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In the last 10 years, reliability of the transmission lines in Mexico has been affected due to the remotion of redundant Steel members from electric power transmission towers. An alternative to reduce non-technical losses in transmission line towers is by replacing redundant steel members by composite members. However, when these composites are drilled for installation, using the traditional screw method, their mechanical properties diminish drastically due to the discontinuity and reduction of the net material area. This paper proposes a connection system formed by a nodular cast iron connector attached to a composite member by using a structural adhesive, for further installation replacing main and secondary steel members of transmission lines towers. The substitution of metallic redundant members instead of composite members will result in a great economic benefit for Utilities that supply electricity, since it is expected that composite members will not be attractive to theft.

Complex pathological brain patterns generally are found in neurodegenerative diseases which can be correlated with different clinical onsets of a particular pathology. Currently, an objective method that aids to determine such signs, in terms of global and local changes, is not available in clinical practice and the whole interpretation is dependent on the radiologist's skills. In this paper, we propose a fully automatic method that analyzes the brain structure under a multidimensional frame and highlights relevant brain patterns. An association of such patterns with the disease is herein evaluated in three classification tasks, involving probable Alzheimer's disease (AD) patients, Mild Cognitive Impairment (MCI) patients and normal subjects (NC). A set of 75 brain MR images from NC subjects (25), MCI (25) and probable AD (25) patients, split into training (15 subjects) and testing (60 subjects) sets, was used to evaluate the performance of the proposed approach. Preliminary results show that the proposed method reaches a maximum classification accuracy of 80% when discriminating AD patients from NC, of 75% for classification of MCI patients from NC.

Currently, updating Land Used Land Cover map databases requires a costly manual process. One of the main obstacles in trying to automate this process is the loss of spectral information in shadow areas of the aerial or high resolution satellite images. In this paper, we present a method to automate the detection of shadows in aerial images by using an nDSM built with LIDAR technology and metadata from space images. Additionally, we show that it is possible to recover the class information for these shadow regions by including this process of shadow detection in an object-oriented perspective.

Most cartographic work is made extracting features from aerial or space images. A first step in this work is segmenting the images in regions that represent, as close as possible, cartographic entities (e.g., roads, buildings, vegetation). Region-Growing segmentation is implemented in a multispectral image using an open source programming language. This segmentation method is analyzed for land used and land cover applications, and it is compared with classification-based segmentation, known as Fuzzy K-Means. Both algorithms, Region Growing and Fuzzy K-Means, are run in an aerial image with four spectral bands (red, green, blue, and near infrared). Depending on the scale, the values of the parameters of the algorithms can yield an under segmentation or over segmentation results. Advantages and disadvantages of both segmentation methods are provided.

This paper examines the effect of using different Digital Terrain Models (DTMs) for different return periods and different configurations of cross-sections in the simulation of flooding. The hydraulic behavior is simulated for a one-dimensional model of part of the Henares river located in Madrid, Spain, with two maximum flood return periods (5 and 100 years), using two sets of cross sections (50 and 100 meters apart). The influence of three DTMs—raw LiDAR, edited LiDAR, and DTM from photogrammetry—was studied with respect to the final height of the water layer for these different floods. The edited LiDAR gave the best results, and it is proposed for use in a pseudo DTM

Article of the IEEE Education Engineering Conference (EDUCON). Keywords: educational courses, electronic engineering education, telecommunication engineering education, electronics curriculum, project based learning activities, project-oriented integral curriculum, telecommunication engineer degree, university degree structure, Bologna process This paper describes the Electronics curriculum in the Telecommunication Engineer degree at Rey Juan Carlos University (URJC) in Spain. Telecommunication Engineering started in the 2003-2004 academic year. In these years, all the electronic courses have been set up with a main practical orientation and with Project Based Learning (PBL) activities, both compulsory and voluntary. Once these courses have been successfully implemented we have reoriented some of the practical activities to be more interlaced. In this sense, projects involving students of different courses have been developed, as well as projects involving students from different years. All these activities fit in the principles promulgated by the Declaration of Bologna, which results in the actual updating of the university degree structure in Spain. Tecnología Electrónica

We present firstly the design and construction of a unmanned aerial vehicle (UAV) in delta configuration in order to accomplish certain tasks and requirements which are explained along this document. After the construction, we present the dynamic model of the UAV developed, based on its structural characteristics and obtained through the Newton-Euler method. The final dynamic model is restricted to longitudinal motion in order to simplify the system, allowing this fact to propound a suitable control law to control the pitch angle of the UAV. Finally we discuss the use of a set of components embedded into this aircraft, whose main tasks are to make it fly, giving the option of manual and autonomous flight, and to acquire a whole range of physical measurements produced by the UAV's motion, such as its acceleration, angular rate, attitude, velocity and position.

In this work, a device for generating automated olfactory stimuli in functional magnetic resonance imaging (fMRI) studies is described. The novel issues of our design are: synchronization between the acquisition and the olfactory task, automated control of experimental parameters (odorants sequences, frequency, time and concentration of stimuli). Finally, we present the preliminary results obtained on a General Electric 3 Tesla MRI scanner belong to The Alzheimer Project of the Fundacion Reina Sofia.

