bluuebunny/crossref_metadata_2025 huggingface dataset:
Fundamentals and Applications of Red Light-Emitting Diodes (LEDs) In Vitro Plant Growth on Tomato Lycopersicon esculentum Mill
Authors: Thien Nguyen Phuc
Published: June 2019

The aim of these studies was mainly to investigate the effects of monochromatic LEDs applied singly on the in vitro plant growth and morphogenesis. Various morphological and physiological parameters are considered that influence the growth and development of plants in vitro under red LED light as compared to those under normal light. Upon exposure to LED, in vitro-raised plants have shown significant improvements in growth and morphogenesis. In particular, red and blue lights, either alone or in combination, have a significant influence on plant growth. The present study gives an overview of the fundamentals of LEDs and describes their effects on in vitro plant growth and morphogenesis and their future potentials. The main objective of this study was to carry out line and combing ability of plant growth on tomato.
Study on Service Life of OPC and HPC in Marine Environment
Authors: Chen Hao Yu
Published: June 2019

In this paper, ordinary Portland cement concrete (OPC) and high performance concrete (HPC) were used in the marine environment exposure experiments, Using the second Fick’s law, five parameter of life prediction model-binding ability, diffusion coefficient of free C1- time dependent parameters, chloride ion concentration of surface and degradation effect coefficients are confirmed. The service life of OPC and HPC in ocean conditions is calculated and compared using mathematic software in atmosphere region, underwater region and tidal zone.
Buckling Analysis of Variable Stiffness Composite Cylindrical Shells Based on Hermite Curves
Authors: Nian Chun Bo , Wang Xiao Ping , Pei Jing Yu
Published: June 2019

Based on the Hermite curve, the buckling behavior of a variable stiffness composite cylindrical shell is investigated. Firstly, the cylindrical shell is unfolded into a plane, and the Hermite curve is taken as the basic reference path on the plane and the variation of the fiber orientation is obtained. Then, the finite element analysis pre-processing program of the variable stiffness composite cylindrical shell is written by Python to develop ABAQUS interactive interface. Finally, the GUI plug-in is developed successfully, the buckling analysis of the constant stiffness and variable stiffness cylindrical shells is carried out and the effect of buckling load on the initial tangential direction q1, the initial point tangential magnitude L1, the end point tangential direction q2, the end point tangential magnitude L2 is preliminarily explored. It is found that the buckling load of the variable stiffness cylindrical shell is improved greatly. The secondary development of ABAQUS by Python is used to realize the automatic modeling and calculation analysis of the variable stiffness cylindrical shell parts, which provides research ideas and processes for practical engineering research, and has certain practical significance.
Elastoplastic Equilibrium of a Hollow Thick-Walled Radially Inhomogeneous Ball
Authors: Andreev Vladimir I.
Published: June 2019

The article deals with the axisymmetric elastoplastic problem for a hollow thick-walled ball (plane deformed state), loaded from the inside and outside by uniform pressures proportional to one parameter. The material is considered to be perfectly plastic, with the elastic modulus and yield strength generally are arbitrary functions of the radius. In addition, the material is considered to be incompressible in both plastic and elastic zones. On the basis of the criteria for the plasticity of Huber - Mises and Tresca - Saint-Venant, the radius at which the first plastic deformations occur is determined. It is shown that, depending on the functions of the inhomogeneity of elastic and plastic parameters and loads, the occurrence of plastic deformations is possible both on the surfaces and on the inner walls of the ball.
Study on Factors which Make CBN Insert can Turn S45C Steel Have Surface Roughness Less than Ra 0.4
Authors: Sriswat Manus , Kimapong Kittipong , Chanchana Atthakorn
Published: June 2019

Grinding process is necessary final process of making cylindrical parts with less than Ra 0.4 surface roughness. Generally we cannot obtain good surface quality without grinding process. As the experience of the authors, using CBN (Cubic Boron Nitride) insert to turning cylindrical parts could be obtained Ra 0.438 surface roughness. The surface roughness result is similar to ground parts. This result becomes the main focus of the study. Authors study to find out factors affecting CBN performance in turning with CBN to obtain less than Ra 0.4 surface roughness. According to the study, it was found that tool contact area allied to surface roughness. The experiment is turning S45C medium carbon steel under the following condition: Cutting speed is 300 m./min, Feed is 0.05 mm./rev and depth of cut is 0.1 mm. Experiment under the same condition in different contact area. Modify contact area of CBN insert to be 5,10,15,20 and 25 mm. and testing in order. CBN insert standard type contact area is 0 mm. Compare test results of modified CBN inserts with standard type result. The results of experiments were as follows: 1) Turning steel with CBN contact area 10 mm. was obtained Ra 0.456 surface roughness, 2) Turning steel with CBN contact area 15 mm. was obtained Ra 0.293 surface roughness, Thus less than Ra 0.4 surface roughness.
Investigation of Side-Dam Plate in Single-Wheel Caster for Casting Rods
Authors: Haga Toshio , Miyake Taisei
Published: June 2019

The cross section of a thin rod cast by a single-wheel caster, for which the wheel cross section is an inverted trapezoidal groove, is concave. To make the cross section convex, an inner side-dam plate is proposed. A single-wheel caster with a flat wheel (without a groove) and rotating side-dam plates is also proposed. 5182 aluminum alloy rods with a convex or rectangular cross section can be cast. The area of the rod is smaller than 150 mm2. The diameter of the converted circle area is 15 mm.
Forming of Small Projection on Roll-Cast A356 Strip by Cold Rolling and Small Groove on PET Plate Using A356 Die
Authors: Haga Toshio , Nakazawa Yhuta
Published: June 2019

