bluuebunny/crossref_metadata_2025 huggingface dataset:
Construction of Real-time Interactive Mode-based Online Course Live Broadcast Teaching Platform for Physical Training
Authors: Liu Jianqiu
Published: May 2018

As a new teaching mode, online courses have become one of the most important teaching methods in higher education. At present, there are still some shortcomings in online course live broadcast teaching platform including insufficient hardware support, low flexibility and weak interactivity. Meanwhile, during the entire online course teaching process, teachers do not know the overall learning effect of students in real time to determine the next teaching plan. This study presented a real-time interactive technology to enhance the interactive of the entire online course broadcast teaching platform. At the same time, it combined a monitoring method for online course terminals, servers and learning process to demonstrate students’ learning effect in the whole online course learning process, and finally built the online course broadcast teaching platform. The practice test in teaching shows that the online course broadcast teaching platform can improve the teaching effect among students, which is of great significance for the improvement of teaching quality.
« Des trucs qui rapportent »
Authors: Juven Pierre-André
Published: May 2018

Si, historiquement, la très grande majorité des recherches consacrées à l’hôpital public ont porté la focale sur les soins, les savoirs, les relations entre soignant.e.s ou entre soignant.e.s et soigné.e.s, la prégnance des enjeux économiques en matière de santé indique que le spectre des questionnements doit désormais être étendu. Cet article propose d’étudier au plus près de sa fabrique et de ses effets, la logique économique à l’œuvre à l’hôpital public en France aujourd’hui. En observant les opérations de mise en compte et d’évaluation quantitative des activités, des médecins et des services hospitaliers, des logiques économiques nouvelles apparaissent, logiques que nous proposons d’appeler processus de capitalisation. Un regard porté sur l’économie hospitalière telle qu’elle se fait montre que ces processus supposent une hybridation des logiques économiques et cliniques et que ces logiques coexistent selon des degrés de conflictualité variables.
Quand l'allaitement « fait » la mère
Authors: Chautems Caroline
Published: May 2018

Les expert·e·s en périnatalité identifient l’allaitement au sein comme la manière la plus adéquate de nourrir les nouveau-nés. Sa réussite constitue dès lors un enjeu central du post-partum. Cet article explore les pratiques et expériences d’allaitement de femmes qui ont choisi d’être accompagnées par une sage-femme indépendante et d’accoucher à domicile ou en maison de naissance. Lors du suivi post-partum, les sages-femmes s'engagent avec les mères dans un processus de co-construction du corps maternel. Le rapport au corps lactant marque ainsi fortement l'expérience du post-partum et pose les fondations de l'identité maternelle. Le modèle de soins des sages-femmes propose une lecture à la fois naturaliste et productiviste de l’allaitement, conjointement avec la mobilisation d’outils et de techniques pour optimiser son déroulement. Dans l'échange avec leur sage-femme, puis à travers le travail corporel requis par la gestion de leur lactation, les mères découvrent et s'ajustent à leur nouveau rôle. L'expérience de la transition à la maternité est ainsi indissociable du travail corporel déployé pour la mise en place et le maintien de l’allaitement.
Une pratique hospitalière des médecines non conventionnelles à l’essai
Authors: Candelise Lucia , Remillet Gilles
Published: May 2018

L’hôpital de Pitigliano (Toscane), sur le point d’être fermé il y a quelques années pour des raisons relatives à des politiques de centralisation des hôpitaux italiens, se trouve depuis 2011 être au cœur d’un projet de réorganisation structurelle à travers la création d’un service de « médecine intégrée », associant médecines non conventionnelles (acupuncture et homéopathie) et biomédecine. À partir d’une ethnographie des pratiques de soin en situations cliniques, l’étude montre comment s’articulent entre elles les contraintes normatives du travail hospitalier (insertion de thérapeutiques autres dans une structure biomédicale, organisation du travail d’équipe, interrelations des approches disciplinaires au chevet du malade) et les aspirations humanistes de ces professionnels de santé (discours, valeurs, motivations, parcours professionnels) pour saisir les logiques politiques et idéologiques qui les sous-tendent, tant sur le plan individuel que collectif. En d’autres termes, il s’agit de penser, à partir de cette expérience de pluralisme médical, la transformation contemporaine des pratiques cliniques hospitalières en cours en Italie comme dans les autres pays européens.
Navigating the complexity of the therapeutic and clinical use of photography in psychosocial settings: a review of the literature
Authors: Saita Emanuela , Tramontano Martina
Published: May 2018

In contrast with the recent increase in the use of photography as a therapeutic tool in psychological settings, lack of clarity exists regarding this intervention modality. While the distinction among Photo Therapy, Therapeutic Photography, and Photo Art Therapy is theoretically established we examined whether this classification is confirmed also in practice. Electronic databases (PsychINFO, PubMed, MEDLINE, and Social Sciences Abstracts-EBSCO) were systematically searched for studies published in the last fifteen years utilizing photographic techniques as the elective method of intervention. A total of 124 articles were identified, of which 21 met the inclusion criteria. Results indicate that photography has been used in health, clinical, social, and community settings. Photovoice, Photographic Self-Portrait, and Photo Presentation are the methods most commonly implemented. Several contributions could be placed in more than one of the above-mentioned models of intervention; suggesting that the criteria to assign articles to each model are difficult to apply when the models are put into practice.
The variance conjecture on hyperplane projections of the $\ell_p^n$ balls
Authors: Alonso David , Bastero Jesús
Published: May 2018

