Kinematic analysis of a novel 2-d.o.f. orientation device

This paper presents the development of a new parallel robot designed for helping with bone milling surgeries. The robot is a small modular wrist with 2 active degrees of freedom, and it is proposed to be used as an orientation device located at the end of a robotic arm designed for bone milling processes. A generic kinematic geometry is proposed for this device. This first article shows the developments on the workspace optimization and the analysis of the force field required to complete a reconstruction of the inferior jawbone. The singularities of the mechanism are analyzed, and the actuator selection is justified with the torque requirements and the study of the force space. The results obtained by the simulations allow building a first prototype using linear motors. Bone milling experiment video is shown as additional material.

Unified access to media metadata on the web: Towards interoperability using a core vocabulary.

The goal of the W3C's Media Annotation Working Group (MAWG) is to promote interoperability between multimedia metadata formats on the Web. As experienced by everybody, audiovisual data is omnipresent on today's Web. However, different interaction interfaces and especially diverse metadata formats prevent unified search, access, and navigation. MAWG has addressed this issue by developing an interlingua ontology and an associated API. This article discusses the rationale and core concepts of the ontology and API for media resources. The specifications developed by MAWG enable interoperable contextualized and semantic annotation and search, independent of the source metadata format, and connecting multimedia data to the Linked Data cloud. Some demonstrators of such applications are also presented in this article.

Suitability of artificial neural networks for designing LoC circuits

he simulation of complex LoC (Lab-on-a-Chip) devices is a process that requires solving computationally expensive partial differential equations. An interesting alternative uses artificial neural networks for creating computationally feasible models based on MOR techniques. This paper proposes an approach that uses artificial neural networks for designing LoC components considering the artificial neural network topology as an isomorphism of the LoC device topology. The parameters of the trained neural networks are based on equations for modeling microfluidic circuits, analogous to electronic circuits. The neural networks have been trained to behave like AND, OR, Inverter gates. The parameters of the trained neural networks represent the features of LoC devices that behave as the aforementioned gates. This would mean that LoC devices universally compute.

Probabilistic reasoning with a bayesian DNA device based on strand displacement

We present a computing model based on the DNA strand displacement technique which performs Bayesian inference. The model will take single stranded DNA as input data, representing the presence or absence of a specific molecular signal (evidence). The program logic encodes the prior probability of a disease and the conditional probability of a signal given the disease playing with a set of different DNA complexes and their ratios. When the input and program molecules interact, they release a different pair of single stranded DNA species whose relative proportion represents the application of Bayes? Law: the conditional probability of the disease given the signal. The models presented in this paper can empower the application of probabilistic reasoning in genetic diagnosis in vitro.

2D tunable graded index prism beam steering device based on nematic liquid crystals

Liquid crystal devices are being used in many non-display applications in order to construct small devices controlled by low voltage electronics without mechanical components. In this work, we present a novel liquid crystal device for laser beam steering. In this device the orientation of the liquid crystal molecules can be controlled. A change in the liquid crystal orientation results in a change of the refractive index. When a laser beam passes through the device, the beam will be deviated (Fig.1) and the device works a prism. The main difference between this device and a prism is that in the device the orientation profile of the liquid crystal molecules can be modified so that the laser beam can be deviated a required angle: the device is tuneable.

In situ control of Si(100) and Ge(100) surface preparation for the heteroepitaxy of III-V solar cell architectures

Si(100) and Ge(100) substrates essential for subsequent III-V integration were studied in the hydrogen ambient of a metalorganic vapor phase epitaxy reactor. Reflectance anisotropy spectroscopy (RAS) enabled us to distinguish characteristic configurations of vicinal Si(100) in situ: covered with oxide, cleaned by thermal removing in H2, and terminated with monohydrides when cooling in H2 ambient. RAS measurements during cooling in H2 ambient after the oxide removal process revealed a transition from the clean to the monohydride terminated Si(100) surface dependent on process temperature. For vicinal Ge(100) we observed a characteristic RA spectrum after annealing and cooling in H2 ambient. According to results from X-ray photo electron spectroscopy and Fourier-transform infrared spectroscopy the spectrum corresponds to the monohydride terminated Ge(100) surface.

Calibration process on the study of new antenna array architectures for space communications

This paper introduces novel calibration processes applied to antenna arrays with new architectures and technologies designed to improve the performance of traditional earth stations for satellite communications due to the increasing requirement of data capacity during last decades. Besides, the Radiation Group from the Technical University of Madrid has been working on the development of new antenna arrays based on novel architecture and technologies along many projects as a solution for the ground segment in the early future. Nowadays, the calibration process is an interesting and cutting edge research field in a period of expansion with a lot of work to do for calibration in transmission and also for reception of these novel antennas under development.

