bluuebunny/crossref_metadata_2025 huggingface dataset:
Success of IT Deployment
Authors: Dahlberg Tomi , Kivijärvi Hannu , Saarinen Timo
Published: May 2015

IT business value (ITBV) research generally state that various “good” IT management and IT governance practices influence positively IT deployment success and organizational performance. This has proved hard to verify empirically. For this study, the authors analyzed factors that influence IT deployment success. First, the authors identified potential factors, then hypothesized about the relationships among and between the factors and finally integrated the hypotheses into a research model. The authors then empirically evaluated the hypotheses and the entire research model. Special attention was placed on the Business-IT alignment, IT management and the consistency of IT investments in relation to the cyclical behavior of the economy. The consistency of IT investment is a novel factor introduced in this study to the ITBV research. The authors used survey data of 212 responses collected from CxOs during an economic recession. Empirical results confirmed that all research model factors impacted positively on IT deployment success.
An Interactive Ecosystem of Digital Literacy Services
Authors: Guzmán-Mendoza José Eder , Muñoz-Arteaga Jaime , Muñoz-Zavala Ángel Eduardo , Santaolaya-Salgado René
Published: May 2015

Knowledge Society (KS) is influenced by Information and Communication Technologies (ICT), economic changes, political, cultural and social concepts allowing access to other levels of welfare and progress. However, the differences in terms of access and ICT skills between different groups in society have created a problem of digital divide. To overcome this problem, models and strategies are required to achieve a greater impact on the population and that population can develop skills that enhance inclusion in the society knowledge. This work proposes an Interactive Ecosystem of digital literacy that aims to set a new educational paradigm approach to encourage different learning communities to uses new technologies of information and communication that allows them to be more competitive in today's world and thus shorten the digital divide. Finally, a case study is shown as an implementation of the ecosystem throughout an architectural model in the state of Aguascalientes, México.
Component Based Model Driven Development
Authors: Vera Pablo Martin
Published: May 2015

Current MDD methodologies are complex to use and require doing lots of models and configurations. Usually after all that effort only some part of the application source code can be automatically created. It would be desirable to have a more simple technique, but powerful enough for automatically creating a fully functional application. This works introduces a component based model driven development approach where a set of user interface components will be configured to define system behavior. Component configuration will be direct, simple and supported by a modeling tool which also includes automatic transformations for reducing the modeling task. The methodology requires the designer to build only two models: a class diagram, representing the data model of the application and a component diagram defining the user interface and the system navigation. Both components are based on UML extended with stereotypes and tagged values allowing configuring the system behavior.
Elastic-Plastic Adhesive Contact of Rough Surfaces Based on Accurate FEA Study Using N-Point Asperity Model
Authors: Waghmare Ajay K. , Sahoo Prasanta
Published: May 2015

The paper describes a theoretical study of elastic-plastic adhesive contact of rough surfaces based on n-point asperity model and accurate finite element analysis (FEA) of elastic-plastic deformation of single asperity contact. The n-point asperity model developed by Hariri et al (2006) is integrated with the elastic-plastic model of . In this study an attempt is made to extend the work of by incorporating intermediate elastic-plastic regime of deformation. A large range of interference values ranging from fully elastic through elastic-plastic to fully plastic deformation of contacting asperities is considered. The effect of varying load and material parameters is analyzed in terms of well established adhesion index and plasticity index. A comparison between the present analysis with that of model shows significant difference in load–separation behaviour depending on combinations of mean separation, adhesion index and plasticity index.
Optimization of Friction and Wear Properties of Electroless Ni-P-Al2O3 Composite Coatings
Authors: Sahoo Prasanta , Gadhari Prasanna
Published: May 2015

Electroless Ni-P coatings with hard Al2O3 composite particles are developed on mild steel specimens. The coating parameters viz. source of nickel ions, concentration of reducing agent and concentration of Al2O3 particles are used as coating parameters to minimize wear rate (wear depth in µm) and friction coefficient. As annealing temperature strongly affects hardness and wear resistance of coating, it is considered as fourth parameter. In the present study wear depth and friction coefficient are used as response variables. To convert multiple responses into single performance index, Weighted Principal Component Analysis (WPCA) is used. Taguchi L27 OA with four process parameters at three levels is used to conduct the experiments. ANOVA is used to find out the significance of each coating parameters and their interactions. Annealing temperature is found to be the most significant factor followed by concentration of composite particles. The surface morphology, composition and phase structure analysis are done with the help of SEM, EDAX and XRD respectively.
Use of Sociology Concepts as the Basis of a Model for Context-Aware Computing
Authors: Santos Vitor M.
Published: May 2015

