La Bibliografía Científica de Fernando de Buen.

Si bien existen varios ensayos biográficos que enfocan diferentes momentos de su vida (ANÓNIMO, 1963, BAHAMONDE, 1962, LÓPEZ et al., 2015, NION, 2015, PEQUEÑO, 2015, SÁNCHEZ CARRILLO, 2001), hasta donde tenemos conocimiento, no se ha publicado aún una bibliografía completa de la obra del Dr. FERNANDO DE BUEN Y LOZANO (Fig. de tapa). Bibliografías parciales se encuentran, entre otros, en los autores arriba citados. Aquí nos atrevemos a hacer el intento, aunque en forma defectuosa, ya que muchas de sus publicaciones no las hemos podido consultar directamente (se señalan con un asterisco, *). En parte nos hemos basado en una compilación hecha por el propio DE BUEN, que abarca los años 1915 a 1949 (Fig. 1), aunque no siempre con los datos necesarios para una completa información sobre la publicación; en lo posible intentamos complementarla. En sus casi cincuenta años de actividad científica, llegó a producir casi 300 títulos, de variado contenido, aunque siempre relacionados con el medio acuático, sea marino o dulceacuícola. Esta producción se puede dividir en cuatro períodos, que comienza con su etapa española, europea y africana (marroquí), entre 1915 y 1937, durante la cual publicó más de 140 títulos. Como consecuencia de la Guerra Civil Española, en 1939 se radica en México, donde permanece desde el 12 de Julio de 1939 hasta Noviembre 1946, país al que regresa entre 1953 y 1957. Durante este período escribe unos 70 artículos. Entre esas dos etapas mexicanas, estuvo brevemente radicado en el Uruguay, desde el 26 de Noviembre de 1946 hasta 1953, sin duda la etapa de menor producción científica, con una docena trabajos. A ésta sigue el último período de su vida, en Chile (Fig. 2), la que lamentablemente termina trágicamente, en 1962. Durante este período publica más de 60 publicaciones, de los cuales, aparentemente, seis quedan inéditas. Cabe señalar que durante estas tres etapas de exilio americano, si bien sus publicaciones están mayoritariamente relacionadas con el país de residencia, hay algunas excepciones. Preivo a estas estadías en América, hay que mencionar tres europeas, fuera de España, a saber: en el Museo Oceanográfico de Mónaco (1919), en el Instituto Centrale di Biologia Marina, Messina, Italia (1919), y en el Laboratorio Arago, Banyuls sur Mer, Francia (1939). En general, puede considerarse que FERNANDO DE BUEN fue un investigador solitario, ya que solamente seis, de sus casi 300 trabajos, fueron publicados en colaboración: dos con su hermano SADÍ DE BUEN (#31 y 32), dos con F. FRADE (#115 y 116), y dos con MANUEL ZOZAYA (#162 y 176). En su obra científica hemos podido identificar la descripción original de 12 géneros, 9 subgéneros, 54 especies y 11 subespecies, como se indican en la Tabla I.

An experimental model of relay deployment planning tool for a wireless sensor network system to monitor civil engineering structures

It is essential to monitor deteriorated civil engineering structures cautiously to detect symptoms of their serious disruptions. A wireless sensor network can be an effective system for monitoring civil engineering structures. It is fast to deploy sensors especially in difficult-to-access areas, and it is extendable without any cable extensions. Since our target is to monitor deteriorations of civil engineering structures such as cracks at tunnel linings, most of the locations of sensors are known, and sensors are not required to move dynamically. Therefore, we focus on developing a deployment plan of a static network in order to reduce the value of a cost function such as initial installation cost and summation of communication distances of the network. The key issue of the deployment is the location of relays that forward sensing data from sensors to a data collection device called a gateway. In this paper, we propose a relay deployment-planning tool that can be used to design a wireless sensor network for monitoring civil engineering structures. For the planning tool, we formalize the model and implement a local search based algorithm to find a quasi-optimal solution. Our solution guarantees two routings from a sensor to a gateway, which can provide higher reliability of the network. We also show the application of our experimental tool to the actual environment in the London Underground.

