130,611 research outputs found
Akca 1 FULL AUTOMATIC REGISTRATION OF LASER SCANNER POINT CLOUDS
No full textThe registration of point clouds that are acquired from different laser scanner standpoints is an essential task in the environment modelling works. In this paper, a full automatic point cloud registration scheme is presented. Special targets attached onto the object(s) are used as landmarks and their 3-D coordinates are measured with a theodolite in a ground coordinate system before the scanning process. The presented registration scheme can automatically find these targets in the point clouds using radiometric and geometric information (shape, size, and planarity). At the last step, targets are labelled using the consistent labelling by discrete relaxation in order to find the actual names of the points in the ground control points list.
Observing the effects or rapid industrialization, on forestry and pastures by remote sensing
No full textRapid and uncontrolled industrialization in an area and related population growth require fast assessments for the actual land-cover/land-use (LC/LU) maps and related practices, in order to avoid the overuse and damaging of the landscape beyond sustainability. Growth of industry, brings an increase in population beyond its needs, increasing the housing demands. All these may cause the loss of vegetation cover in the region, mostly of forestry and grassland in the present case (YILDIRIM et al., 1997, 2002). Modern remote sensing and geographic information system (GIS) technologies fit well for the evaluation and long term monitoring of such effects. In the present case, a region of Gebze County (Kocaeli-Turkey), 50 km east of metropolitan Istanbul is considered as a pilot site for long term monitoring of such rapid changes and their effects on the vegetation cover and environment. The region is observed between 1985-2005, by satellite images and quantified the LC/LU changes. Comparisons were then made among the observed patterns over these years and also between images and the land-use patterns projected by the government planning offices carried out in the region in the start of the interval considered. The LC/LU patterns quickly overshot the planned industrial and settlement areas in much less than a decade. The research work also includes an interval just before the 17 August 1999 Marmara Earthquake devastated the dwellings and roads in the area to a large extent. Therefore, the results could also be used, for a comparison of before and after earthquake inventories in many areas. The results in 2005 were indicative of rather fast recovery of the region from the negative effects of earthquake, in many respects. Further, a projection from the observed trends to the year 2010 (the next 5 years) was also made: Industrial areas are expected to increase to about 25% of all the total land area, from a start in 1986, of 2.4% to a 9% in a decade. Forests, although constitutionally protected, also may reduce to 20% (from a starting value of 30%). However the main loser among vegetation cover types was the pasture, which started at 39% in 1986 and is reduced to 5% in 2005. Extrapolation to 2010 is indicative of the possibility that no pasture area would be left in the region
Observing the effects or rapid industrialization, on forestry and pastures by remote sensing
No full textRapid and uncontrolled industrialization in an area and related population growth require fast assessments for the actual land-cover/land-use (LC/LU) maps and related practices, in order to avoid the overuse and damaging of the landscape beyond sustainability. Growth of industry, brings an increase in population beyond its needs, increasing the housing demands. All these may cause the loss of vegetation cover in the region, mostly of forestry and grassland in the present case (YILDIRIM et al., 1997, 2002). Modern remote sensing and geographic information system (GIS) technologies fit well for the evaluation and long term monitoring of such effects. In the present case, a region of Gebze County (Kocaeli-Turkey), 50 km east of metropolitan Istanbul is considered as a pilot site for long term monitoring of such rapid changes and their effects on the vegetation cover and environment. The region is observed between 1985-2005, by satellite images and quantified the LC/LU changes. Comparisons were then made among the observed patterns over these years and also between images and the land-use patterns projected by the government planning offices carried out in the region in the start of the interval considered. The LC/LU patterns quickly overshot the planned industrial and settlement areas in much less than a decade. The research work also includes an interval just before the 17 August 1999 Marmara Earthquake devastated the dwellings and roads in the area to a large extent. Therefore, the results could also be used, for a comparison of before and after earthquake inventories in many areas. The results in 2005 were indicative of rather fast recovery of the region from the negative effects of earthquake, in many respects. Further, a projection from the observed trends to the year 2010 (the next 5 years) was also made: Industrial areas are expected to increase to about 25% of all the total land area, from a start in 1986, of 2.4% to a 9% in a decade. Forests, although constitutionally protected, also may reduce to 20% (from a starting value of 30%). However the main loser among vegetation cover types was the pasture, which started at 39% in 1986 and is reduced to 5% in 2005. Extrapolation to 2010 is indicative of the possibility that no pasture area would be left in the region
Marker-free Automatic Matching of Range Data
No full textMatching of multiple views is often addressed in 3D-model generation and is normally a two-stage process consisting of a coarse and a fine matching stage. Coarse matching, that is the pre-alignment of the surfaces for the complex forms, which can be positioned far away from each other in 3D space, is a difficult problem to solve. Fine matching on the other hand can be performed accurately using either the ICP (iterative closest point) method or the least square surface matching method. Nevertheless, ICP involves an iterative solution which consumes much computing time, and it requires models with considerable degree of overlap at the start position. This is because it treats the closest point in the other model as the corresponding point and updates the corresponding relationship in each iterative step. If the models have insufficient overlap, ICP will converge to false result. Consequently, a good coarse matching is a precondition for a successful ICP. The other matching method- least square surface matching- needs a prealigned corresponding relationship between the surfaces of complex objects, exactly the task of the coarse matching process. This paper presents a novel algorithm to perform coarse matching with an innovative data structure, a “matching tree”, which is a combination of a interpretation tree and a bipartite matching graph. The whole systematic process can be divided in three steps: firstly, it performs segmentation of the laser range scan data according to the geometric characteristics; secondly, a coarse matching is conducted to solve the pre-alignment problem; and finally, an efficient fine matching aligns the models accurately. The coarse matching is not affected by the position of the models, because it generated from a matching tree using invariant relationships from the models themselves. This method is particularly suitable for laser range scan point cloud matching of rooms during th
MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
Matching of 3D surfaces and their intensities
No full text3D surface matching would be an ill conditioned problem when the curvature of the object surface is either homogenous or isotropic, e.g. for plane or spherical types of objects. A reliable solution can only be achieved if supplementary information or functional constraints are introduced. In a previous paper, an algorithm for the least squares matching of overlapping 3D surfaces, which were digitized/sampled point by point using a laser scanner device, by the photogrammetric method or other techniques, was proposed [Gruen, A., and Akca, D., 2005. Least squares 3D surface and curve matching. ISPRS Journal of Photogrammetry and Remote Sensing 59 (3), 151–174.]. That method estimates the transformation parameters between two or more fully 3D surfaces, minimizing the Euclidean distances instead of z-differences between the surfaces by least squares. In this paper, an extension to the basic algorithm is given, which can simultaneously match surface geometry and its attribute information, e.g. intensity, colour, temperature, etc. under a combined estimation model. Three experimental results based on terrestrial laser scanner point clouds are presented. The experiments show that the basic algorithm can solve the surface matching problem provided that the object surface has at least the minimal information. If not, the laser scanner derived intensities are used as supplementary information to find a reliable solution. The method derives its mathematical strength from the least squares image matching concept and offers a high level of flexibility for many kinds of 3D surface correspondence problem
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