Resorting to mobile devices and their use for Internet access, for georeferentiation and services consumption had a huge increase. Today, these devices ability to establish cooperation networks and to interact intelligently and cooperatively with the surrounding environment has growing importance. In this article the authors present a model where a minimum set of features and information could be embedded in mobile devices to dynamically enable their integration into computer systems with pre-defined formal structure. It is argued that if a device is only partially competent to perform a particular role in a given context, may yet play this role in collaboration with other devices also partly responsible for the performance of this role in this context. This model is inspired by concepts originating in organization theory and sociology as they are typical, the notions of “social role”, “ownership” and “responsibility.” It presented an application example that makes available a formal structure of computation that allows the use of mobile devices with computational skills at a restaurant.
Collaborative Framework for Dynamic Scheduling Supporting in Networked Manufacturing Environments
Authors: Varela Maria Leonilde R. , Santos André S. , Madureira Ana M. , Putnik Goran D. , Cruz-Cunha Maria Manuela
Published: May 2015

Scheduling continues to play an important role in manufacturing systems. It enables the production of suitable scheduling plans, considering shared resources between several different products, through several manufacturing environments including networked ones. High levels of uncertainty characterize networked manufacturing environments. Processes have specific and complex requirements and management requisites, along with diversified objectives, which are dynamic and often conflicting. Dynamic adaptation and a real-time response for manufacturing scheduling is still possible and is critical in this new manufacturing environments, which have a flexible nature, where disturbances on working conditions occur on a continuous and even unexpected basis. Therefore, scheduling systems should have the ability of automatically and intelligently maintain a real-time adaptation and optimization of orders production, to effectively and efficiently adapt these manufacturing environments to the inherent dynamic of markets. In this paper a collaborative framework for supporting dynamic scheduling in networked manufacturing environments is proposed, based on a hyper-organization model and on hyper-heuristics, in order to obtain feasible and robust scheduling plans.
A Novel Ammonic Conversion Algorithm for Securing Data in DNA using Parabolic Encryption
Authors: Jain Shipra , Bhatnagar Vishal
Published: May 2015

In today's era, the traditional cryptographic methods are not sufficient to provide security to the data. Everyone wants to secure their data whether the data is bank transaction, email transaction, personal data or the data related to work. To provide security to the data, DNA cryptography emerges as a new field. DNA cryptography is a new branch of cryptography. It provides security to the data by converting the data in the form of DNA sequence. A lot of research has been done in the area of this cryptography. It consists of various stages like converting data in the form of DNA, reverse conversion, various methods of encryption etc. Various methods of encryption are present until now in the DNA cryptography. But the problem with them is that they all have more emphasis on biological encryption methods. There is a need of methods which make use of simple biological methods and complex binary or other number system encryption. In this paper, the authors are proposing a new algorithm for providing security to the data at two levels. The authors propose a parabolic transposition in a circular arrangement of data. In the proposed algorithm, data is arranged in a circular way. The number of rows and columns acts as a key for binary encryption. For encrypting the DNA sequence, the authors convert the DNA sequence into amino acid. This amino acid sequence will act as a cipher text and send to the receiver through the open environment. The proposed algorithm is a type of block cipher. It is a transposition cipher. It changes the position of data for binary encryption.
Seeding rate and cultivar effects on yield, yield components and grain quality of spring spelt in eastern Canada
Authors: Dorval Isabelle , Vanasse Anne , Pageau Denis , Dion Yves
Published: May 2015

Dorval, I., Vanasse, A., Pageau, D. and Dion, Y. 2015. Seeding rate and cultivar effects on yield, yield components and grain quality of spring spelt in eastern Canada. Can. J. Plant. Sci. 95: 841–849. There is currently an increasing demand from master millers for spelt (Triticum aestivum ssp. spelta), but little is known about crop management of spring spelt under the eastern Canadian climate in organic or low-input systems. Field experiments were carried out at three sites in Quebec from 2011 to 2013 to assess the effect of cultivar (CDC Origin, CDC Zorba, CDC Nexon, CDC Silex) and seeding rate (250, 300, 350, 400 and 450 grains m−2) on grain and straw yields, yield components and some grain quality characteristics of spelt. CDC Origin produced higher hulled grain yields at all sites, while CDC Silex produced similar hulled grain yields and achieved the highest naked grain yields at two of the three test sites. The hull content varied from 24.0 to 37.6% among cultivars. CDC Origin had the highest hull content at each site. The seeding rate generally had no effect on yields, but had an effect on yield components; increasing seeding rates slightly increased the number of spikes per square metre and decreased the number of grains per spike, while the 1000-grain weight remained unaffected. Protein content of all cultivars was high (14.2 to 15.4%), while falling number varied from 219 to 385 s.
AAC Elevate hard red winter wheat
Authors: Graf R. J. , Beres B. L. , Randhawa H. S. , Gaudet D. A. , Laroche A. , Eudes F.
Published: May 2015

