Models as well as Learning Automata-based probabilistic algorithms. We have evaluated the robustness of the algorithms, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.

Scheduling Ontology Engineering Projects Using gOntt

In order to manage properly ontology development projects in complex settings and to apply correctly the NeOn Methodology, it is crucial to have knowledge of the entire ontology development life cycle before starting the development projects. The ontology project plan and scheduling helps the ontology development team to have this knowledge and to monitor the project execution. To facilitate the planning and scheduling of ontology development projects, the NeOn Toolkit plugin called gOntt has been developed. gOntt is a tool that supports the scheduling of ontology network development projects and helps to execute them. In addition, prescriptive methodological guidelines for scheduling ontology development projects using gOntt are provided.

Supervised classification of minimally invasive surgery psychomotor competence based on instruments motion analysis

Background Objective assessment of psychomotor skills has become an important challenge in the training of minimally invasive surgical (MIS) techniques. Currently, no gold standard defining surgical competence exists for classifying residents according to their surgical skills. Supervised classification has been proposed as a means for objectively establishing competence thresholds in psychomotor skills evaluation. This report presents a study comparing three classification methods for establishing their validity in a set of tasks for basic skills’ assessment. Methods Linear discriminant analysis (LDA), support vector machines (SVM), and adaptive neuro-fuzzy inference systems (ANFIS) were used. A total of 42 participants, divided into an experienced group (4 expert surgeons and 14 residents with >10 laparoscopic surgeries performed) and a nonexperienced group (16 students and 8 residents with <10 laparoscopic surgeries performed), performed three box trainer tasks validated for assessment of MIS psychomotor skills. Instrument movements were captured using the TrEndo tracking system, and nine motion analysis parameters (MAPs) were analyzed. The performance of the classifiers was measured by leave-one-out cross-validation using the scores obtained by the participants. Results The mean accuracy performances of the classifiers were 71 % (LDA), 78.2 % (SVM), and 71.7 % (ANFIS). No statistically significant differences in the performance were identified between the classifiers. Conclusions The three proposed classifiers showed good performance in the discrimination of skills, especially when information from all MAPs and tasks combined were considered. A correlation between the surgeons’ previous experience and their execution of the tasks could be ascertained from results. However, misclassifications across all the classifiers could imply the existence of other factors influencing psychomotor competence.

Decision-Making Mechanism to Organize the Agenda of a Guide-Robot

One of the major challenges in evolutionary robotics is constituted by the need of the robot being able to make decisions on its own, in accordance with the multiple tasks programmed, optimizing its timings and power. In this paper, we present a new automatic decision making mechanism for a robot guide that allows the robot to make the best choice in order to reach its aims, performing its tasks in an optimal way. The election of which is the best alternative is based on a series of criteria and restrictions of the tasks to perform. The software developed in the project has been verified on the tour-guide robot Urbano. The most important aspect of this proposal is that the design uses learning as the means to optimize the quality in the decision making. The modeling of the quality index of the best choice to perform is made using fuzzy logic and it represents the beliefs of the robot, which continue to evolve in order to match the "external reality”. This fuzzy system is used to select the most appropriate set of tasks to perform during the day. With this tool, the tour guide-robot prepares its agenda daily, which satisfies the objectives and restrictions, and it identifies the best task to perform at each moment. This work is part of the ARABOT project of the Intelligent Control Research Group at the Universidad Politécnica de Madrid to create "awareness" in a robot guide.