New control architecturebased on PXI for a 3-finger haptic device applied to virtual manipulation

To perform advanced manipulation of remote environments such as grasping, more than one finger is required implying higher requirements for the control architecture. This paper presents the design and control of a modular 3-finger haptic device that can be used to interact with virtual scenarios or to teleoperate dexterous remote hands. In a modular haptic device, each module allows the interaction with a scenario by using a single finger; hence, multi-finger interaction can be achieved by adding more modules. Control requirements for a multifinger haptic device are analyzed and new hardware/software architecture for these kinds of devices is proposed. The software architecture described in this paper is distributed and the different modules communicate to allow the remote manipulation. Moreover, an application in which this haptic device is used to interact with a virtual scenario is shown.

Wearable soft robotic device for post-stroke shoulder rehabilitation: identifying misalignments

Stroke is the leading cause of long-term disability in the United States, affecting over 795,000 people annually. In order to regain motor function of the upper body, patients are usually treated by regular sessions with a dedicated physical therapist. A cost-effective wearable upper body orthotics system that can be used at home to empower both the patients and physical therapists is described. The system is composed of a thin, compliant, lightweight, cost-effective soft orthotic device with an integrated cable actuation system that is worn over the upper body, an embedded limb position sensing system, an electric actuator package and controller. The proposed device is robust to misalignments that may occur during actuation of the compliant brace or when putting on the system. Through simulations and experimental evaluation, it was demonstrated i) that the soft orthotic cable-driven shoulder brace can be successfully actuated without the production of off-axis torques in the presence of misalignments and ii) that the proposed model can identify linear and angular misalignments online.

Survey of architectures and optimizations for wide bandwidth envelope amplifier

In the last years, RF power amplifiers are taking advantage of the switched dc-dc converters to use them in several architectures that may improve the efficiency of the amplifier, keeping a good linearity. The use of linearization techniques such as Envelope Elimination and Restoration(EER) and Envelope Tracking (ET) requires a very fast dc-dc power converter to provide variable voltage supply to the power amplifier but theoretically the efficiency can be much higher than using the classical amplifiers belonging to classes A, B or AB. The purpose of this paper is to analyze the state of the art of the power converters used as envelope amplifiers in this application. The power topologies will be explored and several important parameters such as efficiency, bandwidth will be discussed.

Power management techniques in an FPGA-Based WSN node for high performance application

In this work, the power management techniques implemented in a high-performance node for Wireless Sensor Networks (WSN) based on a RAM-based FPGA are presented. This new node custom architecture is intended for high-end WSN applications that include complex sensor management like video cameras, high compute demanding tasks such as image encoding or robust encryption, and/or higher data bandwidth needs. In the case of these complex processing tasks, yet maintaining low power design requirements, it can be shown that the combination of different techniques such as extensive HW algorithm mapping, smart management of power islands to selectively switch on and off components, smart and low-energy partial reconfiguration, an adequate set of save energy modes and wake up options, all combined, may yield energy results that may compete and improve energy usage of typical low power microcontrollers used in many WSN node architectures. Actually, results show that higher complexity tasks are in favor of HW based platforms, while the flexibility achieved by dynamic and partial reconfiguration techniques could be comparable to SW based solutions.

Functional validation of MB-OFDM system using HW-in the loop

Functional validation of complex digital systems is a hard and critical task in the design flow. In particular, when dealing with communication systems, like Multiband Orthogonal Frequency Division Multiplexing Ultra Wideband (MB-OFDM UWB), the design decisions taken during the process have to be validated at different levels in an easy way. In this work, a unified algorithm-architecture-circuit co-design environment for this type of systems, to be implemented in FPGA, is presented. The main objective is to find an efficient methodology for designing a configurable optimized MB-OFDM UWB system by using as few efforts as possible in verification stage, so as to speed up the development period. Although this efficient design methodology is tested and considered to be suitable for almost all types of complex FPGA designs, we propose a solution where both the circuit and the communication channel are tested at different levels (algorithmic, RTL, hardware device) using a common testbench.

Algoritmo para la clasificación de nubes de puntos LiDAR en entornos urbanos: discriminación entre vegetación y edificaciones.

