bluuebunny/crossref_metadata_2025 huggingface dataset:
Modeling soil CO2 production and transport with dynamic source and diffusion terms: testing the steady-state assumption using DETECT v1.0
Authors: Ryan Edmund M. , Ogle Kiona , Kropp Heather , Samuels-Crow Kimberly E. , Carrillo Yolima , Pendall Elise
Published: May 2018

Abstract. The flux of CO2 from the soil to the atmosphere (soil respiration,
Rsoil) is a major component of the global carbon (C) cycle.
Methods to measure and model Rsoil, or partition it into
different components, often rely on the assumption that soil CO2
concentrations and fluxes are in steady state, implying that
Rsoil is equal to the rate at which CO2 is produced by soil
microbial and root respiration. Recent research, however, questions the
validity of this assumption. Thus, the aim of this work was two-fold: (1) to
describe a non-steady state (NSS) soil CO2 transport and production
model, DETECT, and (2) to use this model to evaluate the environmental
conditions under which Rsoil and CO2 production are likely
in NSS. The backbone of DETECT is a non-homogeneous, partial differential
equation (PDE) that describes production and transport of soil CO2,
which we solve numerically at fine spatial and temporal resolution (e.g.,
0.01 m increments down to 1 m, every 6 h). Production of soil CO2 is
simulated for every depth and time increment as the sum of root respiration
and microbial decomposition of soil organic matter. Both of these factors can
be driven by current and antecedent soil water content and temperature, which
can also vary by time and depth. We also analytically solved the ordinary
differential equation (ODE) corresponding to the steady-state (SS) solution
to the PDE model. We applied the DETECT NSS and SS models to the six-month
growing season period representative of a native grassland in Wyoming.
Simulation experiments were conducted with both model versions to evaluate
factors that could affect departure from SS, such as (1) varying soil
texture; (2) shifting the timing or frequency of precipitation; and (3) with
and without the environmental antecedent drivers. For a coarse-textured soil,
Rsoil from the SS model closely matched that of the NSS model.
However, in a fine-textured (clay) soil, growing season Rsoil was
∼ 3 % higher under the assumption of NSS (versus SS). These
differences were exaggerated in clay soil at daily time scales whereby
Rsoil under the SS assumption deviated from NSS by up to 35 % on average in the 10 days
following a major precipitation event. Incorporation of antecedent drivers
increased the magnitude of Rsoil by 15 to 37 % for coarse- and
fine-textured soils, respectively. However, the responses of
Rsoil to the timing of precipitation and antecedent drivers did
not differ between SS and NSS assumptions. In summary, the assumption of SS
conditions can be violated depending on soil type and soil moisture status,
as affected by precipitation inputs. The DETECT model provides a framework
for accommodating NSS conditions to better predict Rsoil and
associated soil carbon cycling processes.
Dealing with non-stationarity in sub-daily stochastic rainfall models
Authors: Benoit Lionel , Vrac Mathieu , Mariethoz Gregoire
Published: May 2018

Abstract. Understanding the stationarity properties of rainfall is critical when using stochastic weather generators. Rainfall stationarity means that the statistics being accounted for remain constant over a given period, which is required for both inferring model parameters and simulating synthetic rainfall. Despite its critical importance, the stationarity of precipitation statistics is often regarded as a subjective choice whose examination is left to the judgement of the modeler. It is therefore desirable to establish quantitative and objective criteria for defining stationary rain periods. To this end, we propose a methodology that automatically identifies rain types with homogeneous statistics. It is based on an unsupervised classification of the space–time–intensity structure of weather radar images. The transitions between rain types are interpreted as non-stationarities. Our method is particularly suited to deal with non-stationarity in the context of sub-daily stochastic rainfall models. Results of a synthetic case study show that the proposed approach is able to reliably identify synthetically generated rain types. The application of rain typing to real data indicates that non-stationarity can be significant within meteorological seasons, and even within a single storm. This highlights the need for a careful examination of the temporal stationarity of precipitation statistics when modelling rainfall at high resolution.
TOWARD AUTOMATIC GEOREFERENCING OF ARCHIVAL AERIAL PHOTOGRAMMETRIC SURVEYS
Authors: Giordano S. , Le Bris A. , Mallet C.
Published: May 2018

Abstract. Images from archival aerial photogrammetric surveys are a unique and relatively unexplored means to chronicle 3D land-cover changes over the past 100 years. They provide a relatively dense temporal sampling of the territories with very high spatial resolution. Such time series image analysis is a mandatory baseline for a large variety of long-term environmental monitoring studies. The current bottleneck for accurate comparison between epochs is their fine georeferencing step. No fully automatic method has been proposed yet and existing studies are rather limited in terms of area and number of dates. State-of-the art shows that the major challenge is the identification of ground references: cartographic coordinates and their position in the archival images. This task is manually performed, and extremely time-consuming. This paper proposes to use a photogrammetric approach, and states that the 3D information that can be computed is the key to full automation. Its original idea lies in a 2-step approach: (i) the computation of a coarse absolute image orientation; (ii) the use of the coarse Digital Surface Model (DSM) information for automatic absolute image orientation. It only relies on a recent orthoimage+DSM, used as master reference for all epochs. The coarse orthoimage, compared with such a reference, allows the identification of dense ground references and the coarse DSM provides their position in the archival images. Results on two areas and 5 dates show that this method is compatible with long and dense archival aerial image series. Satisfactory planimetric and altimetric accuracies are reported, with variations depending on the ground sampling distance of the images and the location of the Ground Control Points.
SENSOR-TOPOLOGY BASED SIMPLICIAL COMPLEX RECONSTRUCTION FROM MOBILE LASER SCANNING
Authors: Guinard S. , Vallet B.
Published: May 2018

