Splat-based surface reconstruction from defect-laden point sets

We introduce a method for surface reconstruction from point sets that is able to cope with noise and outliers. First, a splat-based representation is computed from the point set. A robust local 3D RANSAC-based procedure is used to filter the point set for outliers, then a local jet surface - a low-degree surface approximation - is fitted to the inliers. Second, we extract the reconstructed surface in the form of a surface triangle mesh through Delaunay refinement. The Delaunay refinement meshing approach requires computing intersections between line segment queries and the surface to be meshed. In the present case, intersection queries are solved from the set of splats through a 1D RANSAC procedure

HPLC-DAD based method for the quantification of flavonoids in the hydroethanolic extract of Tonina fluviatilis Aubl. (Eriocaulaceae) and their radical scavenging activity

This article describes the isolation and identification of flavonoids in the hydroethanolic extract of the aerial parts from Tonina fluviatilis and evaluation of their antiradical activity. A method based on HPLC-DAD was developed and validated for detecting and quantifying flavonoids in hydroethanolic extracts. The flavonoids identified and quantified in the extract were 6,7-dimethoxyquercetin-3-O-β-D-glucopyranoside (1), 6-hydroxy-7-methoxyquercetin-3-O-β-D-glucopyranoside (2), and 6-methoxyquercetin-3-O-β-D-glucopyranoside (3). The developed method presented good validation parameters, showing that the results obtained are consistent and can be used in ensuring the quantification of these constituents in the extracts. Compounds 2 and 3 showed strong antiradical activity when compared with the positive controls (quercetin and gallic acid).

Yleislääkärin vastaanottotapahtuma - näkökulmia laatuun

Tutkimuksen tavoitteena oli tutkia yleislääkärin vastaanottotapahtuman laadun eri ulottuvuuksia, erityisesti lääkärin ja potilaan arvioita vastaanottotapahtuman laadusta, sekä verrata näitä arvioita keskenään. Lisäksi tarkoituksena oli tutkia palkkausjärjestelmän yhteyttä laatuun sekä löytää sopivia välineitä yleislääkärin vastaanottotapahtuman laadun arviointiin. Tutkimuksessa käytettiin triangulaatiota sekä materiaalien, tutkijoiden että menetelmien osalta. Materiaali koostui kyselylomakkeista (2191 vastaanottotapahtumaa, 2167 lääkärin lomaketta ja 1777 potilaan lomaketta), potilasasiakirjoista (n=175) ja vastaanottotapahtumien videoinneista (n=20). Analyysissä käytettiin sekä kvantitatiivisia että kvalitatiivisia menetelmiä. Laatu koostuu tässä tutkimuksessa tieteellisteknisestä/ammatillisesta osaamisesta, vuorovaikutustaidoista ja taloudellisesta laadusta. Kaikki osatekijät olivat kyselylomaketutkimuksen perusteella varsin hyviä, ja potilaat arvioivat laadun kaikki osatekijät paremmiksi kuin lääkärit. Potilaiden selviytyminen ja voimaantuminen vastaanottotapahtuman jälkeen oli parempaa, mikäli he pitivät vuorovaikutuksen laatua hyvänä ja lääkäriä omalääkärinään. Kyselylomaketutkimus antoi laadusta kuitenkin positiivisemman kuvan kuin tutkijoiden potilasasiakirjojen ja videointien avulla tekemät arviot. Potilasasiakirjat oli laadittu puutteellisesti ja potilasasiakirjajärjestelmät vaikuttivat postilaisasiakirjojen laatuun. Tutkijoiden arvioimana lääkäreiden vuorovaikutustaidot olivat keskimäärin tyydyttävät. Lääkärin virkaehtosopimus ei näyttänyt vaikuttavan potilaan kokemaan laatuun, mutta väestövastuulääkärit kokivat sekä oman työnsä ammatillisen laadun että vuorovaikutustaitonsa paremmaksi kuin muut lääkärit. Väestövastuuterveyskeskuksissa myös hoidon jatkuvuus ja potilaan valinnanvapaus näyttivät toteutuvan muita terveyskeskuksia paremmin. Yleislääkärin työn laadun arviointiin tarvitaan useita menetelmiä. Potilasasiakirjajärjestelmien tulisi olla helppokäyttöisiä, interaktiivisia ja tietoa automaattisesti kerääviä, jotta niistä saataisiin luotettavaa tietoa laadun arvioimiseksi. Lääkärin työn itsearviointia on edelleen tutkittava ja kehitettävä.