We propose a new quality metric for range images that is based on the multi-scale Structural Similarity (MS-SSIM) Index. The new metric operates in a manner to SSIM but allows for special handling of missing data. We demonstrate its utility by reevaluating the set of stereo algorithms evaluated in the Middlebury Stereo Vision Page http://vision.middlebury.edu/stereo/. The new algorithm which we term Range SSIM (R-SSIM) Index possesses features that make it an attractive choice for assessing the quality of range images.

We present the design and construction of a UAV in delta configuration in order to accomplish certain tasks and requirements which are explained along this document. We presented too, after the construction, the dynamic model of the UAV developed, based on its structural characteristics and obtained through the Newton-Euler method. The final dynamic model is restricted to longitudinal motion to simplify the system and make it easy to simulate using a control law which will lead the system to the stabilization of the aircraft along the longitudinal axis. These simulations of the dynamic model included the control law were added to demonstrate the capability of the aircraft designed to be longitudinally stabilized.

Outliers are important features that are of special interest to image analysts in their work. The objective of this paper is to show how several statistical techniques with different theoretical foundations can be successfully applied complementarily to detect anomalies in hyperspectral imageries. The methodology is shown in airborne hyperspectral imagery with 60 bands. The visual inspection of the last components of Principal Component Analysis (PCA), together with the analysis of the images provided by the Reed and Xiaoli Yu algorithm and projection pursuit algorithm, allows clear extraction of most of the anomalies, such as synthetic material of tennis court floors or metallic roofs of buildings. A discussion and comparison of the three methods is given.

Article of the IEEE International Conference on Microelectronic Systems Education, 2009. MSE '09. Keywords: FPGAs, VHDL digital electronic circuit design, electronic teaching ,project-based learning methodology In this paper we present our experience in teaching digital electronic circuit and system design with FPGAs using VHDL. The course follows a project based learning methodology, in which the students learn how to design digital circuits and systems in a practical way. During the course, students design electronic circuits of incremental complexity. At the end of the course they are capable of implementing relatively complex projects, such as image processing systems and videogames. Tecnología Electrónica

The use of tissue Doppler imaging (TDI) has allowed to obtain velocity, strain and strain rate parameters in real time and is currently used routinely in the echocardiography lab. For analysis 2D image sequences, profiles are marked on the image, and quantitative time profiles are obtained from them, a procedure known as anatomic M-mode. For correct quantification, the position of the region of interest must be tracked along the sequence. We propose a model for tracking profiles using a dual grey level/TDI acquisition. Curves are tracked on the grey level sequence using an optical flow-based snake model and accurate TDI values are obtained from the tracked curve.

The goal of this study is to identify fluorescence excitation wavelengths and reflectance source-detector separations that are significant for diagnosis of cervical pre-cancers. Measurements from fluorescence and reflectance spectroscopy were searched exhaustively using Mahalanobis distance based classification. Fluorescence excitation wavelengths at 340 nm, 350 nm and 410 nm and reflectance source-detector separation of 250 /spl mu/m appear significant for discriminating a pair of diagnostic classes.

In this paper, we bring together the advances of in vivo optical imaging and modern nano-chemistry to permit optical imaging with molecular specificity. We present optically interrogated contrast agents based on metal nanocrystals attached to probe molecules with a high affinity to a specific biomarker on the surface of epithelial cancer cells. We demonstrated that unique optical properties of metal nanoparticles can be used to develop novel optically-interrogatable contrast agents for confocal reflectance imaging of pre-cancers.

Invasive carcinoma of the uterine cervix is preceded by a number of morphological intraepithelial changes. Real-time confocal microscopy has been demonstrated to be successful in imaging subcellular detail in-vivo. The purpose of this pilot study is to image ex-vivo tissue using a near real time confocal microscope and determine whether the images can be used to distinguish between normal and dysplastic tissue. Biopsies from 19 patients were imaged at various depths with our confocal microscope. Nuclear morphologic features were extracted from the confocal images. The morphologic feature measurements compare well with the pathologic examination. Discriminating the images for the presence of dysplasia using morphologic feature detection resulted in a sensitivity and specificity of 100% and 91%, respectively.

Cluster division is a crucial problem in analytical image based cytology. Existing algorithms often make use either of the image content or its geometric characterization. Both sources of information are needed for a correct segmentation of difficult clusters. Morphological algorithms naturally deal with the object oriented criteria such as shape, size, contrast, connectivity, etc. In this paper, we present and evaluate a morphological watershed based algorithm applied to fluorescence stained clustered nuclei division. Results are shown for two different types of samples namely bone marrow and peripheral blood specimens. These results are better than those obtained for other published algorithms. This algorithm can also be easily adapted to different types of specimens.

A surgical zone fuzzy environmental control is implemented for a typical hospital using a fuzzy controller which has been multiplexed for seven surgical rooms. This controller substitutes an On-Off manual control which simply opens or closes completely the air flow dampers permitting the pass of 100% or 0% fresh air to the rooms. Field tests have shown abilities of control for the fuzzy controller between 19 to 22 degrees C with fluctuations of about 0.6 degrees. >