Abstract. We propose a new method for the reconstruction of simplicial complexes (combining points, edges and triangles) from 3D point clouds from Mobile Laser Scanning (MLS). Our main goal is to produce a reconstruction of a scene that is adapted to the local geometry of objects. Our method uses the inherent topology of the MLS sensor to define a spatial adjacency relationship between points. We then investigate each possible connexion between adjacent points and filter them by searching collinear structures in the scene, or structures perpendicular to the laser beams. Next, we create triangles for each triplet of self-connected edges. Last, we improve this method with a regularization based on the co-planarity of triangles and collinearity of remaining edges. We compare our results to a naive simplicial complexes reconstruction based on edge length.
INVESTIGATION OF JOINT VISIBILITY BETWEEN SAR AND OPTICAL IMAGES OF URBAN ENVIRONMENTS
Authors: Hughes L. H. , Auer S. , Schmitt M.
Published: May 2018

Abstract. In this paper, we present a work-flow to investigate the joint visibility between very-high-resolution SAR and optical images of urban scenes. For this task, we extend the simulation framework SimGeoI to enable a simulation of individual pixels rather than complete images. Using the extended SimGeoI simulator, we carry out a case study using a TerraSAR-X staring spotlight image and a Worldview-2 panchromatic image acquired over the city of Munich, Germany. The results of this study indicate that about 55 % of the scene are visible in both images and are thus suitable for matching and data fusion endeavours, while about 25 % of the scene are affected by either radar shadow or optical occlusion. Taking the image acquisition parameters into account, our findings can provide support regarding the definition of upper bounds for image fusion tasks, as well as help to improve acquisition planning with respect to different application goals.
AN EFFICIENT, HIERARCHICAL VIEWPOINT PLANNING STRATEGY FOR TERRESTRIAL LASER SCANNER NETWORKS
Authors: Jia F. , Lichti D. D.
Published: May 2018

Abstract. Terrestrial laser scanner (TLS) techniques have been widely adopted in a variety of applications. However, unlike in geodesy or photogrammetry, insufficient attention has been paid to the optimal TLS network design. It is valuable to develop a complete design system that can automatically provide an optimal plan, especially for high-accuracy, large-volume scanning networks. To achieve this goal, one should look at the “optimality” of the solution as well as the computational complexity in reaching it. In this paper, a hierarchical TLS viewpoint planning strategy is developed to solve the optimal scanner placement problems. If one targeted object to be scanned is simplified as discretized wall segments, any possible viewpoint can be evaluated by a score table representing its visible segments under certain scanning geometry constraints. Thus, the design goal is to find a minimum number of viewpoints that achieves complete coverage of all wall segments. The efficiency is improved by densifying viewpoints hierarchically, instead of a “brute force” search within the entire workspace. The experiment environments in this paper were simulated from two buildings located on University of Calgary campus. Compared with the “brute force” strategy in terms of the quality of the solutions and the runtime, it is shown that the proposed strategy can provide a scanning network with a compatible quality but with more than a 70 % time saving.
DEEP MULTI-TASK LEARNING FOR TREE GENERA CLASSIFICATION
Authors: Ko C. , Kang J. , Sohn G.
Published: May 2018

Abstract. The goal for our paper is to classify tree genera using airborne Light Detection and Ranging (LiDAR) data with Convolution Neural Network (CNN) – Multi-task Network (MTN) implementation. Unlike Single-task Network (STN) where only one task is assigned to the learning outcome, MTN is a deep learning architect for learning a main task (classification of tree genera) with other tasks (in our study, classification of coniferous and deciduous) simultaneously, with shared classification features. The main contribution of this paper is to improve classification accuracy from CNN-STN to CNN-MTN. This is achieved by introducing a concurrence loss (Lcd) to the designed MTN. This term regulates the overall network performance by minimizing the inconsistencies between the two tasks. Results show that we can increase the classification accuracy from 88.7 % to 91.0 % (from STN to MTN). The second goal of this paper is to solve the problem of small training sample size by multiple-view data generation. The motivation of this goal is to address one of the most common problems in implementing deep learning architecture, the insufficient number of training data. We address this problem by simulating training dataset with multiple-view approach. The promising results from this paper are providing a basis for classifying a larger number of dataset and number of classes in the future.
HIGH SPEED VIDEOMETRIC MONITORING OF ROCK BREAKAGE
Authors: Allemand J. , Shortis M. R. , Elmouttie M. K.
Published: May 2018