Development of internet-based value added services in housing estate business in Russia

Value added services are becoming increasingly popular as they increase the perceived value of the core product and can be a strong method of attracting customers and motivating them to make a choice. The purpose of this research is to develop internet-based value added services for housing estate business in Russia. The research is a case study of Russian housing estate market utilising a triangulation of methods for better results. For the qualitative data analysis, 7 interviews with heads of regional departments of construction companies from different regions of Russia were conducted. For the quantitative data analysis, a survey of 128 inhabitants of Saint-Petersburg housing estates was held. Factor analysis and descriptive statistics including cross-tabulations and chi-square tests for significance were used to analyse the results. In this study, a list 19 value added services that can be provided through online platforms in housing estate market was developed. These services fall into three big groups: social networking services, compulsory and additional services. Additionally, the question of monetisation of online platforms in housing estate market was discussed and three business models were suggested.

Precision mapping

The nondestructive determination of plant total dry matter (TDM) in the field is greatly preferable to the harvest of entire plots in areas such as the Sahel where small differences in soil properties may cause large differences in crop growth within short distances. Existing equipment to nondestructively determine TDM is either expensive or unreliable. Therefore, two radiometers for measuring reflected red and near-infrared light were designed, mounted on a single wheeled hand cart and attached to a differential Global Positioning System (GPS) to measure georeferenced variations in normalized difference vegetation index (NDVI) in pearl millet fields [Pennisetum glaucum (L.) R. Br.]. The NDVI measurements were then used to determine the distribution of crop TDM. The two versions of the radiometer could (i) send single NDVI measurements to the GPS data logger at distance intervals of 0.03 to 8.53 m set by the user, and (ii) collect NDVI values averaged across 0.5, 1, or 2 m. The average correlation between TDM of pearl millet plants in planting hills and their NDVI values was high (r^2 = 0.850) but varied slightly depending on solar irradiance when the instrument was calibrated. There also was a good correlation between NDVI, fractional vegetation cover derived from aerial photographs and millet TDM at harvest. Both versions of the rugged instrument appear to provide a rapid and reliable way of mapping plant growth at the field scale with a high spatial resolution and should therefore be widely tested with different crops and soil types.

Low-altitude aerial photography for optimum N fertilization of winter wheat on the North China Plain

Previous research has shown that site-specific nitrogen (N) fertilizer recommendations based on an assessment of a soil’s N supply (mineral N testing) and the crop’s N status (sap nitrate analysis) can help to decrease excessive N inputs for winter wheat on the North China Plain. However, the costs to derive such recommendations based on multiple sampling of a single field hamper the use of this approach at the on-farm level. In this study low-altitude aerial true-color photographs were used to examine the relationship between image-derived reflectance values and soil–plant data in an on-station experiment. Treatments comprised a conventional N treatment (typical farmers’ practice), an optimum N treatment (N application based on soil–plant testing) and six treatments without N (one to six cropping seasons without any N fertilizer input). Normalized intensities of the red, green and blue color bands on the photographs were highly correlated with total N concentrations, SPAD readings and stem sap nitrate of winter wheat. The results indicate the potential of aerial photography to determine in combination with on site soil–plant testing the optimum N fertilizer rate for larger fields and to thereby decrease the costs for N need assessments.

Determining nugget: sill ratios of standardized variograms from aerial photographs to krige sparse soil data

Maps of kriged soil properties for precision agriculture are often based on a variogram estimated from too few data because the costs of sampling and analysis are often prohibitive. If the variogram has been computed by the usual method of moments, it is likely to be unstable when there are fewer than 100 data. The scale of variation in soil properties should be investigated prior to sampling by computing a variogram from ancillary data, such as an aerial photograph of the bare soil. If the sampling interval suggested by this is large in relation to the size of the field there will be too few data to estimate a reliable variogram for kriging. Standardized variograms from aerial photographs can be used with standardized soil data that are sparse, provided the data are spatially structured and the nugget:sill ratio is similar to that of a reliable variogram of the property. The problem remains of how to set this ratio in the absence of an accurate variogram. Several methods of estimating the nugget:sill ratio for selected soil properties are proposed and evaluated. Standardized variograms with nugget:sill ratios set by these methods are more similar to those computed from intensive soil data than are variograms computed from sparse soil data. The results of cross-validation and mapping show that the standardized variograms provide more accurate estimates, and preserve the main patterns of variation better than those computed from sparse data.