Seminario sobre ciencias básicas como prerequisito para la enseñanza de la oceanografía (1-2 octubre de 1962)- Seminario sobre biogeografía de los organismos marinos (3-6 octubre de 1962)

Por acuerdo del Seminario Latinoamericano sobre Estudios Oceanográficos realizado en la Universidad de Concepción, Chile, 20-25 noviembre de 1961, se recomendó la realización en Argentina de un Seminario sobre Biogeografía de Organismos Marinos, indicándose al Museo Argentino de Ciencias Naturales Bernardino Rivadavia como sede del mismo. Luego de varias conversaciones en Buenos Aires (Argentina), entre autoridades del Centro de Cooperación Científica para América Latina, del CONICET (Consejo Nacional de Investigaciones Científicas y Técnicas), del Servicio de Hidrografía Naval, del mencionado Museo y del Instituto de Biología Marina de Mar del Plata, se acordó realizar los seminarios en éste último instituto del 1 al 6 octubre de 1962. Del 1 al 2 de octubre, se realizó el Seminario sobre Ciencias Básicas como prerrequisito para la Enseñanza de la Oceanografía, pero los documentos no fueron incluídos en este Boletín. Del 3 al 6 de octubre, tuvo lugar el Seminario sobre Biogeografía de Organismos Marinos, con la participación de investigadores de: Brasil, Colombia, Costa Rica, Chile, Mexico, Perú, Uruguay, Venezuela y de Argentina, y se incluyeron los siguientes trabajos publicados: Joly, A. - Extensao da flora marinha no sul do Brasil- nota preliminar; Etcheverry Daza, H. - Distribución geográfica de las algas del Pacífico; Diaz-Piferrer, M. - Biogeografía de las algas marinas tropicales de la costa Atlántica de America, Resumen,; Kuhneman, O. - Importancia de la vegetación en biogeografía marina; Boschi, E.E. - Los peneidos de Brasil, Uruguay y Argentina; Bernasconi, I. - Distribución geográfica de los equinoideos y asteroideos de la extremidad austral de Sudamérica; Szidat, L. - La parasitología como ciencia auxiliar para la biogeografía de organismos marinos; López, R.B. - Problemas de la distribución geográfica de los peces marinos sudamericanos; Ximénez, I. - Estudio preliminar de la distribución geográfica actual de los pinípedos en América Latina; Balech, E. - La división zonal en biología marina y su nomenclatura; Stuardo, J. - Distribución de los moluscos marinos litorales en Latinoamérica; Boltovskoy, E. - Provincias zoogeográficas de América del Sur y su sector Antártico según los foraminíferos bentónicos; Rioja, E. - Caracteres de la biogeografía marina de México y de Centro América; Balech, E. - Caracteres biogeográficos de la región de Argentina y Uruguay; Vannucci, M. - Zoogeografía marinha do Brasil.

Visual pattern recognition models for remote sensing of civil infrastructure

As-built models have been proven useful in many project-related applications, such as progress monitoring and quality control. However, they are not widely produced in most projects because a lot of effort is still necessary to manually convert remote sensing data from photogrammetry or laser scanning to an as-built model. In order to automate the generation of as-built models, the first and fundamental step is to automatically recognize infrastructure-related elements from the remote sensing data. This paper outlines a framework for creating visual pattern recognition models that can automate the recognition of infrastructure-related elements based on their visual features. The framework starts with identifying the visual characteristics of infrastructure element types and numerically representing them using image analysis tools. The derived representations, along with their relative topology, are then used to form element visual pattern recognition (VPR) models. So far, the VPR models of four infrastructure-related elements have been created using the framework. The high recognition performance of these models validates the effectiveness of the framework in recognizing infrastructure-related elements.

Comparison of Civil Infrastructure Optical-based Spatial Data Acquisition Techniques

Infrastructure spatial data, such as the orientation and the location of in place structures and these structures' boundaries and areas, play a very important role for many civil infrastructure development and rehabilitation applications, such as defect detection, site planning, on-site safety assistance and others. In order to acquire these data, a number of modern optical-based spatial data acquisition techniques can be used. These techniques are based on stereo vision, optics, time of flight, etc., and have distinct characteristics, benefits and limitations. The main purpose of this paper is to compare these infrastructure optical-based spatial data acquisition techniques based on civil infrastructure application requirements. In order to achieve this goal, the benefits and limitations of these techniques were identified. Subsequently, these techniques were compared according to applications' requirements, such as spatial accuracy, the automation of acquisition, the portability of devices and others. With the help of this comparison, unique characteristics of these techniques were identified so that practitioners will be able to select an appropriate technique for their own applications.

Comparison of Civil Infrastructure Optical-based Spatial Data Acquisition Techniques

Infrastructure spatial data, such as the orientation and the location of in place structures and these structures' boundaries and areas, play a very important role for many civil infrastructure development and rehabilitation applications, such as defect detection, site planning, on-site safety assistance and others. In order to acquire these data, a number of modern optical-based spatial data acquisition techniques can be used. These techniques are based on stereo vision, optics, time of flight, etc., and have distinct characteristics, benefits and limitations. The main purpose of this paper is to compare these infrastructure optical-based spatial data acquisition techniques based on civil infrastructure application requirements. In order to achieve this goal, the benefits and limitations of these techniques were identified. Subsequently, these techniques were compared according to applications' requirements, such as spatial accuracy, the automation of acquisition, the portability of devices and others. With the help of this comparison, unique characteristics of these techniques were identified so that practitioners will be able to select an appropriate technique for their own applications.