We show that for any

1\leq p\leq\infty

, the family of random vectors uniformly distributed on hyperplane projections of the unit ball of

\ell_p^n

verify the variance conjecture

\mathrm {Var} |X|^2 \leq C \mathrm {max}_{\xi\in S^{n-1}}\mathbb E\langle X,\xi\rangle^2\, \mathbb E|X|^2,

where

C

depends on

p

but not on the dimension

n

or the hyperplane. We will also show a general result relating the variance conjecture for a random vector uniformly distributed on an isotropic convex body and the variance conjecture for a random vector uniformly distributed on any Steiner symmetrization of it. As a consequence we will have that the class of random vectors uniformly distributed on any Steiner symmetrization of an

\ell_p^n

-ball verify the variance conjecture.
Algebraic connections vs. algebraic $\mathcal D$-modules: regularity conditions
Authors: Cailotto Maurizio , Fiorot Luisa
Published: May 2018

This paper is devoted to the comparison of the notions of regularity for algebraic connections and regularity for (holonomic) algebraic

\mathcal D

-modules.
Распределение нулей полиномов Эрмита-Паде в случае Анжелеско
Authors: Rakhmanov Evguenii Andreevich
Published: May 2018

В работе рассматривается вопрос о распределении нулей полиномов Эрмита-Паде типа I, ассоциированных с вектор-функцией $\vec f=(f_1,…,f_s)$, компоненты $f_k$ которой являются функциями с конечным числом точек ветвления на плоскости. Предполагается, что множества ветвления компонент функции достаточно хорошо отделены друг от друга (случай Анжелеско). При этом условии доказывается теорема о предельном распределении нулей для таких полиномов. Предельные меры определяются в терминах стандартной векторной задачи равновесия.
Доказательство теоремы основано на методах, разработанных Г. Шталем [59]-[63], A. A. Гончаром и автором настоящей работы [27], [55]. В настоящей работе указанные методы развиваются с целью приложения к наборам полиномов, определяемых системами комплексных соотношений ортогональности. Наряду с характеризацией предельных распределений нулей полиномов Эрмита-Паде, использующей векторную задачу равновесия, мы рассматриваем альтернативную характеризацию в терминах римановой поверхности $\mathcal R(\vec f )$, ассоциированной с $\vec f$. В этих терминах мы выдвигаем более общую (без условия Анжелеско) гипотезу о распределении нулей полиномов Эрмита-Паде.
Библиография: 72 названия.
Reviewing the relationship between thermal reservoir parameters and geothermal energy output
Authors: Grippi Jamie
Published: May 2018

This meta-study draws upon contemporary literature to examine parameters of thermal reservoirs and their relationships to geothermal power station output metrics. The objectives of the meta-study are to identify trends and quantify the influence of each parameter on the system as a whole. This study provides a framework for industry and researchers exploring new potential geothermal fields. Six reservoir parameters – well depth, temperature, enthalpy, mass flow rate, thermal gradient and crust thickness – were plotted against the net electrical output per production well (Enet/well) and exergy efficiency (ηB) of 64 geothermal facilities. The meta-study identified that reservoir temperature has the greatest proportionality to power output, with yields above 10MWe exhibited only for high enthalpy reservoirs exceeding 500K. Well depth has the greatest inverse proportionality to exergy efficiency, with upper limit values declining below 80% for wells deeper than 3000m. Well depth has a similar trend line, though lesser correlation, as reservoir temperature to power output. Crust thickness has an inverse correlation to exergy efficiency, with upper limit values dropping from 100% to 65% as thickness increased from 30 to 45km. There was significant clustering of data points in most trendless plots, suggesting a considerable degree of homogeneity between currently tapped reservoirs and turbine efficiencies. The low number of well-defined data trends implies a high degree of complexity arising from the relationships between reservoir parameters that make quantification problematic. Despite this difficulty, examination of the aforementioned parameters suggests that although hotter reservoirs are usually found at greater depths, the hottest and shallowest reservoirs should be prioritized for use in order to return maximal power outputs and reduce exergy losses that occur along large lengths of piping.
Wastewater and Mixed Microbial Consortia: a metastudy analysis of Optimal Microbial Fuel Cell configuration
Authors: Ryan Jonathon , Ferral-Smith Hayden , Wilson Joshua
Published: May 2018

Microbial Fuel Cells (MFCs) are an area of increasing research for use as an alternative energy source, due to their ability to produce electricity while simultaneously treating organic waste. This meta-study determines the optimal MFC configuration for electricity production, through consideration of the biocatalyst and substrate used. This study focuses primarily on comparing the use of mixed microbial consortia to pure strains of biocatalyst, and the use of waste water in contrast to simple substrates such as; acetate, glucose, and lactate. The use of algae as a substrate, and as a biocatalyst, is also investigated. In this study, only single and dual chamber MFCs are compared, and power density standardised to anode surface area (mW/m2) is used as a metric to facilitate the comparison of different experimental setups. This meta-study shows that dual chamber MFCs, using simple substrates, when catalysed by mixed culture biocatalysts, produce greater power densities, than algae, and complex substrates, with average power densities of 280, 70 and 30 (mW/m2) observed respectively. In single chamber MFC configurations, mixed culture biocatalysts have been observed to yield approximately double the power output of pure culture biocatalysts.
Using photonic cooling systems to improve the efficiency of photovoltaic cells and their means of electricity production
Authors: Gordon Alice , Cross Ben , Evans Oliver
Published: May 2018