A small projection with a height and width of about 40 and 50 µm, respectively, was formed on a twin-roll-cast A356 aluminum alloy sheet by cold rolling at a rolling speed of 0.5 m/min. This projection was then used as a die to form a groove with a depth and width of about 40 and 50 µm, respectively, on a polyethylene terephthalate plate by pressing.
Mechanical Properties of PP/clay Nanocomposites Prepared from Masterbatch: Effect of Nanoclay Loadings and Re-Processing
Authors: Chafidz Achmad , Tamzysi Cholila , Kistriyani Lilis , Kusumaningtyas Ratna Dewi , Hartanto Dhoni
Published: June 2019

PP/clay nanocomposites samples of 1st and 2nd cycles (recycle) and different nanoclay loadings (i.e. 0, 5, 10, 15 wt%) samples were made by utilizing twin-screw extruder and injection molding machine. The samples were then characterized using a tensile test machine. The tensile tests results showed that modulus of elasticity and tensile strength of the nanocomposites samples for both 1st and 2nd cycles were all higher than the neat PP, and increased with increasing nanoclay loadings. The enhancements of modulus of elasticity (as compared to the neat PP) for 1st cycle of the nanocomposites were about 38.08%, 49.33%, and 78.65% for NC-5-I, NC-10-I, and NC-15-I, respectively. Whereas, for the 2nd cycle of the nanocomposites were about 44.33%, 59.59%, and 84.69% for NC-5-II, NC-10-II, and NC-15-I, respectively. This indicated that the incorporation of nanoclay in the PP matrix significantly increased mechanical properties, especially modulus of elasticity and tensile strength of the nanocomposites. Additionally, values of modulus of elasticity and tensile strength of 1st cycle and 2nd cycle of PP/clay nanocomposites were compared by plotting them in two graphs. The plots revealed that reprocessing of the nanocomposites did not significantly influence the mechanical properties of the nancomposites.
Physical and Mechanical Properties of Bi0.5(Na0.81K0.19)0.5TiO3 Ceramic Modified by KNbO3
Authors: Inthong Suchittra , Kruae-In Chatchai , Thanomsiang Wuttikrai , Kosolwattana Suppanat , Sweatman Denis Russell , Eitssayeam Sukum , Tunkasiri Tawee
Published: June 2019

This research reports the physical and mechanical properties of (1-x) Bi0.5(Na0.81K0.19)0.5TiO3-xKNbO3 (x=0.00-0.06) ceramics. The Modified Bi0.5(Na0.81K0.19)0.5TiO3 ceramics were synthesized by solid state reaction technique. The mixed oxides powders were calcined at 850 °C, 4 h and sintered at 1120 °C, 2 h to form pure phase perovskite and the optimum bulk density, respectively. The phase formation of the modified ceramic samples was determined by X-ray diffraction technique. All of the modified Bi0.5(Na0.81K0.19)0.5TiO3 ceramics exhibited a single perovskite phase. The bulk densities of the modified ceramic samples were 5.41±0.27-5.75±0.28 g/cm3 using the Archimedes’ method. The microstructure was revealed by the scanning electron microscope. The rectangular-like shape was found of all studied ceramics which had the grain size between 1.31±0.02-1.56±0.03 mm. The mechanical properties were studied by both Vickers and Knoop microhardness tester. The results are discussed in term of the relation among hardness properties, Young’s modulus, and fracture toughness.
Sec62 Suppresses Foot-and-Mouth Disease Virus Proliferation by Promotion of IRE1α–RIG-I Antiviral Signaling
Authors: Han Shichong , Mao Lejiao , Liao Ying , Sun Shiqi , Zhang Zhihui , Mo Yaxia , Liu Haiyun , Zhi Xiaoying , Lin Shunmei , Seo Ho Seong , Guo Huichen
Published: June 2019

Foot-and-mouth disease virus (FMDV) is highly infectious and causes a major plague in animal farming. Unfolded protein response is one of the major cellular responses to pathogenic infections, which performs a crucial role in cell survival, apoptosis, and antiviral innate immune response. In this study, we showed that FMDV infection activated two unfolded protein response branches (PERK-eIF2α and ATF6 signaling) in both baby hamster kidney cells (BHK-21) and porcine kidney (PK-15) cells, whereas it suppressed the IRE1α-XBP1 signaling by decreasing IRE1α level. Further study revealed IRE1α signaling as an important antiviral innate immune mechanism against FMDV. Sec62, the transport protein, was greatly decreased at the late stages of FMDV infection. By overexpression and knockdown study, we also found that the expression of Sec62 was positively involved in the levels of IRE1α and RIG-I and subsequent activation of downstream antiviral signaling pathways in FMDV-infected PK-15 cells. Taken together, our study demonstrates that Sec62 is an important antiviral factor that upregulates IRE1α–RIG-I–dependent antiviral innate immune responses, and FMDV evades antiviral host defense mechanism by downregulating Sec62-IRE1α/RIG-I.
Lipopolysaccharide-Stimulated Human Fetal Membranes Induce Neutrophil Activation and Release of Vital Neutrophil Extracellular Traps
Authors: Tong Mancy , Potter Julie A. , Mor Gil , Abrahams Vikki M.
Published: June 2019