Graf, R. J., Beres, B. L., Randhawa, H. S., Gaudet, D. A., Laroche, A. and Eudes, F. 2015. AAC Elevate hard red winter wheat. Can. J. Plant Sci. 95: 1021–1027. AAC Elevate is a hard red winter wheat (Triticum aestivum L.) cultivar that is well adapted across western Canada and eligible for all grades of the Canada Western Red Winter (CWRW) wheat class. It was developed using wheat×maize-pollen doubled haploid methodology. AAC Elevate was evaluated in the Western Winter Wheat Cooperative Registration trials relative to CDC Osprey, AC Bellatrix, Radiant and CDC Buteo for 3 yr (2011–2013), with Flourish and Moats added as checks in the latter 2 yr. Based on these 35 replicated trials, AAC Elevate produced higher grain yield than all of the checks (103.3–114.4%) and exhibited good winter survival, medium height with excellent straw strength, large kernels, acceptable end-use quality, and broad disease resistance. AAC Elevate expressed moderate resistance to stem rust and common bunt, intermediate resistance to leaf rust, stripe rust and Fusarium head blight, and resistance to colonization by the wheat curl mite vector for wheat streak mosaic virus.
Strongly Summable Ultrafilters, Union Ultrafilters, and the Trivial Sums Property
Authors: Fernández Bretón David J.
Published: May 2015

We answer two questions of Hindman, Steprāns, and Strauss; namely, we prove that every strongly summable ultrafilter on an abelian group is sparse and has the trivial sums property. Moreover, we show that in most cases the sparseness of the given ultrafilter is a consequence of its being isomorphic to a union ultrafilter. However, this does not happen in all cases; we also construct (assuming Martin's Axiom for countable partial orders, i.e., , a strongly summable ultrafilter on the Boolean group that is not additively isomorphic to any union ultrafilter.
The ENSO signal in atmospheric composition fields: emission driven vs. dynamically induced changes
Authors: Inness A. , Benedetti A. , Flemming J. , Huijnen V. , Kaiser J. W. , Parrington M. , Remy S.
Published: May 2015

Abstract. The El Niño Southern Oscillation (ENSO) does not only affect meteorological fields but also has a large impact on atmospheric composition. Atmospheric composition fields from the Monitoring Atmospheric Composition and Climate (MACC) reanalysis are used to identify the ENSO signal in tropospheric ozone, carbon monoxide, nitrogen oxide and smoke aerosols, concentrating on the months October to December. During El Niño years all these fields have increased concentrations over maritime South East Asia in October. The MACC Composition Integrated Forecasting System (C-IFS) model is used to quantify the relative magnitude of dynamically induced and emission driven changes in the atmospheric composition fields. While changes in tropospheric ozone are a combination of dynamically induced and emission driven changes, the changes in carbon monoxide, nitrogen oxide and smoke aerosols are almost entirely emission driven in the MACC model. The ozone changes continue into December, i.e. after the end of the Indonesian fire season while changes in the other fields are confined to the fire season.
Impact of 2050 climate change on North American wildfire: consequences for ozone air quality
Authors: Yue X. , Mickley L. J. , Logan J. A. , Hudman R. C. , Val Martin M. , Yantosca R. M.
Published: May 2015

Abstract. We estimate future area burned in Alaskan and Canadian forest by the midcentury (2046–2065) based on the simulated meteorology from 13 climate models under the A1B scenario. We develop ecoregion-dependent regressions using observed relationships between annual total area burned and a suite of meteorological variables and fire weather indices, and apply these regressions to the simulated meteorology. We find that for Alaska and western Canada almost all models predict significant (p < 0.05) increases in area burned at the midcentury, with median values ranging from 150 to 390%, depending on the ecoregion. Such changes are attributed to the higher surface air temperatures and 500 hPa geopotential heights relative to present day, which together lead to favorable conditions for wildfire spread. Elsewhere the model predictions are not as robust. For the central and southern Canadian ecoregions, the models predict increases in area burned of 45–90%. Except for the Taiga Plain, where area burned decreases by 50%, no robust trends are found in northern Canada, due to the competing effects of hotter weather and wetter conditions there. Using the GEOS-Chem chemical transport model, we find that changes in wildfire emissions alone increase mean summertime surface ozone levels by 5 ppbv for Alaska, 3 ppbv for Canada, and 1 ppbv for the western US by the midcentury. In the northwestern US states, local wildfire emissions at midcentury enhance surface ozone by an average of 1 ppbv, while transport of boreal fire pollution further degrades ozone air quality by an additional 0.5 ppbv. The projected changes in wildfire activity increase daily summertime surface ozone above the 95th percentile by 1 ppbv in the northwestern US, 5 ppbv in the high latitudes of Canada, and 15 ppbv in Alaska, suggesting a greater frequency of pollution episodes in the future atmosphere.
Explorative study on GOME-2 total column ozone retrievals and the validation with ground-based and balloon measurements
Authors: Wassmann A. , Borsdorff T. , aan de Brugh J. M. J. , Hasekamp O. P. , Aben I. , Landgraf J.
Published: May 2015

