bluuebunny/crossref_metadata_2025 huggingface dataset:
Visual Detail Augmented Mapping for Small Aerial Target Detection
Authors: Li Jing , Dai Yanran , Li Congcong , Shu Junqi , Li Dongdong , Yang Tao , Lu Zhaoyang
Published: December 2018

Moving target detection plays a primary and pivotal role in avionics visual analysis, which aims to completely and accurately detect moving objects from complex backgrounds. However, due to the relatively small sizes of targets in aerial video, many deep networks that achieve success in normal size object detection are usually accompanied by a high rate of false alarms and missed detections. To address this problem, we propose a novel visual detail augmented mapping approach for small aerial target detection. Concretely, we first present a multi-cue foreground segmentation algorithm including motion and grayscale information to extract potential regions. Then, based on the visual detail augmented mapping approach, the regions that might contain moving targets are magnified to multi-resolution to obtain detailed target information and rearranged into new foreground space for visual enhancement. Thus, original small targets are mapped to a more efficient foreground augmented map which is favorable for accurate detection. Finally, driven by the success of deep detection network, small moving targets can be well detected from aerial video. Experiments extensively demonstrate that the proposed method achieves success in small aerial target detection without changing the structure of the deep network. In addition, compared with the-state-of-art object detection algorithms, it performs favorably with high efficiency and robustness.
An Improved Jitter Detection Method Based on Parallax Observation of Multispectral Sensors for Gaofen-1 02/03/04 Satellites
Authors: Zhu Ying , Wang Mi , Cheng Yufeng , He Luxiao , Xue Lin
Published: December 2018

Gaofen-1 02/03/04 satellites, the first civilian high resolution optical operational constellation in China, have Earth observation capabilities with panchromatic/multispectral imaging at 2/8 m resolution. Satellite jitter, the fluctuation of satellite points, has a negative influence on the geometric quality of high-resolution optical satellite imagery. This paper presents an improved jitter detection method based on parallax observation of multispectral sensors for Gaofen-1 02/03/04 satellites, which can eliminate the effect of the relative internal error induced by lens distortion, and accurately estimate the parameters of satellite jitter. The relative internal error is estimated by polynomial modelling and removed from the original parallax image generated by pixel-to-pixel image matching between two bands of images. The accurate relative time-varying error and absolute distortion caused by satellite jitter could be estimated by using the sine function. Three datasets of multispectral images captured by Gaofen-1 02/03/04 satellites were used to conduct the experiments. The results show that the relative system errors in both the across- and along-track directions can be modelled with a quadratic polynomial, and satellite jitter with a frequency of 1.1–1.2 Hz in the across-track direction was detected for the first time. The amplitude of the jitter differed in the three datasets. The largest amplitude, from satellite 04, is 1.3 pixels. The smallest amplitude, from satellite 02, is 0.077 pixels. The reliability and accuracy of the detection results were verified by using two groups of band combinations and ortho-images with a 1 m resolution. The comparison results show that the detection accuracy is improved by approximately 30% using the proposed method.
GPS Multipath Analysis Using Fresnel Zones
Authors: Zimmermann Florian , Schmitz Berit , Klingbeil Lasse , Kuhlmann Heiner
Published: December 2018

GNSS (Global Navigation Satellite Systems) multipath has been subject to scientific research for decades and although numerous methods and techniques have already been developed to mitigate this effect, it is still one of the accuracy-limiting factors in many GNSS applications. Since multipath is highly dependent on the individual antenna environment, there is still a need for new methods and further investigations to increase the understanding of this systematic effect. In this paper, the concept of Fresnel zones is applied to two different aspects of multipath. First, Fresnel zones are determined for the line-of-sight transmission between satellite and receiver. By comparing the boundary of the Fresnel zones to an obstruction adaptive elevation mask, potentially diffracted signals can be identified and excluded from the position estimation process. Both the percentage of epochs with fixed ambiguities and the positioning accuracy can be increased by the proposed method. Second, Fresnel zones are used to analyze the multipath induced by a horizontal and spatially-limited reflector. The comparison of simulated and real signal-to-noise (SNR) observations reveals a relationship between the percentage of the overlap of the Fresnel zone and reflector and the occurrence of multipath. It is found that an overlap of 50% is sufficient to induce multipath effects. This is of special interest, since this does not confirm theoretical assumptions of the multipath theory.
Adaptive Multiclass Mahalanobis Taguchi System for Bearing Fault Diagnosis under Variable Conditions
Authors: Wang Ning , Wang Zhipeng , Jia Limin , Qin Yong , Chen Xinan , Zuo Yakun
Published: December 2018