Photovoltaic (PV) systems generate electricity from the abundance of solar energy provided by the sun, making them a significant technology in utilising clean, renewable energy. It is in our best interest to achieve the maximum possible electrical output from these systems.
Solar photovoltaic (PV) systems are a effective technology to resource clean energy, it is in our best interest to achieve the maximum possible electrical output from these cells.
Through this meta-study we discuss how the efficiency of photovoltaic systems can be optimised using photonic cooling systems (PCS). The use of laser and doppler cooling upon photovoltaic (solar) cells combat the thermodynamic property of semiconductors where increases in temperature result in a decrease in electroconductive efficiency. PCS’ ability to bring materials to the mK range theoretically improves PV systems efficiency by more than double the current practical results. However, we show the inability for semiconductors to function at such low temperatures resulting in such cells acting as insulators in the mK range. Through this meta-study we have researched efficiency of PV cells and PCS through multiple paper analysis. Using databases such as Scopus and Nature where we recognise highly cited journals/papers while focusing upon PV and PCS as search parameters. Linking between their temperature, efficiency and success during practical testing.
A new interpretative framework for below-cloud effects on stable water isotopes in vapour and rain
Authors: Graf Pascal , Wernli Heini , Sodemann Harald
Published: May 2018

Abstract. Raindrops interact with water vapour in ambient air while sedimenting from the cloud base to the ground. They constantly exchange water molecules with the environment and, in sub-saturated air, they evaporate partially or entirely. The latter of these below-cloud processes is important for predicting the resulting surface rainfall amount and it influences the boundary layer profiles of temperature and moisture through to evaporative latent cooling and humidity changes. However, despite its importance, it is very difficult to quantify this process from observations. Stable water isotopes provide such information, as they are influenced by both rain evaporation and equilibration. This study elucidates this option by introducing a novel interpretation framework for stable water isotope measurements performed simultaneously at high temporal resolution in both near-surface vapour and rain. We refer to this viewing device as the ΔδΔd-diagram, which shows the isotopic composition (δ2H, d-excess) of equilibrium vapour from precipitation samples relative to the ambient vapour. It is shown that this diagram facilitates the diagnosis of below-cloud processes and their effects on the isotopic composition of vapour and rain since equilibration and evaporation lead to different pathways in the two-dimensional phase space of the ΔδΔd-diagram. For a specific cold front in Central Europe, the analysis shows that below-cloud processes lead to distinct and temporally variable imprints on the isotope signal in surface rain. The influence of evaporation on this signal is particularly strong during periods with a weak precipitation rate. After the frontal passage, the near-surface atmospheric layer is characterised by higher relative humidity and a lower melting layer, leading to weaker below-cloud evaporation and equilibration. Measurements from four cold frontal events reveal a surprisingly similar slope of ΔdΔδ= −0.30 in the phase space, indicating a potentially characteristic signature of below-cloud processes for this type of rain events.
An empirical zenith wet delay correction model using piecewise height functions
Authors: Yao YiBin , Hu YuFeng
Published: May 2018

Abstract. Tropospheric delay is an important error source in space geodetic techniques. The temporal and spatial variations of the zenith wet delay (ZWD) are very large, and thus limit the accuracy of tropospheric delay modelling. Thus it is worthwhile undertaking research aimed at constructing a precise ZWD model. Traditional tropospheric modelling methods do not consider the effects of different heights on ZWD. Based on the analysis of vertical variations of ZWD, we divided the troposphere into three height intervals: below 2 km, 2 km to 5 km, and 5 km to 10 km, and determined the fitting functions for the ZWD within these height intervals. The global ZWD model HZWD, which considers the periodic variations of ZWD with a spatial resolution of 5° × 5°, is established using the ECMWF ZWD profiles from 2001 to 2010. Validated by the ECMWF ZWD data in 2015, the precisions of the ZWD estimation in the HZWD model over the three height intervals are improved by 1.4 mm, 0.9 mm, and 1.2 mm, respectively, compared to that of the currently best GPT2w model (23.8 mm, 13.1 mm, and 2.6 mm). The test results from ZWD data from 318 radiosonde stations show that the root mean square (RMS) error in the HZWD model over the three height intervals was reduced by 2 %, 5 %, and 33 %, respectively, compared to the GPT2w model (30.1 mm, 15.8 mm, and 3.5 mm) over the three height intervals. In addition, the spatial and temporal stabilities of the HZWD model are higher than those of GPT2w and UNB3m.
Placing the Common Era in a Holocene context: millennial to centennial patterns and trends in the hydroclimate of North America over the past 2000 years
Authors: Shuman Bryan N. , Routson Cody , McKay Nicholas , Fritz Sherilyn , Kaufman Darrell , Kirby Matthew E. , Nolan Connor , Pederson Gregory T. , St-Jacques Jeannine-Marie
Published: May 2018