Preterm birth is a major contributor to neonatal mortality and morbidity, and infection is a major risk factor. Chorioamnionitis, inflammation of the placenta, and fetal membranes (FMs) are commonly observed in preterm birth and are characterized by neutrophil infiltration. However, interactions between FMs and neutrophils remain incompletely understood. The objectives of this study were to determine how FMs, with or without bacterial LPS stimulation, affect neutrophil recruitment, activation, and the formation of neutrophil extracellular traps (NETs) and to elucidate the signaling mechanisms involved. Using a combination of in vitro, ex vivo, and in vivo approaches, we show that human resting FMs can directly recruit neutrophils and induce them to produce proinflammatory factors. Furthermore, neutrophils release vital NETs in response to FM-derived factors. LPS-stimulated FMs further augmented neutrophil recruitment, inflammatory cytokine/chemokine secretion, and vital NET release and also induced reactive oxygen species production and degranulation. We demonstrate a role for FM-derived TNF-α in mediating these effects through activation of neutrophil p38 MAPK. We propose that, during infection, neutrophil recruitment and activation may neutralize pathogens, vital NET formation, and prolonged neutrophil viability, and in combination with degranulation, reactive oxygen species production and inflammatory chemokine/cytokine production may contribute to tissue injury at the maternal/fetal interface.
Helios Deficiency Predisposes the Differentiation of CD4+Foxp3− T Cells into Peripherally Derived Regulatory T Cells
Authors: Skadow Mathias , Penna Vinay R. , Galant-Swafford Jessica , Shevach Ethan M. , Thornton Angela M.
Published: June 2019

The transcription factor Helios is expressed in a large percentage of Foxp3+ regulatory T (Treg) cells and is required for the maintenance of their suppressive phenotype, as mice with a selective deficiency of Helios in Treg cells spontaneously develop autoimmunity. However, mice with a deficiency of Helios in all T cells do not exhibit autoimmunity, despite the defect in the suppressor function of their Treg cell population, suggesting that Helios also functions in non-Treg cells. Although Helios is expressed in a small subset of CD4+Foxp3− and CD8+ T cells and its expression is upregulated upon T cell activation, its function in non-Treg cells remains unknown. To examine the function of Helios in CD4+Foxp3− T cells, we transferred Helios-sufficient or -deficient naive CD4+Foxp3− TCR transgenic T cells to normal recipients and examined their capacity to respond to their cognate Ag. Surprisingly, Helios-deficient CD4+ T cells expanded and differentiated into Th1 or Th2 cytokine-producing effectors in a manner similar to wild-type TCR transgenic CD4+ T cells. However, the primed Helios-deficient cells failed to expand upon secondary challenge with Ag. The tolerant state of the Helios-deficient memory T cells was not cell-intrinsic but was due to a small population of Helios-deficient naive T cells that had differentiated into Ag-specific peripheral Treg cells that suppressed the recall response in an Ag-specific manner. These findings demonstrate that Helios plays a role in the determination of CD4+ T cell fate.
CanCoast 2.0: data and indices to describe the sensitivity of Canada's marine coasts to changing climate
Authors: Manson G K , Couture N J , James T S
Published: June 2019

Baseline mapping of coastal characteristics and understanding of the dynamic response of coastal sensitivity to environmental changes provide a strong foundation for climate change adaptation in Canada's coastal regions. CanCoast is a collection of datasets that
describe the physical characteristics of Canada's marine coasts. It includes datasets that are not expected to change through time (such as coastal materials and backshore slope), and some that are projected to change as climate changes (such as wave height and mean sea level). CanCoast includes:
sea-level change (early and late 21st century); wave-heights including the effects of sea ice (early and late 21st century); ground ice content; coastal materials; tidal range; and backshore slope. These are mapped to a common high-resolution shoreline and used to calculate indices that show the
generalised coastal sensitivity of Canada's marine coasts in early and late 21st century climates, and the spatially-variable change in sensitivity between the early and the late 21st century. Because of the scales of the input data, the generalised indices are best used to identify regions that
differ in sensitivity to changing climate, rather than local properties or coastal infrastructure with specific characteristics that cannot be resolved in this national-scale approach.
An organic geochemical study of outcrop oil shows in the Colville Hills, Mackenzie Corridor: oil-saturated Quaternary sand and Cretaceous sandstone and oil-stained Devonian dolostone
Authors: Jiang C , Fallas K M , MacNaughton R
B
Published: June 2019

Outcrop samples collected from some visually oil-stained or oil-saturated exposures in the Colville Hills area were submitted for bulk and molecular organic geochemical analyses to investigate their crude oil quality, sources of the hydrocarbons, and/or their
potential as petroleum source rocks. Results show that the apparently oil-stained Devonian Bear Rock Formation dolostone interval at Lac à Jacques cannot be considered as an effective source rock due to its low content of organic matter, nor can it be an efficient reservoir rock due to its low
oil content. The Quaternary (?) oil sand deposit at Lac des Bois and the oil-saturated Cretaceous sandstone at Belot Ridge both contain hydrocarbons that have been subjected to very heavy to severe biodegradation, with a majority of their saturated and aromatic compounds having been removed due to
microbial activities. Within their saturated and aromatic fractions only terpane biomarkers can be detected in these bituminous sands or sandstone. Although the characteristics of their main source rocks cannot be ascertained, their different distributions of tri-, tetra- and penta-cyclic terpanes
appear to indicate that oil charges to the Quaternary sand at Lac des Bois and the Cretaceous sandstone at Belot Ridge are from source rock units developed within different depositional environments.
The impact of cervicogenic headache on patients attending a private physiotherapy practice in Cape Town
Authors: Diener I.
Published: June 2019