Bearings are vital components in industrial machines. Diagnosing the fault of rolling element bearings and ensuring normal operation is essential. However, the faults of rolling element bearings under variable conditions and the adaptive feature selection has rarely been discussed until now. Thus, it is essential to develop a practicable method to put forward the disposal of the fault under variable conditions. Considering these issues, this paper uses the method based on the Mahalanobis Taguchi System (MTS), and overcomes two shortcomings of MTS: (1) MTS is an effective tool to classify faults and has strong robustness to operating conditions, but it can only handle binary classification problems, and this paper constructs the multiclass measurement scale to deal with multi-classification problems. (2) MTS can determine important features, but uses the hard threshold to select the features, and this paper selects the proper feature sequence instead of the threshold to overcome the lesser adaptivity of the threshold configuration for signal-to-noise gain. Hence, this method proposes a novel method named adaptive Multiclass Mahalanobis Taguchi system (aMMTS), in conjunction with variational mode decomposition (VMD) and singular value decomposition (SVD), and is employed to diagnose the faults under the variable conditions. Finally, this method is verified by using the signal data collected from Case Western Reserve University Bearing Data Center. The result shows that it is accurate for bearings fault diagnosis under variable conditions.
An Efficient Incremental Mining Algorithm for Discovering Sequential Pattern in Wireless Sensor Network Environments
Authors: Lyu Xin , Ma Hongxu
Published: December 2018

Wireless sensor networks (WSNs) are an important type of network for sensing the environment and collecting information. It can be deployed in almost every type of environment in the real world, providing a reliable and low-cost solution for management. Huge amounts of data are produced from WSNs all the time, and it is significant to process and analyze data effectively to support intelligent decision and management. However, the new characteristics of sensor data, such as rapid growth and frequent updates, bring new challenges to the mining algorithms, especially given the time constraints for intelligent decision-making. In this work, an efficient incremental mining algorithm for discovering sequential pattern (novel incremental algorithm, NIA) is proposed, in order to enhance the efficiency of the whole mining process. First, a reasoned proof is given to demonstrate how to update the frequent sequences incrementally, and the mining space is greatly narrowed based on the proof. Second, an improvement is made on PrefixSpan, which is a classic sequential pattern mining algorithm with a high-complexity recursive process. The improved algorithm, named PrefixSpan+, utilizes a mapping structure to extend the prefixes to sequential patterns, making the mining step more efficient. Third, a fast support number-counting algorithm is presented to choose frequent sequences from the potential frequent sequences. A reticular tree is constructed to store all the potential frequent sequences according to subordinate relations between them, and then the support degree can be efficiently calculated without scanning the original database repeatedly. NIA is compared with various kinds of mining algorithms via intensive experiments on the real monitoring datasets, benchmarking datasets and synthetic datasets from aspects including time cost, sensitivity of factors, and space cost. The results show that NIA performs better than the existed methods.
Bearing-Only Obstacle Avoidance Based on Unknown Input Observer and Angle-Dependent Artificial Potential Field
Authors: Wang Xiaohua , Liang Yan , Liu Shun , Xu Linfeng
Published: December 2018

This paper presents the problem of obstacle avoidance with bearing-only measurements in the case that the obstacle motion is model-free, i.e., its acceleration is absolutely unknown, which cannot be dealt with by the mainstream Kalman-like schemes based on the known motion model. First, the essential reason of the collision caused by local minimum problem in the standard artificial potential field method is proved, and hence a revised method with angle dependent factor is proposed. Then, an unknown input observer is proposed to estimate the position and velocity of the obstacle. Finally, the numeric simulation demonstrates the effectiveness in terms of estimation accuracy and terminative time.
Identification of Wheat Yellow Rust Using Optimal Three-Band Spectral Indices in Different Growth Stages
Authors: Zheng Qiong , Huang Wenjiang , Cui Ximin , Dong Yingying , Shi Yue , Ma Huiqin , Liu Linyi
Published: December 2018