Abstract. Estimation of rock breakage characteristics plays an important role in optimising various industrial and mining processes used for rock comminution. Although little research has been undertaken into 3D photogrammetric measurement of the progeny kinematics, there is promising potential to improve the efficacy of rock breakage characterisation. In this study, the observation of progeny kinematics was conducted using a high speed, stereo videometric system based on laboratory experiments with a drop weight impact testing system. By manually tracking individual progeny through the captured video sequences, observed progeny coordinates can be used to determine 3D trajectories and velocities, supporting the idea that high speed video can be used for rock breakage characterisation purposes. An analysis of the results showed that the high speed videometric system successfully observed progeny trajectories and showed clear projection of the progeny away from the impact location. Velocities of the progeny could also be determined based on the trajectories and the video frame rate. These results were obtained despite the limitations of the photogrammetric system and experiment processes observed in this study. Accordingly there is sufficient evidence to conclude that high speed videometric systems are capable of observing progeny kinematics from drop weight impact tests. With further optimisation of the systems and processes used, there is potential for improving the efficacy of rock breakage characterisation from measurements with high speed videometric systems.
POLE-LIKE ROAD FURNITURE DETECTION IN SPARSE AND UNEVENLY DISTRIBUTED MOBILE LASER SCANNING DATA
Authors: Li F. , Lehtomäki M. , Oude Elberink S. , Vosselman G. , Puttonen E. , Kukko A. , Hyyppä J.
Published: May 2018

Abstract. Pole-like road furniture detection received much attention due to its traffic functionality in recent years. In this paper, we develop a framework to detect pole-like road furniture from sparse mobile laser scanning data. The framework is carried out in four steps. The unorganised point cloud is first partitioned. Then above ground points are clustered and roughly classified after removing ground points. A slicing check in combination with cylinder masking is proposed to extract pole-like road furniture candidates. Pole-like road furniture are obtained after occlusion analysis in the last stage. The average completeness and correctness of pole-like road furniture in sparse and unevenly distributed mobile laser scanning data was above 0.83. It is comparable to the state of art in the field of pole-like road furniture detection in mobile laser scanning data of good quality and is potentially of practical use in the processing of point clouds collected by autonomous driving platforms.
AUTOMATIC SPATIO-TEMPORAL FLOW VELOCITY MEASUREMENT IN SMALL RIVERS USING THERMAL IMAGE SEQUENCES
Authors: Lin D. , Eltner A. , Sardemann H. , Maas H.-G.
Published: May 2018

Abstract. An automatic spatio-temporal flow velocity measurement approach, using an uncooled thermal camera, is proposed in this paper. The basic principle of the method is to track visible thermal features at the water surface in thermal camera image sequences. Radiometric and geometric calibrations are firstly implemented to remove vignetting effects in thermal imagery and to get the interior orientation parameters of the camera. An object-based unsupervised classification approach is then applied to detect the interest regions for data referencing and thermal feature tracking. Subsequently, GCPs are extracted to orient the river image sequences and local hot points are identified as tracking features. Afterwards, accurate dense tracking outputs are obtained using pyramidal Lucas-Kanade method. To validate the accuracy potential of the method, measurements obtained from thermal feature tracking are compared with reference measurements taken by a propeller gauge. Results show a great potential of automatic flow velocity measurement in small rivers using imagery from a thermal camera.
SEMANTIC BUILDING FAÇADE SEGMENTATION FROM AIRBORNE OBLIQUE IMAGES
Authors: Lin Y. , Nex F. , Yang M. Y.
Published: May 2018

Abstract. With the introduction of airborne oblique camera systems and the improvement of photogrammetric techniques, high-resolution 2D and 3D data can be acquired in urban areas. This high-resolution data allows us to perform detailed investigations on building roofs and façades which can contribute to LoD3 city modeling. Normally, façade segmentation is achieved from terrestrial views. In this paper, we address the problem from aerial views by using high resolution oblique aerial images as the data source in urban areas. In addition to traditional image features, such as RGB and SIFT, normal vector and planarity are also extracted from dense matching point clouds. Then, these 3D geometrical features are projected back to 2D space to assist façade interpretation. Random forest is trained and applied to label façade pixels. Fully connected conditional random field (CRF), capturing long-range spatial interactions, is used as a post-processing to refine our classification results. Its pairwise potential is defined by a linear combination of Gaussian kernels and the CRF model is efficiently solved by mean field approximation. Experiments show that 3D features can significantly improve classification results. Also, fully connected CRF performs well in correcting noisy pixels.
EXPLOITING AUTO-COLLIMATION FOR REAL-TIME ONBOARD MONITORING OF SPACE OPTICAL CAMERA GEOMETRIC PARAMETERS
Authors: Liu W. , Wang H. , Liu D. , Miu Y.
Published: May 2018

Abstract. Precise geometric parameters are essential to ensure the positioning accuracy for space optical cameras. However, state-of-the-art onorbit calibration method inevitably suffers from long update cycle and poor timeliness performance. To this end, in this paper we exploit the optical auto-collimation principle and propose a real-time onboard calibration scheme for monitoring key geometric parameters. Specifically, in the proposed scheme, auto-collimation devices are first designed by installing collimated light sources, area-array CCDs, and prisms inside the satellite payload system. Through utilizing those devices, the changes in the geometric parameters are elegantly converted into changes in the spot image positions. The variation of geometric parameters can be derived via extracting and processing the spot images. An experimental platform is then set up to verify the feasibility and analyze the precision index of the proposed scheme. The experiment results demonstrate that it is feasible to apply the optical auto-collimation principle for real-time onboard monitoring.
HIGH QUALITY FACADE SEGMENTATION BASED ON STRUCTURED RANDOM FOREST, REGION PROPOSAL NETWORK AND RECTANGULAR FITTING
Authors: Rahmani K. , Mayer H.
Published: May 2018