Abstract. In this work we present an extensive sensitivity study of retrieved total ozone columns from clear sky Global Ozone Monitoring Experiment 2 (GOME-2) measurements between 325 and 335nm which are corrected for instrument degradation. Employing an algorithm based on the scaling of a reference ozone profile with the extension to analytically calculate total column averaging kernels, allows us to investigate the impact of the choice of the reference profile on the retrieved total ozone column, since it represents a regularization of the retrieval. It introduces an error to the retrieved column with respect to the true column typically in the order of 1% depending on the reference scaling profile. However, a proper interpretation of the retrieved column using the total column averaging kernel avoids this error, which is demonstrated by a validation of GOME-2 total ozone columns with collocated ozonesonde and ground-based total ozone column measurements. Globally, we report a bias of 0.1% and a SD of 2.5% for 647 collocations with ground-based and ozonesonde measurements at different geolocations in the period of 2007 to 2010. Futhermore, an extended validation solely based on ground-based observations and a strict cloud filtering shows that the use of pseudo spherical scalar radiative transfer is fully sufficient for the purpose of this retrieval. Polarization of light by atmospheric scattering affects the retrieval accuracy only marginally and thus can be ignored. Finally, we study the effect of instrument degradation on the retrieved total ozone columns for the first four years of GOME-2 observations and discuss the efficiency of the proposed radiometric correction.
Including high frequency variability in coastal ocean acidification projections
Authors: Takeshita Y. , Frieder C. A. , Martz T. R. , Ballard J. R. , Feely R. A. , Kram S. , Nam S. , Navarro M. O. , Price N. N. , Smith J. E.
Published: May 2015

Abstract. Assessing the impacts of anthropogenic ocean acidification requires knowledge of present-day and future environmental conditions. Here, we present a simple model for upwelling margins that projects anthropogenic acidification trajectories by combining high-temporal resolution sensor data, hydrographic surveys for source water characterization, empirical relationships of the CO2 system, and the atmospheric CO2 record. This model characterizes CO2 variability on timescales ranging from hours (e.g. tidal) to months (e.g. seasonal), bridging a critical knowledge gap in ocean acidification research. The amount of anthropogenic carbon in a given water mass is dependent on the age, therefore a density–age relationship was derived for the study region, and was combined with the 2013 Intergovernmental Panel on Climate Change CO2 emission scenarios to add density-dependent anthropogenic carbon to the sensor time series. The model was applied to time series from four autonomous pH sensors, each deployed in the surf zone, kelp forest, submarine canyon edge, and shelf break in the upper 100 m of the Southern California Bight. All habitats were within 5 km of one another, and exhibited unique, habitat-specific CO2 variability signatures and acidification trajectories, demonstrating the importance of making projections in the context of habitat-specific CO2 signatures. In general, both the mean and range of pCO2 increase in the future, with the greatest increases in both magnitude and range occurring in the deeper habitats due to reduced buffering capacity. On the other hand, the saturation state of aragonite (ΩAr) decreased in both magnitude and range. This approach can be applied to the entire California Current System, and upwelling margins in general, where sensor and complementary hydrographic data are available.
Hydrography in the Mediterranean Sea during a cruise with RV POSEIDON in April 2014
Authors: Hainbucher D. , Cardin V. , Siena G. , Hübner U. , Moritz M. , Drübbisch U. , Basan F.
Published: May 2015

Abstract. We report on data from an oceanographic cruise in the Mediterranean Sea on the German research vessel POSEIDON in April 2014. Data were taken on a west–east section starting at the Strait of Gibraltar and ending south-east of Crete as well on sections in the Ionian and Adriatic Sea. The objectives of the cruise were twofold; long-term variations of the Levantine Intermediate Water (LIW) and the deep water masses of the Eastern Mediterranean Sea were investigated. The measurements include salinity, temperature, oxygen and currents and were conducted with a CTD/rosette system, an underway CTD and an ADCP. The sections are on tracks which have been sampled during several other cruises, thus supporting the opportunity to investigate the long term temporal development of the different variables. The use of an underway CTD made it possible to conduct measurements of temperature and salinity with a high resolution of 6 nm and a vertical resolution of 1 dbar for the upper 800 m of the water column.
Development and evaluation of the Screening Trajectory Ozone Prediction System (STOPS, version 1.0)
Authors: Czader B. H. , Percell P. , Byun D. , Kim S. , Choi Y.
Published: May 2015

Abstract. A hybrid Lagrangian–Eulerian based modeling tool has been developed using the Eulerian framework of the Community Multiscale Air Quality (CMAQ) model. It is a moving nest that utilizes saved original CMAQ simulation results to provide boundary conditions, initial conditions, as well as emissions and meteorological parameters necessary for a simulation. Given that these files are available, this tool can run independently of the CMAQ whole domain simulation, and it is designed to simulate source–receptor relationships upon changes in emissions. In this tool, the original CMAQ's horizontal domain is reduced to a small sub-domain that follows a trajectory defined by the mean mixed-layer wind. It has the same vertical structure and physical and chemical interactions as CMAQ except advection calculation. The advantage of this tool compared to other Lagrangian models is its capability of utilizing realistic boundary conditions that change with space and time as well as detailed chemistry treatment. The correctness of the algorithms and the overall performance was evaluated against CMAQ simulation results. Its performance depends on the atmospheric conditions occurring during the simulation period, with the comparisons being most similar to CMAQ results under uniform wind conditions. The mean bias for surface ozone mixing ratios varies between −0.03 and −0.78 ppbV and the slope is between 0.99 and 1.01 for different analyzed cases. For complicated meteorological conditions, such as wind circulation, the simulated mixing ratios deviate from CMAQ values as a result of the Lagrangian approach of using mean wind for its movement, but are still close, with the mean bias for ozone varying between 0.07 and −4.29 ppbV and the slope varying between 0.95 and 1.06 for different analyzed cases. For historical reasons, this hybrid Lagrangian–Eulerian based tool is named the Screening Trajectory Ozone Prediction System (STOPS), but its use is not limited to ozone prediction as, similarly to CMAQ, it can simulate concentrations of many species, including particulate matter and some toxic compounds, such as formaldehyde and 1,3-butadiene.
Simulations and parameterisation of shallow volcanic plumes of Piton de la Fournaise, Réunion Island, using Méso-NH version 4-9-3
Authors: Sivia S. G. , Gheusi F. , Mari C. , Di Muro A.
Published: May 2015