Headache (HA) disorders constitute a public health problem which impacts on individuals and on society. The functional limitations and participation restrictions caused by chronic HA’s may be a more reliable indication of the severity of the disorder than the intensity and HA pattern itself. Evaluation of all these parameters may assist holistic assessment, with impact on the health care of chronic HA sufferers. A quantitative retrospective study of 450 patients’ perceptions of the impact of chronic recurrent cervicogenic HA (CRCHA) was done by reviewing clinical notes made at first consultation. Bio-demographic data, Total Pain Pattern and impact of HA’s on function, relationships and emotions were recorded using Likert scales. High scores were reported for severe functional disability (60% of the subjects), for considerable emotional handicap (41%) and for negative impact on close relationships (86%). Decreased productivity was reported by 89% of the population studied. Subjects expressed emotions of anxiety (75%), anger (48%) and helplessness (62%). CRCHA has a severe impact on the health-related quality of life of individuals. A combination of these results and existing instruments is currently being used to develop a measuring instrument reflecting a bio-psychosocial approach to assessment. This may improve physiotherapy management of CRCHA patients and may facilitate outcome-based research in this field.
Analysis of technological knowledge flows in the Basque Country
Authors: Gavilanes-Trapote J. , Etxeberria-Agiriano I. , Cilleruelo E. , Garechana G.
Published: June 2019

Knowledge flow of technology is important for continuous growth and extension of science. Patent data analysis has facilitated this knowledge acquisition. The available patent information crosses borders, corresponds and interacts with new inventions to give new strength and dimension to the technology. Therefore, the patent citation information functions as a key indicator of the knowledge flow providing relevant information. It can be identified to which extent a region is a relevant technological knowledge generator to other regions. As an illustrative case, we present a study to determine the role played by the Basque Country region as a generator of technological innovation during the period 1991-2011.
Patentometric: monitoring the scientific and technological trends of Additive Manufacturing in Medical Applications
Authors: Alvarez-Meaza I. , Zarrabeitia-Bilbao E. , Rio-Belver R.M. , Martinez de Alegria I. , Bildosola I.
Published: June 2019

Patents are a means of protecting inventions developed by firms, institutions or individuals, and they may be interpreted as indicators of invention. Patents indicators convey information on the processes of inventive activities. Therefore, patent statistics will assess science and technology (S&T) activities. Besides, additive manufacturing (AM) has become a revolutionary technology that is changing medical science. For this reason, the patent statistics will allow us to monitor what is the state of the inventive activity of AM in medical applications. The database used in order to retrieve patent information is Patseer and the data have been analyzed through the analytics package called Quick Stats. From the data obtained, it can be concluded that, additive manufacturing in medical applications is an emerging technology with huge market potential. Undoubtedly, the core of invention is located in United States, followed by Germany, United Kingdom and China somewhat behind. Firms are the main holders of legal rights, and the firm’s market value and the knowledge diffusion of technology are ensured by the technological diversity and the number of forward citations presented by patents.
Special issue: Advances in Engineering Networks
Authors: De Castro R. , Gimenez G. , Mula J. , Boza A. , Cuenca Ll. , Gómez-Gasquet P. , Vicens-Salort E.
Published: June 2019

This special issue of the International Journal of Production Management and Engineering is dedicated on the most recent and relevant research, theories and practices in Industrial Engineering and Operations Management presented at the 12th International Conference on Industrial Engineering and Industrial Management and XXII Congreso de Ingeniería de Organización - CIO18.
Auroral hydrogen emissions: a historic survey
Authors: Egeland Alv , Burke William J.
Published: June 2019

Abstract. Auroral spectroscopy provided the first tool for remotely sensing the compositions and dynamics of the high-latitude ionosphere. In 1885, Balmer discovered that the visible hydrogen spectrum consists of a series of discrete lines whose wavelengths follow a simple mathematical pattern, which ranks among the first steps toward developing this tool. On 18 October 1939 Lars Vegard discovered the Hα (656.3 nm) and Hβ (486.1 nm) spectral lines of Balmer series emissions, emanating from a diffuse structure, located equatorward of the auroral zone. Intense, first positive bands of N2+ nearly covered the Hα emissions. With more advanced instrumentation after World War II, auroral spectroscopists Vegard, Gartlein and Meinel investigated other characteristics of the auroral hydrogen emissions. The first three lines of the Balmer series, including Hγ at 410 nm, were identified in ground-based measurements prior to the space age. Based on satellite observations, the Balmer lines Hδ and Hε at 410.13 and 396.97 nm, respectively, as well as extreme ultraviolet (EUV) Lyman α (121.6 nm) hydrogen emissions, were also detected. Doppler blue shifts in hydrogen emissions, established in the 1940s, indicated that emitting particles had energies well into the kiloelectron volt range, corresponding to velocities >1000 km s−1. Systematic spatial separations between the locations of electron- and proton-generated aurorae were also established. These observations in turn, suggested that protons, ultimately of solar origin, precipitate into the topside ionosphere, where they undergo charge-exchange events with atmospheric neutrals. Newly generated hydrogen atoms were left in excited states and emitted the observed Balmer radiation. Sounding rocket data showed that most of the hydrogen radiation came from altitudes between 105 and 120 km. Space-age data from satellite-borne sensors made two significant contributions: (1) energetic particle detectors demonstrated the existence of regions in the magnetosphere, conjugate to nightside proton aurora, where conditions for breaking the first adiabatic invariants of kiloelectron volt protons prevail, allowing them to precipitate through filled loss cones. (2) EUV imagers showed that dayside hydrogen emissions appear in response to changes in solar wind dynamic pressure or the polarity of the north–south component of the interplanetary magnetic field.
CLASSIFICATION OF MOBILE LIDAR DATA USING VOX-NET AND AUXILIARY TRAINING SAMPLES
Authors: He H. , Khoshelham K. , Fraser C.
Published: June 2019