Abstract. In this paper we present a pipeline for high quality semantic segmentation of building facades using Structured Random Forest (SRF), Region Proposal Network (RPN) based on a Convolutional Neural Network (CNN) as well as rectangular fitting optimization. Our main contribution is that we employ features created by the RPN as channels in the SRF.We empirically show that this is very effective especially for doors and windows. Our pipeline is evaluated on two datasets where we outperform current state-of-the-art methods. Additionally, we quantify the contribution of the RPN and the rectangular fitting optimization on the accuracy of the result.
TRAINING IN INNOVATIVE TECHNOLOGIES FOR CLOSE-RANGE SENSING IN ALPINE TERRAIN
Authors: Rutzinger M. , Bremer M. , Höfle B. , Hämmerle M. , Lindenbergh R. , Oude Elberink S. , Pirotti F. , Scaioni M. , Wujanz D. , Zieher T.
Published: May 2018

Abstract. The 2nd international summer school “Close-range sensing techniques in Alpine terrain” was held in July 2017 in Obergurgl, Austria. Participants were trained in selected close-range sensing methods, such as photogrammetry, laser scanning and thermography. The program included keynotes, lectures and hands-on assignments combining field project planning, data acquisition, processing, quality assessment and interpretation. Close-range sensing was applied for different research questions of environmental monitoring in high mountain environments, such as geomorphologic process quantification, natural hazard management and vegetation mapping. The participants completed an online questionnaire evaluating the summer school, its content and organisation, which helps to improve future summer schools.
DENSE MATCHING COMPARISON BETWEEN CENSUS AND A CONVOLUTIONAL NEURAL NETWORK ALGORITHM FOR PLANT RECONSTRUCTION
Authors: Xia Y. , Tian J. , d’Angelo P. , Reinartz P.
Published: May 2018

Abstract. 3D reconstruction of plants is hard to implement, as the complex leaf distribution highly increases the difficulty level in dense matching. Semi-Global Matching has been successfully applied to recover the depth information of a scene, but may perform variably when different matching cost algorithms are used. In this paper two matching cost computation algorithms, Census transform and an algorithm using a convolutional neural network, are tested for plant reconstruction based on Semi-Global Matching. High resolution close-range photogrammetric images from a handheld camera are used for the experiment. The disparity maps generated based on the two selected matching cost methods are comparable with acceptable quality, which shows the good performance of Census and the potential of neural networks to improve the dense matching.
IFCWALL RECONSTRUCTION FROM UNSTRUCTURED POINT CLOUDS
Authors: Bassier M. , Klein R. , Van Genechten B. , Vergauwen M.
Published: May 2018

Abstract. The automated reconstruction of Building Information Modeling (BIM) objects from point cloud data is still ongoing research. A key aspect is the creation of accurate wall geometry as it forms the basis for further reconstruction of objects in a BIM. After segmenting and classifying the initial point cloud, the labelled segments are processed and the wall topology is reconstructed. However, the preocedure is challenging due to noise, occlusions and the complexity of the input data.In this work, a method is presented to automatically reconstruct consistent wall geometry from point clouds. More specifically, the use of room information is proposed to aid the wall topology creation. First, a set of partial walls is constructed based on classified planar primitives. Next, the rooms are identified using the retrieved wall information along with the floors and ceilings. The wall topology is computed by the intersection of the partial walls conditioned on the room information. The final wall geometry is defined by creating IfcWallStandardCase objects conform the IFC4 standard. The result is a set of walls according to the as-built conditions of a building. The experiments prove that the used method is a reliable framework for wall reconstruction from unstructured point cloud data. Also, the implementation of room information reduces the rate of false positives for the wall topology. Given the walls, ceilings and floors, 94% of the rooms is correctly identified. A key advantage of the proposed method is that it deals with complex rooms and is not bound to single storeys.
BUILDING CONSTRUCTION PROGRESS MONITORING USING UNMANNED AERIAL SYSTEM (UAS), LOW-COST PHOTOGRAMMETRY, AND GEOGRAPHIC INFORMATION SYSTEM (GIS)
Authors: Bognot J. R. , Candido C. G. , Blanco A. C. , Montelibano J. R. Y.
Published: May 2018

