Urban satellite image classification using biologically inspired techniques

This paper focuses on optimisation algorithms inspired by swarm intelligence for satellite image classification from high resolution satellite multi- spectral images. Amongst the multiple benefits and uses of remote sensing, one of the most important has been its use in solving the problem of land cover mapping. As the frontiers of space technology advance, the knowledge derived from the satellite data has also grown in sophistication. Image classification forms the core of the solution to the land cover mapping problem. No single classifier can prove to satisfactorily classify all the basic land cover classes of an urban region. In both supervised and unsupervised classification methods, the evolutionary algorithms are not exploited to their full potential. This work tackles the land map covering by Ant Colony Optimisation (ACO) and Particle Swarm Optimisation (PSO) which are arguably the most popular algorithms in this category. We present the results of classification techniques using swarm intelligence for the problem of land cover mapping for an urban region. The high resolution Quick-bird data has been used for the experiments.

A preliminary classification of lake types in Northern Ireland

The EC Water Framework Directive (WFD) introduces the concept of the ecological status of surface waters. The WFD requires that water bodies within an ecoregion are divided into waterbody "types" or "ecotypes". The waterbody type is determined by physico-chemical descriptors. A group of representatives from two government environmental agencies (Environment and Heritage Service and the Industrial Research and Technology Unit) and the two universities (Queen's University Belfast and the University of Ulster) in Northern Ireland, has been established to develop methods for measuring the ecological status of lakes, for the purposes of the WFD. The work here is that contributing to the first objective classification into waterbody types.

On the classification of lakes and lake-like bodies of the Ukraine [Translation from: Gidrobiologicheskie Zhurnal, Kiev 19(2) 100-101, 1983]

In the Ukraine there are several thousand large, medium and small lakes and lake-like reservoirs, distinguished by origin, salinity, regional position, productivity and by construction a significant number of large and small water bodies, ponds and industrial reservoirs of variable designation. The problem of national systems necessitates the creation of specific schemes and classifications. Classifying into specific types of reservoir by means of suitable specifications is required for planning national measures with the objective of the rational utilisation of natural resources. It is now necessary to consider the present-day characteristics of Ukranian lakes. In the case of the Ukraine it is possible to use two approaches - genetical and ecological. This paper uses the genetical system to classify the lake-like water bodies of the Ukraine.

Estudio, análisis y clasificación de mecanismos con aplicación industrial

[ES]El uso de maquinaria en la industria es algo muy habitual en la actualidad. Dicha maquinaria necesita una serie de mecanismos para realizar una acción deseada, y en función de esa acción, se hará uso de un mecanismo u otro. Este informe representa el estudio y análisis cinemático que se ha llevado a cabo para la posterior clasificación de mecanismos planos que tengan un grado de libertad con aplicación industrial. Para todo ello se ha partido de un previo conocimiento de la materia que se ha ido complementando con diferentes fuentes de información especializadas. La clasificación de los mecanismos que se va a realizar en este trabajo no es más que una de las muchas posibilidades que hay a la hora de clasificarlos ya que se han hecho bastantes intentos para realizar clasificaciones de mecanismos, pero dada la complejidad de la tarea no se ha llegado a una clasificación general unificada. La línea de trabajo que se presenta aquí consiste en el análisis cinemático de diferentes mecanismos para la posterior creación de un prototipo de uno de ellos. La estructura de los contenidos que se desarrollan a continuación es la siguiente: En primer lugar se ha realizado una búsqueda de mecanismos que cumplan la condición de ser mecanismos planos que tengan un grado de libertad y que tengan utilidad demostrada. En segundo lugar se han recopilado los resultados cinemáticos del mecanismo, construcciones gráficas de los elementos que lo componen y se añadirán animaciones de cada mecanismo, haciendo después una valoración en función de los resultados obtenidos de los mismos. En tercer lugar se han clasificado en diferentes grupos dependiendo de su función o aplicación. En cuarto lugar, se ha realizado un prototipo de uno de los mecanismos para comprobar su funcionamiento.