Abstract. The classification of mobile Lidar data is challenged by the complexity of objects in the point clouds and the limited number of available training samples. Incomplete shape, noise points and uneven point density make the extraction of features from point clouds relatively arduous. Additionally, the difference in point density, and size and shape of objects, restricts the utilization of labelled samples from other sources. To solve this problem, we explore the possibility of improving the classification performance of a state-of-the-art deep learning method, Vox-Net, by using auxiliary training samples from a different dataset. We compare the performance of Vox-Net trained with and without the auxiliary dataset. The comparison shows that more instances can be recognized in classes with auxiliary data. At the same time, the performance in classes without complementary data can deteriorate due to the low number of samples in these categories. To achieve a balance in the performance for different categories, we further replace the classification layer of Vox-Net with AdaBoost. The AdaBoost classification displays good recognition ability in classes with few instances but decreases the overall accuracy.
CLASSIFICATION OF AERIAL POINT CLOUDS WITH DEEP LEARNING
Authors: Özdemir E. , Remondino F.
Published: June 2019

Abstract. Due to their usefulness in various implementations, such as energy evaluation, visibility analysis, emergency response, 3D cadastre, urban planning, change detection, navigation, etc., 3D city models have gained importance over the last decades. Point clouds are one of the primary data sources for the generation of realistic city models. Beside model-driven approaches, 3D building models can be directly produced from classified aerial point clouds. This paper presents an ongoing research for 3D building reconstruction based on the classification of aerial point clouds without given ancillary data (e.g. footprints, etc.). The work includes a deep learning approach based on specific geometric features extracted from the point cloud. The methodology was tested on the ISPRS 3D Semantic Labeling Contest (Vaihingen and Toronto point clouds) showing promising results, although partly affected by the low density and lack of points on the building facades for the available clouds.
EXTRACTION AND SHAPE RECONSTRUCTION OF GUARDRAILS USING MOBILE MAPPING DATA
Authors: Matsumoto H. , Mori Y. , Masuda H.
Published: June 2019

Abstract. The mobile mapping system (MMS) can acquire dense point-clouds of roads and roadside features. Roads are often separated into roadways and walkways in many urban areas. Since guardrails are installed to separate roadways and sidewalks, it is important to detect guardrails from point-clouds and reconstruct their 3D models for 3D street maps. Since there are a large variety of designs for guardrails in Japan, flexible methods are required for detection and reconstruction of guardrails. In this paper, we propose a new method for extracting guardrails from point-clouds, and reconstructing their 3D models. Since the MMS captures point-clouds and camera images synchronously, guardrails are detected using both point-clouds and images. In our method, point-clouds are segmented into small segments, and corresponding images are cropped from camera images. Then cropped images are classified into two classes of guardrails and others using the convolutional neural network. When guardrail points are obtained, 3D models of guardrails are reconstructed. However, point-clouds of guardrails are too sparse to reconstruct 3D shapes when guardrails consist of thin pipes. Since the same unit shape repeatedly appears in a guardrail, we create dense point-clouds by superimposing points of unit shapes. Then we reconstruct 3D shapes of pipes, beams, and poles of guardrails. In our evaluation using point-clouds in urban areas, our method could achieve good results of extraction and shape reconstruction of guardrails.
CLASSIFICATION OF AERIAL LASER SCANNING POINT CLOUDS USING MACHINE LEARNING: A COMPARISON BETWEEN RANDOM FOREST AND TENSORFLOW
Authors: Pirotti F. , Tonion F.
Published: June 2019

Abstract. In this investigation a comparison between two machine learning (ML) models for semantic classification of an aerial laser scanner point cloud is presented. One model is Random Forest (RF), the other is a multi-layer neural network, TensorFlow (TF). Accuracy results were compared over a growing set of training data, using a stratified independent sampling over classes from 5% to 50% of the total dataset. Results show RF to have average F1 = 0.823 for the 9 classes considered, whereas TF had average F1 = 0.450. F1 values where higher for RF than TF, due to complexity in the determination of a suitable composition of the hidden layers of the neural network in TF, and this can likely be improved to reach higher accuracy values. Further study in this sense is planned.
COMPARISON OF TRAINING STRATEGIES FOR CONVNETS ON MULTIPLE SIMILAR DATASETS FOR FACADE SEGMENTATION
Authors: Schmitz M. , Huang H. , Mayer H.
Published: June 2019