Abstract. Monitoring the progress of building’s construction is critical in construction management. However, measuring the building construction’s progress are still manual, time consuming, error prone, and impose tedious process of analysis leading to delays, additional costings and effort. The main goal of this research is to develop a methodology for building construction progress monitoring based on 3D as-built model of the building from unmanned aerial system (UAS) images, 4D as-planned model (with construction schedule integrated) and, GIS analysis. Monitoring was done by capturing videos of the building with a camera-equipped UAS. Still images were extracted, filtered, bundle-adjusted, and 3D as-built model was generated using open source photogrammetric software. The as-planned model was generated from digitized CAD drawings using GIS. The 3D as-built model was aligned with the 4D as-planned model of building formed from extrusion of building elements, and integration of the construction’s planned schedule. The construction progress is visualized via color-coding the building elements in the 3D model. The developed methodology was conducted and applied from the data obtained from an actual construction site. Accuracy in detecting ‘built’ or ‘not built’ building elements ranges from 82–84 % and precision of 50–72 %. Quantified progress in terms of the number of building elements are 21.31% (November 2016), 26.84 % (January 2017) and 44.19 % (March 2017). The results can be used as an input for progress monitoring performance of construction projects and improving related decision-making process.
RECOVERING THE 3D POSE AND SHAPE OF VEHICLES FROM STEREO IMAGES
Authors: Coenen M. , Rottensteiner F. , Heipke C.
Published: May 2018

Abstract. The precise reconstruction and pose estimation of vehicles plays an important role, e.g. for autonomous driving. We tackle this problem on the basis of street level stereo images obtained from a moving vehicle. Starting from initial vehicle detections, we use a deformable vehicle shape prior learned from CAD vehicle data to fully reconstruct the vehicles in 3D and to recover their 3D pose and shape. To fit a deformable vehicle model to each detection by inferring the optimal parameters for pose and shape, we define an energy function leveraging reconstructed 3D data, image information, the vehicle model and derived scene knowledge. To minimise the energy function, we apply a robust model fitting procedure based on iterative Monte Carlo model particle sampling. We evaluate our approach using the object detection and orientation estimation benchmark of the KITTI dataset (Geiger et al., 2012). Our approach can deal with very coarse pose initialisations and we achieve encouraging results with up to 82 % correct pose estimations. Moreover, we are able to deliver very precise orientation estimation results with an average absolute error smaller than 4°.
BUNDLE ADJUSTMENT-BASED STABILITY ANALYSIS METHOD WITH A CASE STUDY OF A DUAL FLUOROSCOPY IMAGING SYSTEM
Authors: Al-Durgham K. , Lichti D. D. , Detchev I. , Kuntze G. , Ronsky J. L.
Published: May 2018

Abstract. A fundamental task in photogrammetry is the temporal stability analysis of a camera/imaging-system’s calibration parameters. This is essential to validate the repeatability of the parameters’ estimation, to detect any behavioural changes in the camera/imaging system and to ensure precise photogrammetric products. Many stability analysis methods exist in the photogrammetric literature; each one has different methodological bases, and advantages and disadvantages. This paper presents a simple and rigorous stability analysis method that can be straightforwardly implemented for a single camera or an imaging system with multiple cameras. The basic collinearity model is used to capture differences between two calibration datasets, and to establish the stability analysis methodology. Geometric simulation is used as a tool to derive image and object space scenarios. Experiments were performed on real calibration datasets from a dual fluoroscopy (DF; X-ray-based) imaging system. The calibration data consisted of hundreds of images and thousands of image observations from six temporal points over a two-day period for a precise evaluation of the DF system stability. The stability of the DF system – for a single camera analysis – was found to be within a range of 0.01 to 0.66 mm in terms of 3D coordinates root-mean-square-error (RMSE), and 0.07 to 0.19 mm for dual cameras analysis. It is to the authors’ best knowledge that this work is the first to address the topic of DF stability analysis.
A VOXEL-BASED METADATA STRUCTURE FOR CHANGE DETECTION IN POINT CLOUDS OF LARGE-SCALE URBAN AREAS
Authors: Gehrung J. , Hebel M. , Arens M. , Stilla U.
Published: May 2018

Abstract. Mobile laser scanning has not only the potential to create detailed representations of urban environments, but also to determine changes up to a very detailed level. An environment representation for change detection in large scale urban environments based on point clouds has drawbacks in terms of memory scalability. Volumes, however, are a promising building block for memory efficient change detection methods. The challenge of working with 3D occupancy grids is that the usual raycasting-based methods applied for their generation lead to artifacts caused by the traversal of unfavorable discretized space. These artifacts have the potential to distort the state of voxels in close proximity to planar structures. In this work we propose a raycasting approach that utilizes knowledge about planar surfaces to completely prevent this kind of artifacts. To demonstrate the capabilities of our approach, a method for the iterative volumetric approximation of point clouds that allows to speed up the raycasting by 36 percent is proposed.
Novel method for the detection of short trace gas pulses with metal oxide semiconductor gas sensors
Authors: Baur Tobias , Schultealbert Caroline , Schütze Andreas , Sauerwald Tilman
Published: May 2018