Abstract. A synthesis of 93 hydrologic records from across North and Central America, and adjacent tropical and Arctic islands, reveals centennial to millennial trends in the regional hydroclimates of the Common Era (CE; past 2000 years). The hydrological records derive from materials stored in lakes, bogs, caves, and ice from extant glaciers, which have the continuity through time to preserve low-frequency ( > 100 year) climate signals that may extend deeper into the Holocene. The most common pattern, represented in 46 (49 %) of the records, indicates that the centuries before 1000 CE were drier than the centuries since that time. Principal component analysis indicates that millennial-scale trends represent the dominant pattern of variance in the southwestern US, northeastern US, mid-continent, Pacific Northwest, Arctic, and tropics, although not all records within a region show the same direction of change. The Pacific Northwest and the southernmost tier of the tropical sites tended to dry toward present, as many other areas became wetter than before. In 22 records (24 %), the Medieval Climate Anomaly period (800–1300 CE) was drier than the Little Ice Age (1400–1900 CE), but in many cases the difference was part of the longer millennial-scale trend, and, in 25 records (27 %), the Medieval Climate Anomaly period represented a pluvial (wet) phase. Where quantitative records permitted a comparison, we found that centennial-scale fluctuations over the Common Era represented changes of 3–7 % in the modern interannual range of variability in precipitation, but the accumulation of these long-term trends over the entirety of the Holocene caused recent centuries to be significantly wetter, on average, than most of the past 11 000 years.
The use of radiocarbon 14C to constrain carbon dynamics in the soil module of the land surface model ORCHIDEE (SVN r5165)
Authors: Tifafi Marwa , Camino-Serrano Marta , Hatté Christine , Morras Hector , Moretti Lucas , Barbaro Sebastián , Cornu Sophie , Guenet Bertrand
Published: May 2018

Abstract. Despite the importance of soil as a large component of the terrestrial ecosystems, the soil compartments are not well represented in the Land Surface Models (LSMs). Indeed, soils in current LSMs are generally represented based on a very simplified schema that can induce a misrepresentation of the deep dynamics of soil carbon. Here, we present a new version of the IPSL-Land Surface Model called ORCHIDEE-SOM, incorporating the 14C dynamic in the soil. ORCHIDEE-SOM, first, simulates soil carbon dynamics for different layers, down to 2 m depth. Second, concentration of dissolved organic carbon (DOC) and its transport are modeled. Finally, soil organic carbon (SOC) decomposition is considered taking into account the priming effect. After implementing the 14C in the soil module of the model, we evaluated model outputs against observations of soil organic carbon and 14C activity (F14C) for different sites with different characteristics. The model managed to reproduce the soil organic carbon stocks and the F14C along the vertical profiles. However, an overestimation of the total carbon stock was noted, but was mostly marked on the surface. Then, thanks to the introduction of 14C, it has been possible to highlight an underestimation of the age of carbon in the soil. Thereafter, two different tests on this new version have been established. The first was to increase carbon residence time of the passive pool and decrease the flux from the slow pool to the passive pool. The second was to establish an equation of diffusion, initially constant throughout the profile, making it vary exponentially as a function of depth. The first modifications did not improve the capacity of the model to reproduce observations whereas the second test showed a decrease of the soil carbon stock overestimation, especially at the surface and an improvement of the estimates of the carbon age. This assumes that we should focus more on vertical variation of soil parameters as a function of depth, mainly for diffusion, in order to upgrade the representation of global carbon cycle in LSMs, thereby helping to improve predictions of the future response of soil organic carbon to global warming.
Water-use dynamics of an alien invaded riparian forest within the summer rainfall zone of South Africa
Authors: Scott-Shaw Bruce C. , Everson Colin S.
Published: May 2018

Abstract. In South Africa the invasion of riparian forests by alien trees has the potential to affect the country’s limited water resources. Tree water-use measurements have therefore become an important component of recent hydrological studies. It is difficult for South African government initiatives, such as the Working for Water (WfW) alien clearing programme, to justify alien tree removal and implement rehabilitation unless hydrological benefits are known. Consequently water-use within a riparian forest in the upper Mgeni catchment of KwaZulu-Natal in South Africa was monitored over a two year period. The site consisted of an indigenous stand of eastern mistbelt forest that had been invaded by Acacia mearnsii, Eucalyptus nitens and Solanum mauritianum. The heat ratio method of the heat pulse velocity sap flow technique and the stem steady state techniques were used to measure the sap flow of a selection of indigenous and introduced species. The indigenous trees at New Forest showed clear seasonal trends in the daily sap flow rates varying from 8 to 25 L•day−1 in summer (sap flow being directly proportional to tree size). In the winter periods this was reduced to between 3 and 6 L•day−1 when limited energy flux was available to drive the transpiration process. The water-use in the A. mearnsii and E. grandis trees showed a slight seasonal trend, with a high flow during the winter months in contrast to the indigenous species. The water-use in the understorey indicated that multi-stemmed species used up to 12 L•day−1. Small alien trees (
A Hybrid Stochastic Rainfall Model That Reproduces Rainfall Characteristics at Hourly through Yearly Time Scale
Authors: Park Jeongha , Onof Christian , Kim Dongkyun
Published: May 2018