Análisis tipológico de la serie industrial achelense de Puyo (Lannemezan, Hautes-Pyrénées, France). Ensayo de clasificación de piezas “hacheroides”

[ES] El conjunto industrial achelense de Puyo (Lannemezan, Hautes-Pyrénées), descubierto por G. Laplace en 1954 en posición estratigráfica rissiense, está compuesto por 360 ejemplares líticos tallados en cuarcita local. Este efectivo industrial se reparte entre: 218 piezas retocadas (en las que se han definido 226 tipos primarios), 136 lascas y 6 núcleos. Tecnológicamente, la mayor parte de las industrias parecen estar en relación con un debitado sobre yunque; técnica de talla que ha procurado unas lascas con unos atributos muy específicos, en las que, en varios casos, son más que evidentes sus analogías morfológicas con los "hachereaux". En este sentido, la elevada presencia de "hachereaux" bien formateados y de otras piezas hacheroides más elementales, menos elaboradas, así como de varias formas particulares de utillaje macrolítico (ojivas, puntas), nos ha llevado a plantear una propuesta de definición y clasificación analítica particular para estos temas. La contribución global de estas piezas macrolíticas es superior a la de los útiles convencionales o más habituales. Por último, en lo que concierne a la valoración tipológica, este original complejo achelense está definido esencialmente, además de por los más numerosos tipos hacheroides, por una casi similar presencia de denticulados y una importante contribución de puntas carenoides. Más complementariamente, deben estimarse las aportaciones de ojivas y raederas, y son francamente minoritarios los restantes grupos tipológicos considerados (de cantos tallados, truncaduras, puntas planas, abruptos, raspadores, "becs", fragmentos de piezas bifaciales indeterminadas y "écaillés").

Prediction of integral type failures in semiconductor manufacturing through classification methods

Smart management of maintenances has become fundamental in manufacturing environments in order to decrease downtime and costs associated with failures. Predictive Maintenance (PdM) systems based on Machine Learning (ML) techniques have the possibility with low added costs of drastically decrease failures-related expenses; given the increase of availability of data and capabilities of ML tools, PdM systems are becoming really popular, especially in semiconductor manufacturing. A PdM module based on Classification methods is presented here for the prediction of integral type faults that are related to machine usage and stress of equipment parts. The module has been applied to an important class of semiconductor processes, ion-implantation, for the prediction of ion-source tungsten filament breaks. The PdM has been tested on a real production dataset. © 2013 IEEE.

Prevalencia de neumoconiosis y su relación con medidas de higiene y seguridad industrial y niveles ambientales de carbón en minería subterránea en el departamento de Cundinamarca - Colombia, 2015

Introducción: La exposición en minas subterráneas a altos niveles de polvo de carbón está relacionada con patologías pulmonares. Objetivo: Determinar la prevalencia de neumoconiosis, medidas de higiene y seguridad industrial y su relación con niveles ambientales de carbón en trabajadores de minas de socavón en Cundinamarca. Materiales y Métodos: Estudio de corte transversal, en 215 trabajadores seleccionados mediante muestreo probabilístico estratificado con asignación proporcional. Se realizaron monitoreos ambientales, radiografías de tórax y encuestas con variables sociodemográficas y laborales. Se emplearon medidas de tendencia central y dispersión y la prueba de independencia ji-cuadrado de Pearson o pruebas exactas, con el fin de establecer las asociaciones. Resultados: El 99,5% de la población perteneció al género masculino, el 36,7% tenía entre 41-50 años, con un promedio de años de trabajo de 21,70 ± 9,99. La prevalencia de neumoconiosis fue de 42,3% y la mediana de la concentración de polvo de carbón bituminoso fue de 2,329670 mg/m3. El índice de riesgo de polvo de carbón presentó diferencias significativas en las categorías de bajo (p=0,0001) y medio (p=0,0186) con la prevalencia de neumoconiosis. El 84,2% reporto no usar mascarilla. No se presentan diferencias entre los niveles de carbón (p=0,194) con la prevalencia de neumoconiosis. Conclusiones: Se encontró una prevalencia de neumoconiosis de 42,3% en Cundinamarca. Se requiere contar con medidas de higiene y seguridad industrial efectivas para controlar el riesgo al que están expuestos los mineros de carbón por la inhalación de polvo de carbón.