Abstract. A novel method for the detection of short pulses of gas at very low concentrations, the differential surface reduction (DSR), is presented. DSR is related to the temperature pulsed reduction (TPR) method. In a high temperature phase, e.g., at 400 ∘C, the surface of a metal oxide semiconductor gas sensor (MOS) is oxidized in air and then cooled abruptly down to, e.g., 100 ∘C, conserving the large excess of negative surface charge. In this state reactions of reducing gases with surface oxygen are strongly favored, which increases the sensitivity. Due to the large energy barrier between metal oxide grains caused by the excess surface charge, a highly precise electrical measurement at very low conductance (down to 10−11 S) is a prerequisite for this method. Moreover, the electrical measurement must be very fast to allow a good resolution of retention times. Applying the method to a doped SnO2 detector, gas pulses down to a dosage of 1 ppb times seconds can be detected. The gas transport inside the detector is simulated using the finite element method (FEM) to optimize the gas transport and to keep response and recovery time as short as possible. With this approach, we have demonstrated a detection limit for ethanol of below 47 fg.
Investigation of severe dust storms over the Pan-Eurasian area using
multi-satellite observations and ground-based measurements
Authors: She Lu , Xue Yong , Guang Jie , Che Yahui , Fan Cheng , Li Ying , Xie Yanqing
Published: May 2018

Abstract. The deserts in East Asia are one of the most influential mineral dust source regions in the world. Large amounts of dust particles are emitted and transported to distant regions. A super dust storm characterized by long-distance transport occurred over the Pan-Eurasian Experiment (PEEX) area in early May 2017. In this study, multi-satellite/sensor observations and ground-based measurements combined with the HYbrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model were used to analyse the dynamical processes of the origin and transport of the strong dust storm. The optical and microphysical properties of the dust particles were analysed using Aerosol Robotic Network (AERONET) measurements. From the multi-satellite observations, the dust storms were suggested to have originated from the Gobi Desert on the morning of 3 May 2017, and it transported dust northeastward to the Bering Sea, eastward to the Korean Peninsula and Japan, and southward to southern Central China. The air quality in China drastically deteriorated as a result of this heavy dust storm; the PM10 (particulate matter less than 10 mm in aerodynamic diameter) concentrations measured at some air quality stations located in northern China reached 4000 μg/m3. During the dust event, the maximum AOD values reached 3, 2.3, 2.8, and 0.65 with sharp drops in the extinction Ångström exponent (EAE) to 0.023, 0.068, 0.03, and 0.097 at AOE_Baotou, Beijing, Xuzhou-CUMT, and Ussuriysk, respectively. The dust storm introduced great variations in the aerosol property, causing totally different spectral single-scattering albedo (SSA) and volume size distribution (VSD). The combined observations revealed comprehensive information about the dynamic transport of dust and the dust affected regions, and the effect of dust storms on the aerosol properties.
Climatic responses to systematic time variations of parameters: A dynamical approach
Authors: Nicolis Catherine
Published: May 2018

Abstract. The climatic response to time-dependent parameters is revisited from a nonlinear dynamics perspective. Some general trends are identified, based on a generalised stability criterion extending classical stability analysis to account for the presence of time-varying coefficients in the evolution equations of the system's variables. Theoretical predictions are validated by the results of numerical integration of the evolution equations of prototypical systems of relevance in atmospheric and climatic dynamics.
Exploring the Lyapunov instability properties of high-dimensional atmospheric and climate models
Authors: De Cruz Lesley , Schubert Sebastian , Demaeyer Jonathan , Lucarini Valerio , Vannitsem Stéphane
Published: May 2018

Abstract. The stability properties of intermediate-order climate models are
investigated by computing their Lyapunov exponents (LEs). The two models
considered are PUMA (Portable University Model of the Atmosphere), a
primitive-equation simple general circulation model, and MAOOAM (Modular
Arbitrary-Order Ocean-Atmosphere Model), a quasi-geostrophic coupled
ocean–atmosphere model on a β-plane. We wish to investigate the
effect of the different levels of filtering on the instabilities and dynamics
of the atmospheric flows. Moreover, we assess the impact of the oceanic
coupling, the dissipation scheme, and the resolution on the spectra of LEs. The PUMA Lyapunov spectrum is computed for two different values of the
meridional temperature gradient defining the Newtonian forcing to the
temperature field. The increase in the gradient gives rise to a higher
baroclinicity and stronger instabilities, corresponding to a larger dimension
of the unstable manifold and a larger first LE. The Kaplan–Yorke dimension
of the attractor increases as well. The convergence rate of the rate function
for the large deviation law of the finite-time Lyapunov exponents (FTLEs) is
fast for all exponents, which can be interpreted as resulting from the
absence of a clear-cut atmospheric timescale separation in such a model. The MAOOAM spectra show that the dominant atmospheric instability is
correctly represented even at low resolutions. However, the dynamics of the
central manifold, which is mostly associated with the ocean dynamics, is not
fully resolved because of its associated long timescales, even at
intermediate orders. As expected, increasing the mechanical atmosphere–ocean
coupling coefficient or introducing a turbulent diffusion parametrisation
reduces the Kaplan–Yorke dimension and Kolmogorov–Sinai entropy. In all
considered configurations, we are not yet in the regime in which one can
robustly define large deviation laws describing the statistics of the FTLEs. This paper highlights the need to investigate the natural variability of the
atmosphere–ocean coupled dynamics by associating rate of growth and decay of
perturbations with the physical modes described using the formalism of the
covariant Lyapunov vectors and considering long integrations in order to
disentangle the dynamical processes occurring at all timescales.
Snow depth uncertainty and its implications on satellite derived Antarctic sea ice thickness
Authors: Price Daniel , Soltanzadeh Iman , Rack Wolfgang
Published: May 2018