Abstract. In mesoscale models (resolution ~ 1 km) used for regional dispersion of pollution plumes the volcanic heat sources and emissions of gases and aerosols, as well as the induced atmospheric convective motions, are all sub-grid-scale processes (mostly true for weak effusive eruptions) which need to be parameterised. We propose a modified formulation of the EDMF scheme (eddy diffusivity/mass flux) proposed by Pergaud et al. (2009) which is based on a single sub-grid updraft model. It is used to represent volcano induced updrafts tested for a case study of the January 2010 summit eruption of Piton de la Fournaise (PdF) volcano. The validation of this modified formulation using a reference large eddy simulation (LES) focuses on the ability of the model to transport tracer concentrations up to 1–2 km above the ground in the lower troposphere as is the case of majority of PdF eruptions. The modelled volcanic plume agrees reasonably with the profiles of SO2 (sulfur dioxide) tracer concentrations and specific humidity found from the reference LES. Sensitivity tests performed for the modified formulation of the EDMF scheme emphasise the sensitivity of the parameterisation to ambient fresh air entrainment at the plume base.
Reducing structural uncertainty in conceptual hydrological modelling in the semi-arid Andes
Authors: Hublart P. , Ruelland D. , Dezetter A. , Jourde H.
Published: May 2015

Abstract. The use of lumped, conceptual models in hydrological impact studies requires placing more emphasis on the uncertainty arising from deficiencies and/or ambiguities in the model structure. This study provides an opportunity to combine a multiple-hypothesis framework with a multi-criteria assessment scheme to reduce structural uncertainty in the conceptual modelling of a mesoscale Andean catchment (1515 km2) over a 30-year period (1982–2011). The modelling process was decomposed into six model-building decisions related to the following aspects of the system behaviour: snow accumulation and melt, runoff generation, redistribution and delay of water fluxes, and natural storage effects. Each of these decisions was provided with a set of alternative modelling options, resulting in a total of 72 competing model structures. These structures were calibrated using the concept of Pareto optimality with three criteria pertaining to streamflow simulations and one to the seasonal dynamics of snow processes. The results were analyzed in the four-dimensional (4-D) space of performance measures using a fuzzy c-means clustering technique and a differential split sample test, leading to identify 14 equally acceptable model hypotheses. A filtering approach was then applied to these best-performing structures in order to minimize the overall uncertainty envelope while maximizing the number of enclosed observations. This led to retain eight model hypotheses as a representation of the minimum structural uncertainty that could be obtained with this modelling framework. Future work to better consider model predictive uncertainty should include a proper assessment of parameter equifinality and data errors, as well as the testing of new or refined hypotheses to allow for the use of additional auxiliary observations.
Estimation of crop water requirements: extending the one-step approach to dual crop coefficients
Authors: Lhomme J. P. , Boudhina N. , Masmoudi M. M. , Chehbouni A.
Published: May 2015

Abstract. Crop water requirements are commonly estimated with the FAO-56 methodology based upon a "two-step" approach: first a reference evapotranspiration (ET0) is calculated from weather variables with the Penman–Monteith equation; then ET0 is multiplied by a tabulated crop-specific coefficient (Kc) to determine the water requirement (ETc) of a given crop under standard conditions. This method has been challenged to the benefit of a "one-step" approach, where crop evapotranspiration is directly calculated from a Penman–Monteith equation, its surface resistance replacing the crop coefficient. Whereas the transformation of the two-step approach into a one-step approach has been well documented when a single crop coefficient (Kc) is used, the case of dual crop coefficients (Kcb for the crop and Ke for the soil) has not been treated yet. The present paper examines this specific case. Using a full two-layer model as a reference, it is shown that the FAO-56 dual crop coefficient approach can be translated into a one-step approach based upon a modified combination equation. This equation has the basic form of the Penman–Monteith equation, but its surface resistance is calculated as the parallel sum of a foliage resistance (replacing Kcb) and a soil surface resistance (replacing Ke). We also show that the foliage resistance, which depends on leaf stomatal resistance and leaf area, can be inferred from the basal crop coefficient (Kcb) in a way similar to the Matt–Shuttleworth method.
MULTI SENSOR DATA INTEGRATION FOR AN ACCURATE 3D MODEL GENERATION
Authors: Chhatkuli S. , Satoh T. , Tachibana K.
Published: May 2015