Extraction of tidal channel networks from aerial photographs alone and combined with laser altimetry

Tidal channel networks play an important role in the intertidal zone, exerting substantial control over the hydrodynamics and sediment transport of the region and hence over the evolution of the salt marshes and tidal flats. The study of the morphodynamics of tidal channels is currently an active area of research, and a number of theories have been proposed which require for their validation measurement of channels over extensive areas. Remotely sensed data provide a suitable means for such channel mapping. The paper describes a technique that may be adapted to extract tidal channels from either aerial photographs or LiDAR data separately, or from both types of data used together in a fusion approach. Application of the technique to channel extraction from LiDAR data has been described previously. However, aerial photographs of intertidal zones are much more commonly available than LiDAR data, and most LiDAR flights now involve acquisition of multispectral images to complement the LiDAR data. In view of this, the paper investigates the use of multispectral data for semiautomatic identification of tidal channels, firstly from only aerial photographs or linescanner data, and secondly from fused linescanner and LiDAR data sets. A multi-level, knowledge-based approach is employed. The algorithm based on aerial photography can achieve a useful channel extraction, though may fail to detect some of the smaller channels, partly because the spectral response of parts of the non-channel areas may be similar to that of the channels. The algorithm for channel extraction from fused LiDAR and spectral data gives an increased accuracy, though only slightly higher than that obtained using LiDAR data alone. The results illustrate the difficulty of developing a fully automated method, and justify the semi-automatic approach adopted.

Extraction of tidal channel networks from airborne scanning laser altimetry and aerial photography

The study of the morphodynamics of tidal channel networks is important because of their role in tidal propagation and the evolution of salt-marshes and tidal flats. Channel dimensions range from tens of metres wide and metres deep near the low water mark to only 20-30cm wide and 20cm deep for the smallest channels on the marshes. The conventional method of measuring the networks is cumbersome, involving manual digitising of aerial photographs. This paper describes a semi-automatic knowledge-based network extraction method that is being implemented to work using airborne scanning laser altimetry (and later aerial photography). The channels exhibit a width variation of several orders of magnitude, making an approach based on multi-scale line detection difficult. The processing therefore uses multi-scale edge detection to detect channel edges, then associates adjacent anti-parallel edges together to form channels using a distance-with-destination transform. Breaks in the networks are repaired by extending channel ends in the direction of their ends to join with nearby channels, using domain knowledge that flow paths should proceed downhill and that any network fragment should be joined to a nearby fragment so as to connect eventually to the open sea.

How could construction supply chain benefit from RFID/GPS integration: a knowledge management perspective

Construction materials and equipment are essential building blocks of every construction project and may account for 50-60 per cent of the total cost of construction. The rate of their utilization, on the other hand, is the element that most directly relates to a project progress. A growing concern in the industry that inadequate efficiency hinders its success could thus be accommodated by turning construction into a logistic process. Although mostly limited, recent attempts and studies show that Radio Frequency IDentification (RFID) applications have significant potentials in construction. However, the aim of this research is to show that the technology itself should not only be used for automation and tracking to overcome the supply chain complexity but also as a tool to generate, record and exchange process-related knowledge among the supply chain stakeholders. This would enable all involved parties to identify and understand consequences of any forthcoming difficulties and react accordingly before they cause major disruptions in the construction process. In order to achieve this aim the study focuses on a number of methods. First of all it develops a generic understanding of how RFID technology has been used in logistic processes in industrial supply chain management. Secondly, it investigates recent applications of RFID as an information and communication technology support facility in construction logistics for the management of construction supply chain. Based on these the study develops an improved concept of a construction logistics architecture that explicitly relies on integrating RFID with the Global Positioning System (GPS). The developed conceptual model architecture shows that categorisation provided through RFID and traceability as a result of RFID/GPS integration could be used as a tool to identify, record and share potential problems and thus vastly improve knowledge management processes within the entire supply chain. The findings thus clearly show a need for future research in this area.