Abstract. A novel approach of stochastic rainfall generation that can reproduce various statistical characteristics of observed rainfall at hourly through yearly time scale is presented. The model uses the Seasonal Auto-Regressive Integrated Moving Average (SARIMA) model to generate monthly rainfall. Then, it downscales the generated monthly rainfall to the hourly aggregation level using the Modified Bartlett-Lewis Rectangular Pulse (MBLRP) model, a type of Poisson cluster rainfall model. Here, the MBLRP model is fine-tuned such that it can reproduce the fine-scale properties of observed rainfall. This was achieved by first generating a set of fine scale rainfall statistics reflecting the complex correlation structure between rainfall mean, variance, auto-covariance, and proportion of dry periods, and then coupling it to the generated monthly rainfall, which were used as the basis of the MBLRP parameters to downscale monthly rainfall. The approach was tested at the 29 gauges located in the Midwest to the East Coast of the Continental United States with a variety of rainfall characteristics. The results of the test suggest that our hybrid model accurately reproduces the first through the third order statistics as well as the intermittency properties from the hourly to the annual time scale; and the statistical behaviour of monthly maxima and extreme values of the observed rainfall was well reproduced as well.
H-RANSAC: A HYBRID POINT CLOUD SEGMENTATION COMBINING 2D AND 3D DATA
Authors: Adam A. , Chatzilari E. , Nikolopoulos S. , Kompatsiaris I.
Published: May 2018

Abstract. In this paper, we present a novel 3D segmentation approach operating on point clouds generated from overlapping images. The aim of the proposed hybrid approach is to effectively segment co-planar objects, by leveraging the structural information originating from the 3D point cloud and the visual information from the 2D images, without resorting to learning based procedures. More specifically, the proposed hybrid approach, H-RANSAC, is an extension of the well-known RANSAC plane-fitting algorithm, incorporating an additional consistency criterion based on the results of 2D segmentation. Our expectation that the integration of 2D data into 3D segmentation will achieve more accurate results, is validated experimentally in the domain of 3D city models. Results show that HRANSAC can successfully delineate building components like main facades and windows, and provide more accurate segmentation results compared to the typical RANSAC plane-fitting algorithm.
LOCALIZATION AND MAPPING USING A NON-CENTRAL CATADIOPTRIC CAMERA SYSTEM
Authors: Khurana M. , Armenakis C.
Published: May 2018

Abstract. This work details the development of an indoor navigation and mapping system using a non-central catadioptric omnidirectional camera and its implementation for mobile applications. Omnidirectional catadioptric cameras find their use in navigation and mapping of robotic platforms, owing to their wide field of view. Having a wider field of view, or rather a potential 360° field of view, allows the system to “see and move” more freely in the navigation space. A catadioptric camera system is a low cost system which consists of a mirror and a camera. Any perspective camera can be used. A platform was constructed in order to combine the mirror and a camera to build a catadioptric system. A calibration method was developed in order to obtain the relative position and orientation between the two components so that they can be considered as one monolithic system. The mathematical model for localizing the system was determined using conditions based on the reflective properties of the mirror. The obtained platform positions were then used to map the environment using epipolar geometry. Experiments were performed to test the mathematical models and the achieved location and mapping accuracies of the system. An iterative process of positioning and mapping was applied to determine object coordinates of an indoor environment while navigating the mobile platform. Camera localization and 3D coordinates of object points obtained decimetre level accuracies.
EXPERIENCES WITH ACQUIRING HIGHLY REDUNDANT SPATIAL DATA TO SUPPORT DRIVERLESS VEHICLE TECHNOLOGIES
Authors: Koppanyi Z. , Toth C. K.
Published: May 2018

Abstract. As vehicle technology is moving towards higher autonomy, the demand for highly accurate geospatial data is rapidly increasing, as accurate maps have a huge potential of increasing safety. In particular, high definition 3D maps, including road topography and infrastructure, as well as city models along the transportation corridors represent the necessary support for driverless vehicles. In this effort, a vehicle equipped with high-, medium- and low-resolution active and passive cameras acquired data in a typical traffic environment, represented here by the OSU campus, where GPS/GNSS data are available along with other navigation sensor data streams. The data streams can be used for two purposes. First, high-definition 3D maps can be created by integrating all the sensory data, and Data Analytics/Big Data methods can be tested for automatic object space reconstruction. Second, the data streams can support algorithmic research for driverless vehicle technologies, including object avoidance, navigation/positioning, detecting pedestrians and bicyclists, etc. Crucial cross-performance analyses on map database resolution and accuracy with respect to sensor performance metrics to achieve economic solution for accurate driverless vehicle positioning can be derived. These, in turn, could provide essential information on optimizing the choice of geospatial map databases and sensors’ quality to support driverless vehicle technologies. The paper reviews the data acquisition and primary data processing challenges and performance results.
DEVELOPMENT OF UAV PHOTOGRAMMETRY METHOD BY USING SMALL NUMBER OF VERTICAL IMAGES
Authors: Kunii Y.
Published: May 2018