Visual Pattern Recognition Models for Remote Sensing of Civil Infrastructure

As-built models have been proven useful in many project-related applications, such as progress monitoring and quality control. However, they are not widely produced in most projects because a lot of effort is still necessary to manually convert remote sensing data from photogrammetry or laser scanning to an as-built model. In order to automate the generation of as-built models, the first and fundamental step is to automatically recognize infrastructure-related elements from the remote sensing data. This paper outlines a framework for creating visual pattern recognition models that can automate the recognition of infrastructure-related elements based on their visual features. The framework starts with identifying the visual characteristics of infrastructure element types and numerically representing them using image analysis tools. The derived representations, along with their relative topology, are then used to form element visual pattern recognition (VPR) models. So far, the VPR models of four infrastructure-related elements have been created using the framework. The high recognition performance of these models validates the effectiveness of the framework in recognizing infrastructure-related elements.

Civil and Environmental Engineering Challenges for Data Sensing and Analysis

The objective of this study was to identify challenges in civil and environmental engineering that can potentially be solved using data sensing and analysis research. The challenges were recognized through extensive literature review in all disciplines of civil and environmental engineering. The literature review included journal articles, reports, expert interviews, and magazine articles. The challenges were ranked by comparing their impact on cost, time, quality, environment and safety. The result of this literature review includes challenges such as improving construction safety and productivity, improving roof safety, reducing building energy consumption, solving traffic congestion, managing groundwater, mapping and monitoring the underground, estimating sea conditions, and solving soil erosion problems. These challenges suggest areas where researchers can apply data sensing and analysis research.

Automated 3D Structure Inference of Civil Infrastructure Using a Stereo Camera Set

The commercial far-range (>10m) infrastructure spatial data collection methods are not completely automated. They need significant amount of manual post-processing work and in some cases, the equipment costs are significant. This paper presents a method that is the first step of a stereo videogrammetric framework and holds the promise to address these issues. Under this method, video streams are initially collected from a calibrated set of two video cameras. For each pair of simultaneous video frames, visual feature points are detected and their spatial coordinates are then computed. The result, in the form of a sparse 3D point cloud, is the basis for the next steps in the framework (i.e., camera motion estimation and dense 3D reconstruction). A set of data, collected from an ongoing infrastructure project, is used to show the merits of the method. Comparison with existing tools is also shown, to indicate the performance differences of the proposed method in the level of automation and the accuracy of results.

Generating the Sparse Point Cloud of a Civil Infrastructure Scene Using a Single Video Camera under Practical Constraints

Automating the model generation process of infrastructure can substantially reduce the modeling time and cost. This paper presents a method to generate a sparse point cloud of an infrastructure scene using a single video camera under practical constraints. It is the first step towards establishing an automatic framework for object-oriented as-built modeling. Motion blur and key frame selection criteria are considered. Structure from motion and bundle adjustment are explored. The method is demonstrated in a case study where the scene of a reinforced concrete bridge is videotaped, reconstructed, and metrically validated. The result indicates the applicability, efficiency, and accuracy of the proposed method.

Optimized selection of key frames for monocular videogrammetric surveying of civil infrastructure

Videogrammetry is an inexpensive and easy-to-use technology for spatial 3D scene recovery. When applied to large scale civil infrastructure scenes, only a small percentage of the collected video frames are required to achieve robust results. However, choosing the right frames requires careful consideration. Videotaping a built infrastructure scene results in large video files filled with blurry, noisy, or redundant frames. This is due to frame rate to camera speed ratios that are often higher than necessary; camera and lens imperfections and limitations that result in imaging noise; and occasional jerky motions of the camera that result in motion blur; all of which can significantly affect the performance of the videogrammetric pipeline. To tackle these issues, this paper proposes a novel method for automating the selection of an optimized number of informative, high quality frames. According to this method, as the first step, blurred frames are removed using the thresholds determined based on a minimum level of frame quality required to obtain robust results. Then, an optimum number of key frames are selected from the remaining frames using the selection criteria devised by the authors. Experimental results show that the proposed method outperforms existing methods in terms of improved 3D reconstruction results, while maintaining the optimum number of extracted frames needed to generate high quality 3D point clouds.© 2012 Elsevier Ltd. All rights reserved.