Abstract. The aim of this paper is to introduce a novel technique of data integration between two different data sets, i.e. laser scanned RGB point cloud and oblique imageries derived 3D model, to create a 3D model with more details and better accuracy. In general, aerial imageries are used to create a 3D city model. Aerial imageries produce an overall decent 3D city models and generally suit to generate 3D model of building roof and some non-complex terrain. However, the automatically generated 3D model, from aerial imageries, generally suffers from the lack of accuracy in deriving the 3D model of road under the bridges, details under tree canopy, isolated trees, etc. Moreover, the automatically generated 3D model from aerial imageries also suffers from undulated road surfaces, non-conforming building shapes, loss of minute details like street furniture, etc. in many cases. On the other hand, laser scanned data and images taken from mobile vehicle platform can produce more detailed 3D road model, street furniture model, 3D model of details under bridge, etc. However, laser scanned data and images from mobile vehicle are not suitable to acquire detailed 3D model of tall buildings, roof tops, and so forth. Our proposed approach to integrate multi sensor data compensated each other’s weakness and helped to create a very detailed 3D model with better accuracy. Moreover, the additional details like isolated trees, street furniture, etc. which were missing in the original 3D model derived from aerial imageries could also be integrated in the final model automatically. During the process, the noise in the laser scanned data for example people, vehicles etc. on the road were also automatically removed. Hence, even though the two dataset were acquired in different time period the integrated data set or the final 3D model was generally noise free and without unnecessary details.
AUTOMATIC EXTRACTION OF ROAD SURFACE AND CURBSTONE EDGES FROM MOBILE LASER SCANNING DATA
Authors: Miraliakbari A. , Hahn M. , Sok S.
Published: May 2015

Abstract. We present a procedure for automatic extraction of the road surface from geo-referenced mobile laser scanning data. The basic assumption of the procedure is that the road surface is smooth and limited by curbstones. Two variants of jump detection are investigated for detecting curbstone edges, one based on height differences the other one based on histograms of the height data. Region growing algorithms are proposed which use the irregular laser point cloud. Two- and four-neighbourhood growing strategies utilize the two height criteria for examining the neighborhood. Both height criteria rely on an assumption about the minimum height of a low curbstone. Road boundaries with lower or no jumps will not stop the region growing process. In contrast to this objects on the road can terminate the process. Therefore further processing such as bridging gaps between detected road boundary points and the removal of wrongly detected curbstone edges is necessary. Road boundaries are finally approximated by splines. Experiments are carried out with a ca. 2 km network of smalls streets located in the neighbourhood of University of Applied Sciences in Stuttgart. For accuracy assessment of the extracted road surfaces, ground truth measurements are digitized manually from the laser scanner data. For completeness and correctness of the region growing result values between 92% and 95% are achieved.
QUALIFICATION OF POINT CLOUDS MEASURED BY SFM SOFTWARE
Authors: Oda K. , Hattori S. , Saeki H. , Takayama T. , Honma R.
Published: May 2015

Abstract. This paper proposes a qualification method of a point cloud created by SfM (Structure-from-Motion) software. Recently, SfM software is popular for creating point clouds. Point clouds created by SfM Software seems to be correct, but in many cases, the result does not have correct scale, or does not have correct coordinates in reference coordinate system, and in these cases it is hard to evaluate the quality of the point clouds. To evaluate this correctness of the point clouds, we propose to use the difference between point clouds with different source of images. If the shape of the point clouds with different source of images is correct, two shapes of different source might be almost same. To compare the two or more shapes of point cloud, iterative-closest-point (ICP) is implemented. Transformation parameters (rotation and translation) are iteratively calculated so as to minimize sum of squares of distances. This paper describes the procedure of the evaluation and some test results.
CREATING PRODUCT MODELS FROM POINT CLOUD OF CIVIL STRUCTURES BASED ON GEOMETRIC SIMILARITY
Authors: Hidaka N. , Michikawa T. , Yabuki N. , Fukuda T. , Motamedi A.
Published: May 2015

Abstract. The existing civil structures must be maintained in order to ensure their expected lifelong serviceability. Careful rehabilitation and maintenance planning plays a significant role in that effort. Recently, construction information modelling (CIM) techniques, such as product models, are increasingly being used to facilitate structure maintenance. Using this methodology, laser scanning systems can provide point cloud data that are used to produce highly accurate and dense representations of civil structures. However, while numerous methods for creating a single surface exist, part decomposition is required in order to create product models consisting of more than one part. This research aims at the development of a surface reconstruction system that utilizes point cloud data efficiently in order to create complete product models. The research proposes using the application of local shape matching to the input point clouds in order to define a set of representative parts. These representative parts are then polygonized and copied to locations where the same types of parts exist. The results of our experiments show that the proposed method can efficiently create product models using input point cloud data.
APPLICATIONS OF PANORAMIC IMAGES: FROM 720° PANORAMA TO INTERIOR 3D MODELS OF AUGMENTED REALITY
Authors: Lee I.-C. , Tsai F.
Published: May 2015