Application of integrated GPS and GIS technology for reducing construction waste and improving construction efficiency

This paper presents a study on applying an integrated Global Position System (GPS) and Geographacial Information System (GIS) technology to the reduction of construction waste. During the study, a prototype study is developed from automatic data capture system such as the barcoding system for construction material and equipment (M&E) management onsite, whilst the integrated GPS and GIS technology is combined to the M&E system based on the Wide Area Network (WAN). Then, a case study is conducted to demonstrate the deployment of the system. Experimental results indicate that the proposed system can minimize the amount of onsite material wastage.

An analysis of real time implementation of Fourier transform-based frequency recognition algorithms

Frequency recognition is an important task in many engineering fields such as audio signal processing and telecommunications engineering, for example in applications like Dual-Tone Multi-Frequency (DTMF) detection or the recognition of the carrier frequency of a Global Positioning, System (GPS) signal. This paper will present results of investigations on several common Fourier Transform-based frequency recognition algorithms implemented in real time on a Texas Instruments (TI) TMS320C6713 Digital Signal Processor (DSP) core. In addition, suitable metrics are going to be evaluated in order to ascertain which of these selected algorithms is appropriate for audio signal processing(1).

Optimization algorithms in FMRF model-based segmentation for LIDAR data and co-registered bands

In this paper, a fuzzy Markov random field (FMRF) model is used to segment land-objects into free, grass, building, and road regions by fusing remotely, sensed LIDAR data and co-registered color bands, i.e. scanned aerial color (RGB) photo and near infra-red (NIR) photo. An FMRF model is defined as a Markov random field (MRF) model in a fuzzy domain. Three optimization algorithms in the FMRF model, i.e. Lagrange multiplier (LM), iterated conditional mode (ICM), and simulated annealing (SA), are compared with respect to the computational cost and segmentation accuracy. The results have shown that the FMRF model-based ICM algorithm balances the computational cost and segmentation accuracy in land-cover segmentation from LIDAR data and co-registered bands.

Land-cover classification from airborne LIDAR data fused with aerial optical images

Airborne LIght Detection And Ranging (LIDAR) provides accurate height information for objects on the earth, which makes LIDAR become more and more popular in terrain and land surveying. In particular, LIDAR data offer vital and significant features for land-cover classification which is an important task in many application domains. In this paper, an unsupervised approach based on an improved fuzzy Markov random field (FMRF) model is developed, by which the LIDAR data, its co-registered images acquired by optical sensors, i.e. aerial color image and near infrared image, and other derived features are fused effectively to improve the ability of the LIDAR system for the accurate land-cover classification. In the proposed FMRF model-based approach, the spatial contextual information is applied by modeling the image as a Markov random field (MRF), with which the fuzzy logic is introduced simultaneously to reduce the errors caused by the hard classification. Moreover, a Lagrange-Multiplier (LM) algorithm is employed to calculate a maximum A posteriori (MAP) estimate for the classification. The experimental results have proved that fusing the height data and optical images is particularly suited for the land-cover classification. The proposed approach works very well for the classification from airborne LIDAR data fused with its coregistered optical images and the average accuracy is improved to 88.9%.

Normality mining: privacy implications of behavioral profiles drawn from GPS enabled mobile phones

There is growing interest in the ways in which the location of a person can be utilized by new applications and services. Recent advances in mobile technologies have meant that the technical capability to record and transmit location data for processing is appearing in off-the-shelf handsets. This opens possibilities to profile people based on the places they visit, people they associate with, or other aspects of their complex routines determined through persistent tracking. It is possible that services offering customized information based on the results of such behavioral profiling could become commonplace. However, it may not be immediately apparent to the user that a wealth of information about them, potentially unrelated to the service, can be revealed. Further issues occur if the user agreed, while subscribing to the service, for data to be passed to third parties where it may be used to their detriment. Here, we report in detail on a short case study tracking four people, in three European member states, persistently for six weeks using mobile handsets. The GPS locations of these people have been mined to reveal places of interest and to create simple profiles. The information drawn from the profiling activity ranges from intuitive through special cases to insightful. In this paper, these results and further extensions to the technology are considered in light of European legislation to assess the privacy implications of this emerging technology.