Abstract. In this paper, we analyze different training strategies and accompanying architectures for Convolutional Networks (ConvNets) when multiple similar datasets are available using the semantic segmentation of rectified facade images as example. Additionally to direct training on the target dataset we analyze multi-task learning and fine-tuning. When using multi-task learning to train a ConvNet, multiple objectives are optimized in parallel. Fine-tuning optimizes these objectives sequentially. For both strategies, the tasks share a common part of the ConvNet for which we vary the depth. We present results for all strategies and compare them regarding the overall pixel-wise accuracy and show that for the special case of facade segmentation there are no significant differences using multiple datasets or not or training a ConvNet with different strategies.
TRAJECTORY-BASED VISUALIZATION OF MMS POINT CLOUDS
Authors: Takahashi G. , Masuda H.
Published: June 2019

Abstract. MMSs allow us to obtain detailed 3D information around roads. Especially, LiDAR point clouds can be used for map generation and infrastructure management. For practical uses, however, it is necessary to add labels to a part of the points since various objects can be included in the point clouds. Existing automatic classification methods are not completely error-free, and may incorrectly classify objects. Therefore, even though automatic methods are applied to the point clouds, operators have to verify the labels. While operators classify the point clouds manually, selecting 3D points tasks in 3D views are difficult. In this paper, we propose a new point-cloud image based on the trajectories of MMSs. We call our point-cloud image trajectory-based point-cloud image. Although the image is distorted because it is generated based on rotation angles of laser scanners, we confirmed that most objects can be recognized from point-cloud images by checking main road facilities. We evaluated how efficient the annotation can be done using our method, and the results show that operators could add annotations to point-cloud images more efficiently.
CLOUD-BASED SOLUTION FOR NATIONWIDE POWER LINE MAPPING
Authors: Toschi I. , Morabito D. , Grilli E. , Remondino F. , Carlevaro C. , Cappellotto A. , Tamagni G. , Maffeis M.
Published: June 2019

Abstract. Automatic tools for power line mapping and monitoring are increasingly required by modern societies. Since traditional methods, like ground-based onsite inspections, are very labour- and time-intensive, the use of Geomatics techniques is becoming the most promising solution. However, there is a need for an all-in-one solution that allows the entire 3D mapping pipeline in a nationwide data context. The aim of this paper is to introduce a novel cloud-based solution for nationwide power line mapping. The innovative aspects of the system are threefold. First, to exploit image-based 3D reconstruction algorithms to derive dense point clouds over power line corridors, thus demonstrating the potential of photogrammetry as a promising alternative to costly LiDAR surveys. Second, to supply an all-in-one web-based pipeline that automatically manages all steps of power line mapping, from 3D data generation to clearance anomaly detection. Finally, to exploit cloud-computing technology, to handle massive input data. First tests show promising results for (i) 3D image-based reconstruction, (ii) point cloud classification and (iii) anomaly detection.
TOWARDS BETTER CLASSIFICATION OF LAND COVER AND LAND USE BASED ON CONVOLUTIONAL NEURAL NETWORKS
Authors: Yang C. , Rottensteiner F. , Heipke C.
Published: June 2019

Abstract. Land use and land cover are two important variables in remote sensing. Commonly, the information of land use is stored in geospatial databases. In order to update such databases, we present a new approach to determine the land cover and to classify land use objects using convolutional neural networks (CNN). High-resolution aerial images and derived data such as digital surface models serve as input. An encoder-decoder based CNN is used for land cover classification. We found a composite including the infrared band and height data to outperform RGB images in land cover classification. We also propose a CNN-based methodology for the prediction of land use label from the geospatial databases, where we use masks representing object shape, the RGB images and the pixel-wise class scores of land cover as input. For this task, we developed a two-branch network where the first branch considers the whole area of an image, while the second branch focuses on a smaller relevant area. We evaluated our methods using two sites and achieved an overall accuracy of up to 89.6% and 81.7% for land cover and land use, respectively. We also tested our methods for land cover classification using the Vaihingen dataset of the ISPRS 2D semantic labelling challenge and achieved an overall accuracy of 90.7%.
LAVA DOME CHANGES DETECTION AT AGUNG MOUNTAIN DURING HIGH LEVEL OF VOLCANIC ACTIVITY USING UAV PHOTOGRAMMETRY
Authors: Andaru R. , Rau J.-Y.
Published: June 2019