Abstract. A series of panoramic images are usually used to generate a 720° panorama image. Although panoramic images are typically used for establishing tour guiding systems, in this research, we demonstrate the potential of using panoramic images acquired from multiple sites to create not only 720° panorama, but also three-dimensional (3D) point clouds and 3D indoor models. Since 3D modeling is one of the goals of this research, the location of the panoramic sites needed to be carefully planned in order to maintain a robust result for close-range photogrammetry. After the images are acquired, panoramic images are processed into 720° panoramas, and these panoramas which can be used directly as panorama guiding systems or other applications. In addition to these straightforward applications, interior orientation parameters can also be estimated while generating 720° panorama. These parameters are focal length, principle point, and lens radial distortion. The panoramic images can then be processed with closerange photogrammetry procedures to extract the exterior orientation parameters and generate 3D point clouds. In this research, VisaulSFM, a structure from motion software is used to estimate the exterior orientation, and CMVS toolkit is used to generate 3D point clouds. Next, the 3D point clouds are used as references to create building interior models. In this research, Trimble Sketchup was used to build the model, and the 3D point cloud was added to the determining of locations of building objects using plane finding procedure. In the texturing process, the panorama images are used as the data source for creating model textures. This 3D indoor model was used as an Augmented Reality model replacing a guide map or a floor plan commonly used in an on-line touring guide system. The 3D indoor model generating procedure has been utilized in two research projects: a cultural heritage site at Kinmen, and Taipei Main Station pedestrian zone guidance and navigation system. The results presented in this paper demonstrate the potential of using panoramic images to generate 3D point clouds and 3D models. However, it is currently a manual and labor-intensive process. A research is being carried out to Increase the degree of automation of these procedures.
IMAGE-BASED LOCALIZATION FOR INDOOR ENVIRONMENT USING MOBILE PHONE
Authors: Huang Y. , Wang H. , Zhan K. , Zhao J. , Gui P. , Feng T.
Published: May 2015

Abstract. Real-time indoor localization based on supporting infrastructures like wireless devices and QR codes are usually costly and labor intensive to implement. In this study, we explored a cheap alternative approach based on images for indoor localization. A user can localize him/herself by just shooting a photo of the surrounding indoor environment using the mobile phone. No any other equipment is required. This is achieved by employing image-matching and searching techniques with a dataset of pre-captured indoor images. In the beginning, a database of structured images of the indoor environment is constructed by using image matching and the bundle adjustment algorithm. Then each image’s relative pose (its position and orientation) is estimated and the semantic locations of images are tagged. A user’s location can then be determined by comparing a photo taken by the mobile phone to the database. This is done by combining quick image searching, matching and the relative orientation. This study also try to explore image acquisition plans and the processing capacity of off-the-shell mobile phones. During the whole pipeline, a collection of indoor images with both rich and poor textures are examined. Several feature detectors are used and compared. Pre-processing of complex indoor photo is also implemented on the mobile phone. The preliminary experimental results prove the feasibility of this method. In the future, we are trying to raise the efficiency of matching between indoor images and explore the fast 4G wireless communication to ensure the speed and accuracy of the localization based on a client-server framework.
CAMERA CALIBRATION IN 3D MODELLING FOR UAV APPLICATION
Authors: Yanagi H. , Chikatsu H.
Published: May 2015

Abstract. In recent times, small types of Unmanned Aerial Vehicles (UAVs) have been receiving attention in areas such as 3D modelling, maintenance engineering, and personal interest (hobby) usage. However, the payload a small type of UAV is able to carry is limited. Given these circumstances, small consumer grade digital cameras are often used for UAV photogrammetry with small types of UAV. Though, digital photogrammetry using the consumer grade cameras is enormously expected in various application fields such as UAV photogrammetry. There is a large body of literature on camera calibration. However, the lens distortion of small consumer grade digital cameras is still an issue from the viewpoint of accuracy aspect. The authors have been investigating camera calibration using various cameras. However, small consumer grade digital cameras, which is called as entry-cameras, have an accuracy degradation problem. The issue was addressed by conducting calibration tests using two kinds of consumer grade digital cameras, each with a resolution of 12 mega pixels. This paper presents the results of an investigation into the cause of accuracy degradation in digital photogrammetry using entry-cameras.
DRAWING AND LANDSCAPE SIMULATION FOR JAPANESE GARDEN BY USING TERRESTRIAL LASER SCANNER
Authors: Kumazaki R. , Kunii Y.
Published: May 2015

Abstract. Recently, many laser scanners are applied for various measurement fields. This paper investigates that it was useful to use the terrestrial laser scanner in the field of landscape architecture and examined a usage in Japanese garden. As for the use of 3D point cloud data in the Japanese garden, it is the visual use such as the animations. Therefore, some applications of the 3D point cloud data was investigated that are as follows. Firstly, ortho image of the Japanese garden could be outputted for the 3D point cloud data. Secondly, contour lines of the Japanese garden also could be extracted, and drawing was became possible. Consequently, drawing of Japanese garden was realized more efficiency due to achievement of laborsaving. Moreover, operation of the measurement and drawing could be performed without technical skills, and any observers can be operated. Furthermore, 3D point cloud data could be edited, and some landscape simulations that extraction and placement of tree or some objects were became possible. As a result, it can be said that the terrestrial laser scanner will be applied in landscape architecture field more widely.
VIDEO-BASED POINT CLOUD GENERATION USING MULTIPLE ACTION CAMERAS
Authors: Teo T.
Published: May 2015