Abstract. Knowledge of the snow depth distribution on Antarctic sea ice is poor but is critical to obtaining sea ice thickness from satellite altimetry measurements of freeboard. We examine the usefulness of various snow products to provide snow depth information over Antarctic fast ice with a focus on a novel approach using a high-resolution numerical snow accumulation model (SnowModel). We compare this model to results from ECMWF ERA-Interim precipitation, EOS Aqua AMSR-E passive microwave snow depths and in situ measurements at the end of the sea ice growth season. The fast ice was segmented into three areas by fastening date and the onset of snow accumulation was calibrated to these dates. SnowModel falls within 0.02 m snow water equivalent (swe) of in situ measurements across the entire study area, but exhibits deviations of 0.05 m swe from these measurements in the east where large topographic features appear to have caused a positive bias in snow depth. AMSR-E provides swe values half that of SnowModel for the majority of the sea ice growth season. The coarser resolution ERA-Interim, not segmented for sea ice freeze up area reveals a mean swe value 0.01 m higher than in situ measurements. These various snow datasets and in situ information are used to infer sea ice thickness in combination with CryoSat-2 (CS-2) freeboard data. CS-2 is capable of capturing the seasonal trend of sea ice freeboard growth but thickness results are highly dependent on the assumptions involved in separating snow and ice freeboard. With various assumptions about the radar penetration into the snow cover, the sea ice thickness estimates vary by up to 2 m. However, we find the best agreement between CS-2 derived and in situ thickness when a radar penetration of 0.05-0.10 m into the snow cover is assumed.
Establishing a robust testing approach for displacement measurement on a rotating horizontal-axis wind turbine
Authors: Najafi Nadia , Vesth Allan
Published: May 2018

Abstract. Health monitoring by conventional sensors like accelerometers or strain
gauges becomes challenging for large rotating structures due to the issues
with feasibility, sensing and data transmission. In addition, acceleration
measurements have low capability of presenting very small frequencies, which
happen very often for large structures (for instance, frequencies between 0.2
and 0.5 Hz in horizontal-axis wind turbines). By contrast, displacement
measurement using stereo vision is rapid, non-contacting and distributed
over the structure. The sensors are cheaper and more easily applied to many
places on the object to be measured. Horizontal-axis wind turbines are one of
the most important large rotating structures and need to be measured and
monitored in time to prevent damage and failure, and the blade tip position
is one of the key parameters to measure in order to prevent the blade hitting the
turbine tower. This paper presents a clearly described and easily applicable procedure for
measuring the displacement on the components of a rotating horizontal-axis
wind turbine with
stereophotogrammetry. Paper markers have been applied on the rotor and tower
of a scaled-down horizontal-axis wind turbine model in the workshop and the
displacement measurement method has been demonstrated by measuring
displacement during operation. The method is mainly developed in two parts:
(1) camera calibration and (2) tracking algorithm. We introduce an efficient
camera calibration method for measurement in large fields of view, which has
always been a challenge. This method is easy and practical and offers better
accuracy compared with 2-D traditional camera calibration. The tracking
algorithm also works successfully and is able to track the points during
rotation within the measurement time. Finally, the accuracy analysis has been
conducted and has shown better accuracy of the new calibration method
compared with 2-D traditional camera calibration.
"discamus naturales incurvationes rectificare”. "De ludo globi" I: un diálogo entre el hombre y la naturaleza
Authors: Rusconi María Cecilia
Published: May 2018

Como lo indica su título, el diálogo De ludo globi está construido en torno a un juego. Este juego consta de dos elementos: una bocha de madera levemente ahuecada y una superficie sobre la que están dibujados diez círculos concéntricos. El significado de cada uno de los círculos es detallado en el Libro II. Por su parte, el Libro I se ocupa de la forma de la bocha y su movimiento.El desafío al que se enfrenta el presente trabajo reside en encontrar una unidad sistemática, que sirva de hilo conductor del diálogo De ludo globi, en el marco del Libro I. Esta sistematización del texto deberá mostrar que el diálogo tiene como trasfondo otra dimensión dialógica, que muestra al texto como un diálogo del individuo con la naturaleza.Con esta intención, el presente trabajo está articulado en tres partes. En primer lugar (1) me concentraré en la bocha y su movimiento. En segundo lugar (2) abordaré el planteo cusano del alma y el cuerpo. Éste deberá dirigirnos, por último, a (3) una distinción entre la libertad y la naturaleza.
El enigma de Ralph Cudworth en la historia de la filosofía
Authors: Strok Natalia Soledad
Published: May 2018

En el presente trabajo se estudia el lugar que ocupa Ralph Cudworth en la historia de la filosofía. El objetivo es mostrar que este autor no es parte del canon de la filosofía del siglo XVII y que, sin embargo, es un representante del período moderno en las primeras historias de la filosofía. Para ello, primero se introduce al autor y luego se expone la presentación que se realiza del inglés en las obras de Jacob Brucker, Wilhelm Tennemann, Taddä Rixner y Joseph Marie Degérando, para terminar en las Lecciones sobre historia de la filosofía de Georg Hegel. En un segundo momento se exponen algunas reflexiones en torno a Cudworth, que se originan a partir de la lectura de la bibliografía actualizada sobre dicho autor. Las conclusiones muestran la importancia de estudiar este tipo de pensadores, que no forman parte del canon de la filosofía pero son parte de la conformación del mismo.
Hans-Georg Gadamer y la filosofía española
Authors: Martín Gómez María
Published: May 2018