Abstract. This new and efficient photogrammetric method for unmanned aerial vehicles (UAVs) requires only a few images taken in the vertical direction at different altitudes. The method includes an original relative orientation procedure which can be applied to images captured along the vertical direction. The final orientation determines the absolute orientation for every parameter and is used for calculating the 3D coordinates of every measurement point. The measurement accuracy was checked at the UAV test site of the Japan Society for Photogrammetry and Remote Sensing. Five vertical images were taken at 70 to 90 m altitude. The 3D coordinates of the measurement points were calculated. The plane and height accuracies were ±0.093 m and ±0.166 m, respectively. These values are of higher accuracy than the results of the traditional photogrammetric method. The proposed method can measure 3D positions efficiently and would be a useful tool for construction and disaster sites and for other field surveying purposes.
NEURAL NETWORKS FOR THE CLASSIFICATION OF BUILDING USE FROM STREET-VIEW IMAGERY
Authors: Laupheimer D. , Tutzauer P. , Haala N. , Spicker M.
Published: May 2018

Abstract. Within this paper we propose an end-to-end approach for classifying terrestrial images of building facades into five different utility classes (commercial, hybrid, residential, specialUse, underConstruction) by using Convolutional Neural Networks (CNNs). For our examples we use images provided by Google Street View. These images are automatically linked to a coarse city model, including the outlines of the buildings as well as their respective use classes. By these means an extensive dataset is available for training and evaluation of our Deep Learning pipeline. The paper describes the implemented end-to-end approach for classifying street-level images of building facades and discusses our experiments with various CNNs. In addition to the classification results, so-called Class Activation Maps (CAMs) are evaluated. These maps give further insights into decisive facade parts that are learned as features during the training process. Furthermore, they can be used for the generation of abstract presentations which facilitate the comprehension of semantic image content. The abstract representations are a result of the stippling method, an importance-based image rendering.
LAYOUT SLAM WITH MODEL BASED LOOP CLOSURE FOR 3D INDOOR CORRIDOR RECONSTRUCTION
Authors: Baligh Jahromi A. , Sohn G. , Jung J. , Shahbazi M. , Kang J.
Published: May 2018

Abstract. In this paper, we extend a recently proposed visual Simultaneous Localization and Mapping (SLAM) techniques, known as Layout SLAM, to make it robust against error accumulations, abrupt changes of camera orientation and miss-association of newly visited parts of the scene to the previously visited landmarks. To do so, we present a novel technique of loop closing based on layout model matching; i.e., both model information (topology and geometry of reconstructed models) and image information (photometric features) are used to address a loop-closure detection. The advantages of using the layout-related information in the proposed loop-closing technique are twofold. First, it imposes a metric constraint on the global map consistency and, thus, adjusts the mapping scale drifts. Second, it can reduce matching ambiguity in the context of indoor corridors, where the scene is homogenously textured and extracting sufficient amount of distinguishable point features is a challenging task. To test the impact of the proposed technique on the performance of Layout SLAM, we have performed the experiments on wide-angle videos captured by a handheld camera. This dataset was collected from the indoor corridors of a building at York University. The obtained results demonstrate that the proposed method successfully detects the instances of loops while producing very limited trajectory errors.
VEGETATION REMOVAL FROM UAV DERIVED DSMS, USING COMBINATION OF RGB AND NIR IMAGERY
Authors: Skarlatos D. , Vlachos M.
Published: May 2018

Abstract. Current advancements on photogrammetric software along with affordability and wide spreading of Unmanned Aerial Vehicles (UAV), allow for rapid, timely and accurate 3D modelling and mapping of small to medium sized areas. Although the importance and applications of large format aerial overlaps cameras and photographs in Digital Surface Model (DSM) production and LIDAR data is well documented in literature, this is not the case for UAV photography. Additionally, the main disadvantage of photogrammetry is the inability to map the dead ground (terrain), when we deal with areas that include vegetation. This paper assesses the use of near-infrared imagery captured by small UAV platforms to automatically remove vegetation from Digital Surface Models (DSMs) and obtain a Digital Terrain Model (DTM). Two areas were tested, based on the availability of ground reference points, both under trees and among vegetation, as well as on terrain. In addition, RGB and near-infrared UAV photography was captured and processed using Structure from Motion (SfM) and Multi View Stereo (MVS) algorithms to generate DSMs and corresponding colour and NIR orthoimages with 0.2 m and 0.25 m as pixel size respectively for the two test sites. Moreover, orthophotos were used to eliminate the vegetation from the DSMs using NDVI index, thresholding and masking. Following that, different interpolation algorithms, according to the test sites, were applied to fill in the gaps and created DTMs. Finally, a statistic analysis was made using reference terrain points captured on field, both on dead ground and under vegetation to evaluate the accuracy of the whole process and assess the overall accuracy of the derived DTMs in contrast with the DSMs.
SUPERVISED OUTLIER DETECTION IN LARGE-SCALE MVS POINT CLOUDS FOR 3D CITY MODELING APPLICATIONS
Authors: Stucker C. , Richard A. , Wegner J. D. , Schindler K.
Published: May 2018