Yellow rust, a widely known destructive wheat disease, affects wheat quality and causes large economic losses in wheat production. Hyperspectral remote sensing has shown potential for the detection of plant disease. This study aimed to analyze the spectral reflectance of the wheat canopy in the range of 350–1000 nm and to develop optimal spectral indices to detect yellow rust disease in wheat at different growth stages. The sensitive wavebands of healthy and infected wheat were located in the range 460–720 nm in the early-mid growth stage (from booting to anthesis), and in the ranges 568–709 nm and 725–1000 nm in the mid-late growth stage (from filling to milky ripeness), respectively. All possible three-band combinations over these sensitive wavebands were calculated as the forms of PRI (Photochemical Reflectance Index) and ARI (Anthocyanin Reflectance Index) at different growth stages and assessed to determine whether they could be used for estimating the severity of yellow rust disease. The optimal spectral index for estimating wheat infected by yellow rust disease was PRI (570, 525, 705) during the early-mid growth stage with R2 of 0.669, and ARI (860, 790, 750) during the mid-late growth stage with R2 of 0.888. Comparison of the proposed spectral indices with previously reported vegetation indices were able to satisfactorily discriminate wheat yellow rust. The classification accuracy for PRI (570, 525, 705) was 80.6% and the kappa coefficient was 0.61 in early-mid growth stage, and the classification accuracy for ARI (860, 790, 750) was 91.9% and the kappa coefficient was 0.75 in mid-late growth stage. The classification accuracy of the two indices reached 84.1% and 93.2% in the early-mid and mid-late growth stages in the validated dataset, respectively. We conclude that the three-band spectral indices PRI (570, 525, 705) and ARI (860, 790, 750) are optimal for monitoring yellow rust infection in these two growth stages, respectively. Our method is expected to provide a technical basis for wheat disease detection and prevention in the early-mid growth stage, and the estimation of yield losses in the mid-late growth stage.
The Exponentiated Burr XII Power Series Distribution: Properties and Applications
Authors: Nasir Arslan , Yousof Haitham , Jamal Farrukh , Korkmaz Mustafa
Published: December 2018

In this work, we introduce a new Burr XII power series class of distributions, which is obtained by compounding exponentiated Burr XII and power series distributions and has a strong physical motivation. The new distribution contains several important lifetime models. We derive explicit expressions for the ordinary and incomplete moments and generating functions. We discuss the maximum likelihood estimation of the model parameters. The maximum likelihood estimation procedure is presented. We assess the performance of the maximum likelihood estimators in terms of biases, standard deviations, and mean square of errors by means of two simulation studies. The usefulness of the new model is illustrated by means of three real data sets. The new proposed models provide consistently better fits than other competitive models for these data sets.
Phytotoxicity of Corncob Biochar before and after Heat Treatment and Washing
Authors: Intani Kiatkamjon , Latif Sajid , Islam Md. Shafiqul , Müller Joachim
Published: December 2018

Biochar from crop residues such as corncobs can be used for soil amendment, but its negative effects have also been reported. This study aims to evaluate the phytotoxic effects of different biochar treatments and application rates on cress (Lepidium sativum). Corncob biochar was produced via slow pyrolysis without using purging gas. Biochar treatments included fresh biochar (FB), dried biochar (DB), washed biochar (WB), and biochar water extract (WE). Biochar application rates of 10, 20, and 30 t/ha were investigated. Significant phytotoxic effects of biochar were observed on germination rates, shoot length, fresh weight, and dry matter content, while severe toxic effects were identified in FB and WE treatments. Germination rate after 48 h (GR48) decreased with the increase of biochar application rates in all treatments. The observed order of performance of the biochar treatments for germination, shoot length, and shoot fresh weight for every biochar application rate was WB>DB>WE>FB, while it was the reverse order for the shoot dry matter content. WB treatment showed the best performance in reducing the phytotoxicity of biochar. The mitigation of the phytotoxicity in fresh corncob biochar by washing and heat treatment was found to be a simple and effective method.
Conserving Biocultural Diversity through Community–Government Interaction: A Practice-Based Approach in a Brazilian Extractive Reserve
Authors: Mooij Marjolein L.J. , Dessartre Mendonça Sabina , Arts Koen
Published: December 2018

We examined how community–government interaction may promote or hinder the conservation of biocultural diversity. Research was done with the extractive community of the Reserva Extrativista Riozinho da Liberdade, located in the state of Acre, Brazil. The reserve is governed by ICMBio, a Brazilian governmental organisation overseeing reserve policy implementation. This paper describes the interaction between ICMBio and the inhabitants of Riozinho da Liberdade. A Practice-Based Approach was used as a theoretical scope to look at the interaction on a practical level. It was found that ICMBio tried to develop the living standards of community members in various ways, for example, by offering suggestions for the improvement of livelihoods, and by proposing alternatives for consumptive behaviour. Although the relationship between ICMBio and the community was generally valued by community members, this did not always equal compliance with ICMBio’s rules, or responsiveness to ICBMIO’s suggestions for development. Our results show that although compliance was often suboptimal from a government perspective, biocultural diversity may still be reproduced through close interaction between community and government, and thus conserved. As such, our investigation provides counterweight to the abundant empirical evidence on the harmful social consequences of government interference in local nature governance. A main methodological insight of our work is that a Practice-Based Approach enabled us to detect (non-)compliant behaviour that would have otherwise likely gone unnoticed.
Robust Linear Programming and Its Application to Water and Environmental Decision-Making under Uncertainty
Authors: Zhou Yang , Yang Bo , Han Jingcheng , Huang Yuefei
Published: December 2018