Abstract. Lava dome changes detection during increasingly high volcanic activity are essential for hazard assessment purposes. However, it is challenging to conduct direct field measurement due to safety reason. Here, we investigate the lava dome changes of Mount Agung in Indonesia during the highest level of volcanic activity. On 22 September 2017, the rumbling and seismic activity in this volcano started increasing to the highest level for a period of time. We afterwards collected image data at lava dome area by using UAV over this time period. To accomplish the goal of change detection, we assembled and developed a fixed-wing UAV platform, i.e. Buffalo FX-79 to acquire images of Mount Agung whose elevation is roughly 3,142 m above sea level. We acquired the UAV images on two dates, i.e. Oct 19 and Oct 21 of 2017. Due to an exclusion zone surround the volcano, we could only operate the UAV at 20 km distance from the crater. With these data set, we produced three-dimensional point clouds, high-resolution Digital Elevation Model and orthophoto by using Structure from Motion (SfM) and Multi View Stereo (SfM-MVS) technique with Photoscan Pro software. From orthophoto data, we found two fluid areas at the crater's surface in NE direction (4,375.9 sq-m) and SE direction (3,749.8 sq-m). We also detected a fumarole which emitted steam and gases in the eastern part that continued for several days. In order to reveal the changes in lava dome surface, we used DEM to create cross-section profile. After that, we applied cloud to cloud comparison (C2C) algorithm to calculate the difference of lava dome based on two data set of point clouds and compared it with interferometric result from Sentinel-1A data. The data from the Sentinel-1A satellite (15 Oct – 27 Oct 2017) were processed to obtain the interferogram image of Mount Agung. This research therefore demonstrates a potential method to detect lava dome changes during high level of volcanic activity with photogrammetric methods by using UAV images. Within only two days the data were successfully acquired. From the DEM data and cross-section profile between two data set, we noticed that no significant surface change was found around the lava dome surface. Moreover, we also found that there was no significant lava dome changes and vertical displacement during these two time periods as the point cloud comparison and distance result. The average of difference distance is 2.27 cm with a maximal and minimal displacement of 255 cm and 0.37 cm respectively. This result was then validated by using InSAR Sentinel that showed small displacement, i.e 6.88 cm. It indicated that UAV photogrammetry showed a good performance to detect surface changes in centimeter fraction.
MASS MOVEMENTS OF AN ALPINE ROCK GLACIER
Authors: Boesch R. , Graf C.
Published: June 2019

Abstract. Rock glaciers, tonguelike bodies consisting of angular rock debris frozen in interstitial ice, may flow with velocities varying from a few centimeter up to several meters per year. Recent ground warming may generate an accelerated slope movement related to permafrost creep. Newer generations of commercial off-the-shelf drones like DJI Mavic are cost-effective, lightweight and still have a sufficient pay load reserve for flights at 2800 m.a.s.l. This allows that a two men crew can carry the necessary reference and drone equipment in a high alpine environment and a flight campaign can be conducted within one day. Using different cameras with similar optical resolution allows to generate DSMs with comparable accuracy. The DSM resolution should be 10 cm or better to achieve robust results. Motion tracking of rock glacier with tie point matching algorithms SIFT or SURF combined with an appropriate filter method allows to distinguish different movement patterns within local neighborhood. Compared to point-wise GPS-based methods or image-based cross-correlation approaches, tie point matching allows to detect inhomogeneous movement patterns, which are typical for rock glaciers in a high alpine environment.
WHEAT LODGING ASSESSMENT USING MULTISPECTRAL UAV DATA
Authors: Chauhan S. , Darvishzadeh R. , Lu Y. , Stroppiana D. , Boschetti M. , Pepe M. , Nelson A.
Published: June 2019

Abstract. Lodging is a major yield-reducing factors in wheat, causing reductions up to 80%. Timely detection of lodging can reduce its impacts and support proper decisions regarding expected yield, crop price or its insurance. Since the incidence of lodging is heterogeneous within a field, very high-resolution remote sensing data can be viable for accurate and prompt spatio-temporal assessment of lodging severity. As such unmanned aerial vehicles (UAVs) provide a versatile and cost-effective solution to monitor crops on a small scale with sub-centimetre spatial resolution. In this study, we analysed the spectral variability between different grades of lodging severity (non-lodged (NL), moderate (ML), severe (SL) and very severe (VSL)) and classified them using high-resolution UAV data. Multispectral orthomosaic UAV images with 5cm resolution and nine bands (covering the VIS-NIR spectrum with Sentinel-2 filters) were acquired in May 2018 for two wheat fields in Bonifiche Ferraresi farm, Jolanda di Savoia, Italy. Concurrent to the time of image acquisition, a field campaign was carried out in which crop characteristics and lodging related parameters were collected. The results showed that reflectance magnitude increased with lodging severity and demonstrated that the red-edge and NIR bands can be used to clearly discriminate between NL and lodged (all grades) wheat and to some extent between different lodging classes (ML, SL and VSL). The nearest neighbourhood classification performed using an object-based segmentation yielded optimal results with an overall accuracy of 90%, thus demonstrating the use of multispectral UAV data as a promising tool for wheat lodging assessment.
UAV DIRECT GEOREFERENCING APPROACH IN AN EMERGENCY MAPPING CONTEXT. THE 2016 CENTRAL ITALY EARTHQUAKE CASE STUDY
Authors: Chiabrando F. , Giulio Tonolo F. , Lingua A.
Published: June 2019

Abstract. UAVs platform are increasingly deployed by first responders and local stakeholders to get a first overview of disaster affected areas with a high level of detail and different off-nadir angle configurations. Through a rapid mapping approach, the acquired data (video sequences or pictures) are analysed to extract information on damages to buildings and infrastructures with the goal to support the Search and Rescue operations. The specific focus of the paper is on evaluating the expected benefits (from the rapid mapping perspective) deriving from a direct georeferencing approach when using UAV with RTK capabilities. Specifically, data acquired by a fixed wing eBee RTK platform by SenseFly over the areas affected by the earthquake that hit central Italy in 2016 have been processed to compare the positional accuracies of orthoimagery generated by means of a direct georeferencing approach (without any GPC) with and without a post-processing kinematic solution. The results highlight that an RTK-enabled platform allows to achieve orthoimagery positioning accuracy values up to few centimeters without the need of any control point. In the conclusion session the operational implications of a PPK-based approach versus a standard direct georeferencing are critically discussed.
R&D OF DRONE-BORNE SAR SYSTEM
Authors: Deguchi T. , Sugiyama T. , Kishimoto M.
Published: June 2019