Integrated visual vocabulary in latent Dirichlet allocation-based scene classification for IKONOS image

Scene classification based on latent Dirichlet allocation (LDA) is a more general modeling method known as a bag of visual words, in which the construction of a visual vocabulary is a crucial quantization process to ensure success of the classification. A framework is developed using the following new aspects: Gaussian mixture clustering for the quantization process, the use of an integrated visual vocabulary (IVV), which is built as the union of all centroids obtained from the separate quantization process of each class, and the usage of some features, including edge orientation histogram, CIELab color moments, and gray-level co-occurrence matrix (GLCM). The experiments are conducted on IKONOS images with six semantic classes (tree, grassland, residential, commercial/industrial, road, and water). The results show that the use of an IVV increases the overall accuracy (OA) by 11 to 12% and 6% when it is implemented on the selected and all features, respectively. The selected features of CIELab color moments and GLCM provide a better OA than the implementation over CIELab color moment or GLCM as individuals. The latter increases the OA by only ∼2 to 3%. Moreover, the results show that the OA of LDA outperforms the OA of C4.5 and naive Bayes tree by ∼20%. © 2014 Society of Photo-Optical Instrumentation Engineers (SPIE) [DOI: 10.1117/1.JRS.8.083690]

Mapping soil pollution by spatial analysis and fuzzy classification

Spatial analysis and fuzzy classification techniques were used to estimate the spatial distributions of heavy metals in soil. The work was applied to soils in a coastal region that is characterized by intense urban occupation and large numbers of different industries. Concentrations of heavy metals were determined using geostatistical techniques and classes of risk were defined using fuzzy classification. The resulting prediction mappings identify the locations of high concentrations of Pb, Zn, Ni, and Cu in topsoils of the study area. The maps show that areas of high pollution of Ni and Cu are located at the northeast, where there is a predominance of industrial and agricultural activities; Pb and Zn also occur in high concentrations in the northeast, but the maps also show significant concentrations of Pb and Zn in other areas, mainly in the central and southeastern parts, where there are urban leisure activities and trade centers. Maps were also prepared showing levels of pollution risk. These maps show that (1) Cu presents a large pollution risk in the north-northwest, midwest, and southeast sectors, (2) Pb represents a moderate risk in most areas, (3) Zn generally exhibits low risk, and (4) Ni represents either low risk or no risk in the studied area. This study shows that combining geostatistics with fuzzy theory can provide results that offer insight into risk assessment for environmental pollution.

Identification and feature selection of non-technical losses for industrial consumers using the software WEKA

This work has as objectives the implementation of a intelligent computational tool to identify the non-technical losses and to select its most relevant features, considering information from the database with industrial consumers profiles of a power company. The solution to this problem is not trivial and not of regional character, the minimization of non-technical loss represents the guarantee of investments in product quality and maintenance of power systems, introduced by a competitive environment after the period of privatization in the national scene. This work presents using the WEKA software to the proposed objective, comparing various classification techniques and optimization through intelligent algorithms, this way, can be possible to automate applications on Smart Grids. © 2012 IEEE.

Computer techniques towards the automatic characterization of graphite particles in metallographic images of industrial materials

The automatic characterization of particles in metallographic images has been paramount, mainly because of the importance of quantifying such microstructures in order to assess the mechanical properties of materials common used in industry. This automated characterization may avoid problems related with fatigue and possible measurement errors. In this paper, computer techniques are used and assessed towards the accomplishment of this crucial industrial goal in an efficient and robust manner. Hence, the use of the most actively pursued machine learning classification techniques. In particularity, Support Vector Machine, Bayesian and Optimum-Path Forest based classifiers, and also the Otsu's method, which is commonly used in computer imaging to binarize automatically simply images and used here to demonstrated the need for more complex methods, are evaluated in the characterization of graphite particles in metallographic images. The statistical based analysis performed confirmed that these computer techniques are efficient solutions to accomplish the aimed characterization. Additionally, the Optimum-Path Forest based classifier demonstrated an overall superior performance, both in terms of accuracy and speed. © 2012 Elsevier Ltd. All rights reserved.