Abstract. We propose to use a discriminative classifier for outlier detection in large-scale point clouds of cities generated via multi-view stereo (MVS) from densely acquired images. What makes outlier removal hard are varying distributions of inliers and outliers across a scene. Heuristic outlier removal using a specific feature that encodes point distribution often delivers unsatisfying results. Although most outliers can be identified correctly (high recall), many inliers are erroneously removed (low precision), too. This aggravates object 3D reconstruction due to missing data. We thus propose to discriminatively learn class-specific distributions directly from the data to achieve high precision. We apply a standard Random Forest classifier that infers a binary label (inlier or outlier) for each 3D point in the raw, unfiltered point cloud and test two approaches for training. In the first, non-semantic approach, features are extracted without considering the semantic interpretation of the 3D points. The trained model approximates the average distribution of inliers and outliers across all semantic classes. Second, semantic interpretation is incorporated into the learning process, i.e. we train separate inlieroutlier classifiers per semantic class (building facades, roof, ground, vegetation, fields, and water). Performance of learned filtering is evaluated on several large SfM point clouds of cities. We find that results confirm our underlying assumption that discriminatively learning inlier-outlier distributions does improve precision over global heuristics by up to ≈ 12 percent points. Moreover, semantically informed filtering that models class-specific distributions further improves precision by up to ≈ 10 percent points, being able to remove very isolated building, roof, and water points while preserving inliers on building facades and vegetation.
LAKE ICE MONITORING WITH WEBCAMS
Authors: Xiao M. , Rothermel M. , Tom M. , Galliani S. , Baltsavias E. , Schindler K.
Published: May 2018

Abstract. Continuous monitoring of climate indicators is important for understanding the dynamics and trends of the climate system. Lake ice has been identified as one such indicator, and has been included in the list of Essential Climate Variables (ECVs). Currently there are two main ways to survey lake ice cover and its change over time, in-situ measurements and satellite remote sensing. The challenge with both of them is to ensure sufficient spatial and temporal resolution. Here, we investigate the possibility to monitor lake ice with video streams acquired by publicly available webcams. Main advantages of webcams are their high temporal frequency and dense spatial sampling. By contrast, they have low spectral resolution and limited image quality. Moreover, the uncontrolled radiometry and low, oblique viewpoints result in heavily varying appearance of water, ice and snow. We present a workflow for pixel-wise semantic segmentation of images into these classes, based on state-of-the-art encoder-decoder Convolutional Neural Networks (CNNs). The proposed segmentation pipeline is evaluated on two sequences featuring different ground sampling distances. The experiment suggests that (networks of) webcams have great potential for lake ice monitoring. The overall per-pixel accuracies for both tested data sets exceed 95 %. Furthermore, per-image discrimination between ice-on and ice-off conditions, derived by accumulating per-pixel results, is 100 % correct for our test data, making it possible to precisely recover freezing and thawing dates.
LARGE SCALE TEXTURED MESH RECONSTRUCTION FROM MOBILE MAPPING IMAGES AND LIDAR SCANS
Authors: Boussaha M. , Vallet B. , Rives P.
Published: May 2018

Abstract. The representation of 3D geometric and photometric information of the real world is one of the most challenging and extensively studied research topics in the photogrammetry and robotics communities. In this paper, we present a fully automatic framework for 3D high quality large scale urban texture mapping using oriented images and LiDAR scans acquired by a terrestrial Mobile Mapping System (MMS). First, the acquired points and images are sliced into temporal chunks ensuring a reasonable size and time consistency between geometry (points) and photometry (images). Then, a simple, fast and scalable 3D surface reconstruction relying on the sensor space topology is performed on each chunk after an isotropic sampling of the point cloud obtained from the raw LiDAR scans. Finally, the algorithm proposed in (Waechter et al., 2014) is adapted to texture the reconstructed surface with the images acquired simultaneously, ensuring a high quality texture with no seams and global color adjustment. We evaluate our full pipeline on a dataset of 17 km of acquisition in Rouen, France resulting in nearly 2 billion points and 40000 full HD images. We are able to reconstruct and texture the whole acquisition in less than 30 computing hours, the entire process being highly parallel as each chunk can be processed independently in a separate thread or computer.
ROBUST AND ACCURATE IMAGE-BASED GEOREFERENCING EXPLOITING RELATIVE ORIENTATION CONSTRAINTS
Authors: Cavegn S. , Blaser S. , Nebiker S. , Haala N.
Published: May 2018