Abstract. Due to the development of action cameras, the use of video technology for collecting geo-spatial data becomes an important trend. The objective of this study is to compare the image-mode and video-mode of multiple action cameras for 3D point clouds generation. Frame images are acquired from discrete camera stations while videos are taken from continuous trajectories. The proposed method includes five major parts: (1) camera calibration, (2) video conversion and alignment, (3) orientation modelling, (4) dense matching, and (5) evaluation. As the action cameras usually have large FOV in wide viewing mode, camera calibration plays an important role to calibrate the effect of lens distortion before image matching. Once the camera has been calibrated, the author use these action cameras to take video in an indoor environment. The videos are further converted into multiple frame images based on the frame rates. In order to overcome the time synchronous issues in between videos from different viewpoints, an additional timer APP is used to determine the time shift factor between cameras in time alignment. A structure form motion (SfM) technique is utilized to obtain the image orientations. Then, semi-global matching (SGM) algorithm is adopted to obtain dense 3D point clouds. The preliminary results indicated that the 3D points from 4K video are similar to 12MP images, but the data acquisition performance of 4K video is more efficient than 12MP digital images.
IMPROVEMENT OF 3D MONTE CARLO LOCALIZATION USING A DEPTH CAMERA AND TERRESTRIAL LASER SCANNER
Authors: Kanai S. , Hatakeyama R. , Date H.
Published: May 2015

Abstract. Effective and accurate localization method in three-dimensional indoor environments is a key requirement for indoor navigation and lifelong robotic assistance. So far, Monte Carlo Localization (MCL) has given one of the promising solutions for the indoor localization methods. Previous work of MCL has been mostly limited to 2D motion estimation in a planar map, and a few 3D MCL approaches have been recently proposed. However, their localization accuracy and efficiency still remain at an unsatisfactory level (a few hundreds millimetre error at up to a few FPS) or is not fully verified with the precise ground truth. Therefore, the purpose of this study is to improve an accuracy and efficiency of 6DOF motion estimation in 3D MCL for indoor localization. Firstly, a terrestrial laser scanner is used for creating a precise 3D mesh model as an environment map, and a professional-level depth camera is installed as an outer sensor. GPU scene simulation is also introduced to upgrade the speed of prediction phase in MCL. Moreover, for further improvement, GPGPU programming is implemented to realize further speed up of the likelihood estimation phase, and anisotropic particle propagation is introduced into MCL based on the observations from an inertia sensor. Improvements in the localization accuracy and efficiency are verified by the comparison with a previous MCL method. As a result, it was confirmed that GPGPU-based algorithm was effective in increasing the computational efficiency to 10-50 FPS when the number of particles remain below a few hundreds. On the other hand, inertia sensor-based algorithm reduced the localization error to a median of 47mm even with less number of particles. The results showed that our proposed 3D MCL method outperforms the previous one in accuracy and efficiency.
RESEARCH ON EXTENSION OF SPARQL ONTOLOGY QUERY LANGUAGE CONSIDERING THE COMPUTATION OF INDOOR SPATIAL RELATIONS
Authors: Li C. , Zhu X. , Guo W. , Liu Y. , Huang H.
Published: May 2015

Abstract. A method suitable for indoor complex semantic query considering the computation of indoor spatial relations is provided According to the characteristics of indoor space. This paper designs ontology model describing the space related information of humans, events and Indoor space objects (e.g. Storey and Room) as well as their relations to meet the indoor semantic query. The ontology concepts are used in IndoorSPARQL query language which extends SPARQL syntax for representing and querying indoor space. And four types specific primitives for indoor query, "Adjacent", "Opposite", "Vertical" and "Contain", are defined as query functions in IndoorSPARQL used to support quantitative spatial computations. Also a method is proposed to analysis the query language. Finally this paper adopts this method to realize indoor semantic query on the study area through constructing the ontology model for the study building. The experimental results show that the method proposed in this paper can effectively support complex indoor space semantic query.
LEVERAGING SPATIAL MODEL TO IMPROVE INDOOR TRACKING
Authors: Liu L. , Xu W. , Penard W. , Zlatanova S.
Published: May 2015

Abstract. In this paper, we leverage spatial model to process indoor localization results and then improve the track consisting of measured locations. We elaborate different parts of spatial model such as geometry, topology and semantics, and then present how they contribute to the processing of indoor tracks. The initial results of our experiment reveal that spatial model can support us to overcome problems such as tracks intersecting with obstacles and unstable shifts between two location measurements. In the future, we will investigate more exceptions of indoor tracking results and then develop additional spatial methods to reduce errors of indoor tracks.