Abstract. DInSAR (Differential Interferometric Synthetic Aperture Radar) is already well-known as an effective application technique of SAR data for the displacement measuring of the ground surface. The authors are developing a drone-borne SAR that can apply DInSAR analysis. In Japan, which has suffered various disasters, the slope stability monitoring for active volcanoes, landslide slopes, open-pit mines, etc., and the maintenance management for aging infrastructures are considered important issues. Therefore, by effectively utilizing the position information and terrain information obtained from the satellite data, we have started an R&D project aiming at practical application of DInSAR technology with drone-borne SAR.
SUPPORT VECTOR MACHINE AND DECISION TREE BASED CLASSIFICATION OF SIDE-SCAN SONAR MOSAICS USING TEXTURAL FEATURES
Authors: Febriawan H. K. , Helmholz P. , Parnum I. M.
Published: June 2019

Abstract. The diversity and heterogeneity of coastal, estuarine and stream habitats has led to them becoming a prevalent topic for study. Woody ruins are areas of potential riverbed habitat, particularly for fish. Therefore, the mapping of those areas is of interest. However, due to the limited visibility in some river systems, satellites, airborne or other camera-based systems (passive systems) cannot be used. By contrast, sidescan sonar is a popular underwater acoustic imaging system that is capable of providing high- resolution monochromatic images of the seafloor and riverbeds. Although the study of sidescan sonar imaging using supervised classification has become a prominent research subject, the use of composite texture features in machine learning classification is still limited. This study describes an investigation of the use of texture analysis and feature extraction on side-scan sonar imagery in two supervised machine learning classifications: Support Vector Machine (SVM) and Decision Tree (DT). A combination of first- order texture and second-order texture is investigated to obtain the most appropriate texture features for the image classification. SVM, using linear and Gaussian kernels along with Decision Tree classifiers, was examined using selected texture features. The results of overall accuracy and kappa coefficient revealed that SVM using a linear kernel leads to a more promising result, with 77% overall accuracy and 0.62 kappa, than SVM using either a Gaussian kernel or Decision Tree (60% and 73% overall accuracy, and 0.39 and 0.59 kappa, respectively). However, this study has demonstrated that SVM using linear and Gaussian kernels as well as a Decision Tree makes it capable of being used in side-scan sonar image classification and riverbed habitat mapping.
PRELIMINARY EVALUATION OF ATMOSPHERIC TEMPERATURE AND WIND PROFILES OBTAINED USING UNMANNED AERIAL VEHICLE BASED ACOUSTIC TOMOGRAPHY
Authors: Finn A. , Rogers K. , Meade J. , Skinner J. , Zargarian A.
Published: June 2019

Abstract. An acoustic signature generated by an unmanned aerial vehicle is used in conjunction with tomography to remotely sense temperature and wind profiles within a volume of atmosphere up to an altitude of 120 m and over an area of 300 m × 300 m. Sound fields recorded onboard the aircraft and by an array of microphones on the ground are compared and converted to sound speed estimates for the ray paths intersecting the intervening medium. Tomographic inversion is then used to transform these sound speed values into three-dimensional profiles of virtual temperature and wind velocity, which enables the atmosphere to be visualised and monitored over time. The wind and temperature estimates obtained using this method are compared to independent measurements taken by a co-located mid-range ZephIR LIDAR and sensors onboard the aircraft. These comparisons show correspondences to better than 0.5 °C and 0.3 m/s for temperature and wind velocity, respectively.
AN ADVANCED BENCHMARKING FOR IMAGE COMPOSITING EVALUATION
Authors: Giudici R. , Courtrai L. , Lefevre S.
Published: June 2019

Abstract. This paper introduces a novel benchmarking tool for measuring the robustness of existing mosaicing algorithms in presence of a given set of disturbances. The process combines a set of partially overlapping images into a wide-view result used to represent UAV image series and orthophotography. Geometrical misalignements caused by perspective error may lead to some unpredictable artifacts and phantom effects in the mosaics. A very few solutions measure their immunity to known distortions and mainly focus on registration accuracy measurement. Only limited attention was given to characterize the response of the actual image fusion algorithms and their capacity to properly preserve content geometries. In this paper, we also introduce a new fidelity metric assessing the mosaicing response to a disturbance of a given extent used as prior information. The metric helps to better define the use cases fulfilling aerial imaging requirements.
FIRST APPROACH TO UAV-BASED CONTACT INSPECTION: A SMART PAYLOAD FOR NAVIGATION IN THE NEIGHBOURHOOD OF STRUCTURES
Authors: González-de Santos L. M. , Martínez-Sánchez J. , González-Jorge H. , Novo A. , Arias P.
Published: June 2019

Abstract. Many inspection tasks of structures are already carried out by unmanned aerial vehicles (UAV). Most of these inspections consist of using payloads for close range remote sensing purposes (i.e. digital cameras, thermal or LiDAR sensors). In all these inspection tasks the UAV system does not need to be close to the structure and typically the GPS coverage is good to perform mission navigation. In this paper, a smart payload developed for navigation in the neighbourhood of structures is presented. With this payload the UAV system is able to control the distance to a structure and the angle formed by the UAV and the structure in the horizontal plane. This payload has been calibrated in order to determine the calibration curve and measure the accuracy of the payload. The system has been tested in an indoor environment (GPS-denied). Good position and angular results has been obtained.