Los sistemas de registro aerotransportados que utilizan láser (LiDAR) se están convirtiendo en el principal instrumental para la recogida de la información cartográfica debido, principalmente, a la gran densidad de puntos, precisión alcanzada y rapidez en la obtención de modelos digitales. Sin embargo, sería importante disponer de algoritmos que permitan filtrar la información, seleccionando aquellos puntos medidos en zonas deseadas. Cuando se miden zonas urbanas, los elementos más importantes son las edificaciones. Por ello, se propone un nuevo algoritmo que permite clasificar y diferenciar aquellos puntos medidos sobre edificios, extrayendo, como resultado, el límite exterior que definen, de tal forma que se podría calcular la zona edificada. Abstarct: Registration systems using airborne laser (LIDAR) are becoming the main device for the collection of cartographic information, mainly due to the high density of points, accuracy and rate achieved in obtaining digital models. However, it would be important to have algorithms that filter the information by selecting those points measured in targeted areas. When measuring urban areas, buildings are the most important objects. Therefore, a new algorithm is proposed to classify those measured points on buildings and to compute their outer boundaries, so the built up area can be computed.

Linewidth influence in photonics logic device

Photonics logic devices are currently finding applications in most of the fields where optical signals are employed. These areas range from optical communications to optical computing, covering as well as other applications in photonics sensing and metrology. Most of the proposed configurations with photonics logic devices are based on semiconductor laser structures with “on/off” behaviors, operating in an optical amplifier configuration. They are able to offer non-linear gain or bistable operation, being these properties the basis for their applications in these fields. Moreover, their large number of potential affecting parameters onto their behavior offers the possibility to choose the best solution for each case.

Optimisation of algorithms to compute information theoretic indexes

Analysis of big amount of data is a field with many years of research. It is centred in getting significant values, to make it easier to understand and interpret data. Being the analysis of interdependence between time series an important field of research, mainly as a result of advances in the characterization of dynamical systems from the signals they produce. In the medicine sphere, it is easy to find many researches that try to understand the brain behaviour, its operation mode and its internal connections. The human brain comprises approximately 1011 neurons, each of which makes about 103 synaptic connections. This huge number of connections between individual processing elements provides the fundamental substrate for neuronal ensembles to become transiently synchronized or functionally connected. A similar complex network configuration and dynamics can also be found at the macroscopic scales of systems neuroscience and brain imaging. The emergence of dynamically coupled cell assemblies represents the neurophysiological substrate for cognitive function such as perception, learning, thinking. Understanding the complex network organization of the brain on the basis of neuroimaging data represents one of the most impervious challenges for systems neuroscience. Brain connectivity is an elusive concept that refers to diferent interrelated aspects of brain organization: structural, functional connectivity (FC) and efective connectivity (EC). Structural connectivity refers to a network of physical connections linking sets of neurons, it is the anatomical structur of brain networks. However, FC refers to the statistical dependence between the signals stemming from two distinct units within a nervous system, while EC refers to the causal interactions between them. This research opens the door to try to resolve diseases related with the brain, like Parkinson’s disease, senile dementia, mild cognitive impairment, etc. One of the most important project associated with Alzheimer’s research and other diseases are enclosed in the European project called Blue Brain. The center for Biomedical Technology (CTB) of Universidad Politecnica de Madrid (UPM) forms part of the project. The CTB researches have developed a magnetoencephalography (MEG) data processing tool that allow to visualise and analyse data in an intuitive way. This tool receives the name of HERMES, and it is presented in this document. Analysis of big amount of data is a field with many years of research. It is centred in getting significant values, to make it easier to understand and interpret data. Being the analysis of interdependence between time series an important field of research, mainly as a result of advances in the characterization of dynamical systems from the signals they produce. In the medicine sphere, it is easy to find many researches that try to understand the brain behaviour, its operation mode and its internal connections. The human brain comprises approximately 1011 neurons, each of which makes about 103 synaptic connections. This huge number of connections between individual processing elements provides the fundamental substrate for neuronal ensembles to become transiently synchronized or functionally connected. A similar complex network configuration and dynamics can also be found at the macroscopic scales of systems neuroscience and brain imaging. The emergence of dynamically coupled cell assemblies represents the neurophysiological substrate for cognitive function such as perception, learning, thinking. Understanding the complex network organization of the brain on the basis of neuroimaging data represents one of the most impervious challenges for systems neuroscience. Brain connectivity is an elusive concept that refers to diferent interrelated aspects of brain organization: structural, functional connectivity (FC) and efective connectivity (EC). Structural connectivity refers to a network of physical connections linking sets of neurons, it is the anatomical structur of brain networks. However, FC refers to the statistical dependence between the signals stemming from two distinct units within a nervous system, while EC refers to the causal interactions between them. This research opens the door to try to resolve diseases related with the brain, like Parkinson’s disease, senile dementia, mild cognitive impairment, etc. One of the most important project associated with Alzheimer’s research and other diseases are enclosed in the European project called Blue Brain. The center for Biomedical Technology (CTB) of Universidad Politecnica de Madrid (UPM) forms part of the project. The CTB researches have developed a magnetoencephalography (MEG) data processing tool that allow to visualise and analyse data in an intuitive way. This tool receives the name of HERMES, and it is presented in this document.