El trabajo que a continuación se presenta, fruto de una estancia investigadora en el Deutsches Literatur Archiv de la ciudad de Marbach en Alemania, se ocupa de las relaciones epistolares entre Hans-Georg Gadamer y los filósofos españoles del siglo XX. El hallazgo de nuevos documentos así como el análisis de su correspondencia inédita, revelan intereses y vínculos intelectuales comunes entre Hans-Georg Gadamer y algunos filósofos españoles de la talla de José Ortega y Gasset, Julián Marías, Laín Entralgo, Xavier Zubiri o Emilio Lledó. Las cartas que Gadamer escribe y recibe de estos pensadores muestran que el eminente carácter dialógico de la hermenéutica gadameriana fue siempre en el filósofo alemán una de sus características más representativas. Estas notas inéditas halladas en el Deutsche Literatur Archiv son de especial interés para comprender la no siempre comprensible situación de la filosofía en España y el desarrollo de la hermenéutica.
Chicory syrup as a substitution of sugar in fine pastry
Authors: Zacharová Michaela , Burešová Iva , Gál Robert , Walachová Dominika
Published: May 2018

Fine pastry is a favorite snack but contains big amount fats and sugars. Sugar consumption is a major factor in the development of diabetes and obesity. Because of the growing interest in low-calorie alternatives to sucrose, producers react with different new products which can replace sugar and do not compromise the consumer acceptability of food products. This study deals with replacement of sugar with chicory oligofructose syrup, which provides same sweetness as sugar but contain over 70 % of fiber. Chicory syrup is composed of oligo-fructose and inulin. Inulin-type fructans are beneficial for immune and cardiovascular systems and its prebiotic function can protect colon health. In this study, the influence of sucrose (7 g.100g-1) replacement with chicory oligofructose syrup (0; 3.5; 7 g.100g-1) on the texture, specific loaf volume and sensory acceptability of biologically leavened muffins was tested. The substitution of sugar by the chicory syrup decreased specific loaf volume from 2.15 to 2.01 mL.g-1 while hardness, springiness and chewiness increased. There was no detrimental impact of syrup addition to cohesiveness of fine pastry muffin. It was observed that due to the syrup addition, pastry hardens faster, as showed results of hardnesss measured after 24 h. Bread crumb and crust sensory characteristics were not affected by the syrup addition. Weak impact of sugar replacement on sensory evaluation may be related to a reduced amount of the panelists involved in this study. More extensive study will, however, be performed to describe the impact of sugar replacement of fine biologically leavened muffins in more details. The results of this preliminary study shows, that the substitution of sugar by chicory syrup change textural properties and loaf volume. Despite all, based on sensory analysis the chicory syrup up to amount 7 g.100g-1 seems to be adequate for its use as a sugar replacer in fine pastry as biologically leavened muffins.
Occurrence of selected metals in feed and sheep´s milk from areas with different environmental burden
Authors: Tunegová Martina , Toman Róbert , Tančin Vladimí­r , Janí­ček Martin
Published: May 2018

The content of selected essential elements and toxic metals in feed and sheep's milk from areas with different parts of Slovak Republic was analyzed. Region of Novoť (undisturbed environment; North Slovakia) and region of Klátova Nová Ves (widely disturbed environment; Western Slovakia) were under investigation. Eleven metals have been analyzed (essential elements - calcium, zinc, selenium, iron, magnesium, copper; toxic elements - arsenic, mercury, lead, cadmium, nickel). Samples of feeds and milk were collected five-times during the year (spring and autumn season). Analyses of samples were performed by certified testing laboratory Eurofins Bel/Novamann (Nové Zámky, Slovak Republic). Analyses were performed by routine methods, according to the valid methodologies. The results showed significantly higher content of selected essential elements in feed in spring season from area with widely disturbed environment (Klátova Nová Ves). Significantly higher content of essential elements in milk was on farm of Novoť (undisturbed environment). Occurrence of toxic metals in feed from area with widely disturbed environment in spring season did not affect their content in milk. It can be concluded, that the use of milk of sheep from these areas for direct use or for dairy products processing is appropriate, safe and poses no health risk for the consumers.
Study on the Impact of Strategic Human Resource Management on Enterprise Performance
Authors: Ding Jie , Xiangyu Cai Xiangyu
Published: May 2018

With the development of economy, the competition among enterprises is becoming more and more intense in China. Human resources as the core competitiveness of enterprises are very important to the performance of enterprises. This article mainly discusses the impact of strategic human resource management on enterprise performance. The article has four parts including introduction, literature review, materials and methods and result and discussion. In this article, there are two hypotheses. The first one is the career development and employee training programs have the positive impact of improvement of strategic human resource management on business performance; the other one is performance based wage has the positive impact of improvement of strategic human resource management on business performance. After data analysis, these two hypotheses are verified.