Abstract. Urban environments with extended areas of poor GNSS coverage as well as indoor spaces that often rely on real-time SLAM algorithms for camera pose estimation require sophisticated georeferencing in order to fulfill our high requirements of a few centimeters for absolute 3D point measurement accuracies. Since we focus on image-based mobile mapping, we extended the structure-from-motion pipeline COLMAP with georeferencing capabilities by integrating exterior orientation parameters from direct sensor orientation or SLAM as well as ground control points into bundle adjustment. Furthermore, we exploit constraints for relative orientation parameters among all cameras in bundle adjustment, which leads to a significant robustness and accuracy increase especially by incorporating highly redundant multi-view image sequences. We evaluated our integrated georeferencing approach on two data sets, one captured outdoors by a vehicle-based multi-stereo mobile mapping system and the other captured indoors by a portable panoramic mobile mapping system. We obtained mean RMSE values for check point residuals between image-based georeferencing and tachymetry of 2 cm in an indoor area, and 3 cm in an urban environment where the measurement distances are a multiple compared to indoors. Moreover, in comparison to a solely image-based procedure, our integrated georeferencing approach showed a consistent accuracy increase by a factor of 2–3 at our outdoor test site. Due to pre-calibrated relative orientation parameters, images of all camera heads were oriented correctly in our challenging indoor environment. By performing self-calibration of relative orientation parameters among respective cameras of our vehicle-based mobile mapping system, remaining inaccuracies from suboptimal test field calibration were successfully compensated.
INTERACTIVE CADASTRAL BOUNDARY DELINEATION FROM UAV DATA
Authors: Crommelinck S. , Höfle B. , Koeva M. N. , Yang M. Y. , Vosselman G.
Published: May 2018

Abstract. Unmanned aerial vehicles (UAV) are evolving as an alternative tool to acquire land tenure data. UAVs can capture geospatial data at high quality and resolution in a cost-effective, transparent and flexible manner, from which visible land parcel boundaries, i.e., cadastral boundaries are delineable. This delineation is to no extent automated, even though physical objects automatically retrievable through image analysis methods mark a large portion of cadastral boundaries. This study proposes (i) a methodology that automatically extracts and processes candidate cadastral boundary features from UAV data, and (ii) a procedure for a subsequent interactive delineation. Part (i) consists of two state-of-the-art computer vision methods, namely gPb contour detection and SLIC superpixels, as well as a classification part assigning costs to each outline according to local boundary knowledge. Part (ii) allows a user-guided delineation by calculating least-cost paths along previously extracted and weighted lines. The approach is tested on visible road outlines in two UAV datasets from Germany. Results show that all roads can be delineated comprehensively. Compared to manual delineation, the number of clicks per 100 m is reduced by up to 86 %, while obtaining a similar localization quality. The approach shows promising results to reduce the effort of manual delineation that is currently employed for indirect (cadastral) surveying.
Worm gear efficiency model considering misalignment in electric power steering systems
Authors: Kim Seong Han
Published: May 2018

Abstract. This study proposes a worm gear efficiency model considering misalignment in electric power steering systems. A worm gear is used in Column type Electric Power Steering (C-EPS) systems and an Anti-Rattle Spring (ARS) is employed in C-EPS systems in order to prevent rattling when the vehicle goes on a bumpy road. This ARS plays a role of preventing rattling by applying preload to one end of the worm shaft but it also generates undesirable friction by causing misalignment of the worm shaft. In order to propose the worm gear efficiency model considering misalignment, geometrical and tribological analyses were performed in this study. For geometrical analysis, normal load on gear teeth was calculated using output torque, pitch diameter of worm wheel, lead angle and normal pressure angle and this normal load was converted to normal pressure at the contact point. Contact points between the tooth flanks of the worm and worm wheel were obtained by mathematically analyzing the geometry, and Hertz's theory was employed in order to calculate contact area at the contact point. Finally, misalignment by an ARS was also considered into the geometry. Friction coefficients between the tooth flanks were also researched in this study. A pin-on-disk type tribometer was set up to measure friction coefficients and friction coefficients at all conditions were measured by the tribometer. In order to validate the worm gear efficiency model, a worm gear was prepared and the efficiency of the worm gear was predicted by the model. As the final procedure of the study, a worm gear efficiency measurement system was set and the efficiency of the worm gear was measured and the results were compared with the predicted results. The efficiency considering misalignment gives more accurate results than the efficiency without misalignment.
Assessment of liquefaction-induced hazards using Bayesian networks based on standard penetration test data
Authors: Tang Xiao-Wei , Bai Xu , Hu Ji-Lei , Qiu Jiang-Nan
Published: May 2018

Abstract. Liquefaction-induced hazards such as sand boils, ground
cracks, settlement, and lateral spreading are responsible for considerable
damage to engineering structures during major earthquakes. Presently, there
is no effective empirical approach that can assess different
liquefaction-induced hazards in one model. This is because of the
uncertainties and complexity of the factors related to seismic liquefaction
and liquefaction-induced hazards. In this study, Bayesian networks (BNs) are
used to integrate multiple factors related to seismic liquefaction, sand
boils, ground cracks, settlement, and lateral spreading into a model based on
standard penetration test data. The constructed BN model can assess four
different liquefaction-induced hazards together. In a case study, the BN
method outperforms an artificial neural network and Ishihara and Yoshimine's
simplified method in terms of accuracy, Brier score,
recall, precision, and area under the curve (AUC) of the receiver
operating characteristic (ROC). This demonstrates
that the BN method is a good alternative tool for the risk assessment of
liquefaction-induced hazards. Furthermore, the performance of the BN model in
estimating liquefaction-induced hazards in Japan's 2011 Tōhoku earthquake confirms its correctness and reliability compared with the
liquefaction potential index approach. The proposed BN model can also predict
whether the soil becomes liquefied after an earthquake and can deduce the
chain reaction process of liquefaction-induced hazards and perform backward
reasoning. The assessment results from the proposed model provide informative
guidelines for decision-makers to detect the damage state of a field
following liquefaction.