Optimization of multidimensional cross-section tables for few-group core calculations

Multigroup diffusion codes for three dimensional LWR core analysis use as input data pre-generated homogenized few group cross sections and discontinuity factors for certain combinations of state variables, such as temperatures or densities. The simplest way of compiling those data are tabulated libraries, where a grid covering the domain of state variables is defined and the homogenized cross sections are computed at the grid points. Then, during the core calculation, an interpolation algorithm is used to compute the cross sections from the table values. Since interpolation errors depend on the distance between the grid points, a determined refinement of the mesh is required to reach a target accuracy, which could lead to large data storage volume and a large number of lattice transport calculations. In this paper, a simple and effective procedure to optimize the distribution of grid points for tabulated libraries is presented. Optimality is considered in the sense of building a non-uniform point distribution with the minimum number of grid points for each state variable satisfying a given target accuracy in k-effective. The procedure consists of determining the sensitivity coefficients of k-effective to cross sections using perturbation theory; and estimating the interpolation errors committed with different mesh steps for each state variable. These results allow evaluating the influence of interpolation errors of each cross section on k-effective for any combination of state variables, and estimating the optimal distance between grid points.

Testing of Android testing tools: development of a benchmark for the evaluation

With the ever growing trend of smart phones and tablets, Android is becoming more and more popular everyday. With more than one billion active users i to date, Android is the leading technology in smart phone arena. In addition to that, Android also runs on Android TV, Android smart watches and cars. Therefore, in recent years, Android applications have become one of the major development sectors in software industry. As of mid 2013, the number of published applications on Google Play had exceeded one million and the cumulative number of downloads was more than 50 billionii. A 2013 survey also revealed that 71% of the mobile application developers work on developing Android applicationsiii. Considering this size of Android applications, it is quite evident that people rely on these applications on a daily basis for the completion of simple tasks like keeping track of weather to rather complex tasks like managing one’s bank accounts. Hence, like every other kind of code, Android code also needs to be verified in order to work properly and achieve a certain confidence level. Because of the gigantic size of the number of applications, it becomes really hard to manually test Android applications specially when it has to be verified for various versions of the OS and also, various device configurations such as different screen sizes and different hardware availability. Hence, recently there has been a lot of work on developing different testing methods for Android applications in Computer Science fraternity. The model of Android attracts researchers because of its open source nature. It makes the whole research model more streamlined when the code for both, application and the platform are readily available to analyze. And hence, there has been a great deal of research in testing and static analysis of Android applications. A great deal of this research has been focused on the input test generation for Android applications. Hence, there are a several testing tools available now, which focus on automatic generation of test cases for Android applications. These tools differ with one another on the basis of their strategies and heuristics used for this generation of test cases. But there is still very little work done on the comparison of these testing tools and the strategies they use. Recently, some research work has been carried outiv in this regard that compared the performance of various available tools with respect to their respective code coverage, fault detection, ability to work on multiple platforms and their ease of use. It was done, by running these tools on a total of 60 real world Android applications. The results of this research showed that although effective, these strategies being used by the tools, also face limitations and hence, have room for improvement. The purpose of this thesis is to extend this research into a more specific and attribute-­‐ oriented way. Attributes refer to the tasks that can be completed using the Android platform. It can be anything ranging from a basic system call for receiving an SMS to more complex tasks like sending the user to another application from the current one. The idea is to develop a benchmark for Android testing tools, which is based on the performance related to these attributes. This will allow the comparison of these tools with respect to these attributes. For example, if there is an application that plays some audio file, will the testing tool be able to generate a test input that will warrant the execution of this audio file? Using multiple applications using different attributes, it can be visualized that which testing tool is more useful for which kinds of attributes. In this thesis, it was decided that 9 attributes covering the basic nature of tasks, will be targeted for the assessment of three testing tools. Later this can be done for much more attributes to compare even more testing tools. The aim of this work is to show that this approach is effective and can be used on a much larger scale. One of the flagship features of this work, which also differentiates it with the previous work, is that the applications used, are all specially made for this research. The reason for doing that is to analyze just that specific attribute in isolation, which the application is focused on, and not allow the tool to get bottlenecked by something trivial, which is not the main attribute under testing. This means 9 applications, each focused on one specific attribute. The main contributions of this thesis are: A summary of the three existing testing tools and their respective techniques for automatic test input generation of Android Applications. • A detailed study of the usage of these testing tools using the 9 applications specially designed and developed for this study. • The analysis of the obtained results of the study carried out. And a comparison of the performance of the selected tools.