In this study, we introduce a robust linear programming approach for water and environmental decision-making under uncertainty. This approach is of significant practical utility to decision makers for obtaining reliable and robust management decisions that are “immune” to the uncertainty attributable to data perturbations. The immunization guarantees that the chosen robust management plan will be implementable with no violation of the mandatory constraints of the problem being studied—i.e., natural resource supply constraint, environmental carrying capacity constraint, environmental pollution control constraint, etc.—and that the actual value of the objective will be no worse than the given estimation if the perturbations of data fall within the specified uncertainty set. A simplified example in regional water quality management is provided to help water and environmental practitioners to better understand how to implement robust linear programming from the perspective of application, as well as to illustrate the significance and necessity of implementing robust optimization techniques in real-world practices. Robust optimization is a growing research field that requires more interdisciplinary research efforts and engagements from water and environmental practitioners. Both may benefit from the advances of management science.
Sustainability Improvement in the Design of Lightweight Roofs: A New Prototype of Hybrid Steel and Wood Purlins
Authors: García Harkaitz , Zubizarreta Mikel , Cuadrado Jesús , Osa Juan Luis
Published: December 2018

A new structural typology of a hybrid purlin, made of type C cold steel and rectangular laminated wood (SWP), is presented in this paper. As a result, improvements on the most commonly used steel purlins are achieved, by substituting some of the steel sections for wooden sections. Although the wooden section is weaker and has a lower elastic modulus than the steel, the overall dimensions of the SWP are no larger than the type C steel purlin. In comparison with the steel ones, SWP purlins achieve a far better performance in terms of sustainability and are of lower weight, so less material will be needed for the main structure of the building. The behavior of each material in its position and the improvements in terms of sustainability and lower weight are analyzed as a function of span length, slope, and design load. To do so, the influence of both tensile stress and deformation design criteria in each section and the influence of those criteria on the choice of material and the lengths of each section are all examined. Finally, a design guide for the SWPs is presented that applies the proposed technical specifications.
Customer Complaints Analysis Using Text Mining and Outcome-Driven Innovation Method for Market-Oriented Product Development
Authors: Joung Junegak , Jung Kiwook , Ko Sanghyun , Kim Kwangsoo
Published: December 2018

The rapid increase in the quantity of customer data has promoted the necessity to analyse these data. Recent progress in text mining has enabled analysis of unstructured text data such as customer suggestions, customer complaints and customer feedback. Much research has been attempted to use insights gained from text mining to identify customer needs to guide development of market-oriented products. However, the previous research has a drawback that identifies limited customer needs based on product features. To overcome the limitation, this paper presents application of text mining analysis of customer complaints to identify customers’ true needs by using the Outcome-Driven Innovation (ODI) method. This paper provides a method to analyse customer complaints by using the concept of job. The ODI-based analysis contributes to identification of customer latent needs during the pre-execution and post-execution steps of product use by customers that previous methods cannot discover. To explain how the proposed method can identify customer requirements, we present a case study of stand-type air conditioners. The analysis identified two needs that experts had not identified but regarded as important. This research helps to identify requirements of all the points at which customers want to obtain help from the product.
Cradle-to-Site Carbon Emissions Assessment of Prefabricated Rebar Cages for High-Rise Buildings in China
Authors: Jiang Boya , Li Hongxian , Dong Ling , Wang Yu , Tao Yiqi
Published: December 2018

Construction industrialization is growing rapidly and has received significant attention worldwide in recent years. The industrialization of construction results in several benefits, including the promotion of sustainable construction and the development and application of prefabrication techniques. The Prefabricated Rebar Cage (PRC) is an emerging solution applied to high-rise buildings as a replacement of the In-situ Reinforcing Bar (ISRB) construction method. This paper investigates the cradle-to-site carbon emissions of PRC, and compares the results with those of conventional in-situ rebar construction methods for high-rise buildings. The cradle-to-site cycle is divided into three stages, namely, material preparation, transportation, and on-site construction. For the material preparation stage, it is found that CO2 emissions are increased by 3% when using PRC due to the operation of machinery during the prefabrication process. In the transportation stage, CO2 emissions are found to increase by 3.3 times for PRC, as there is more transportation required for PRCs than for conventional construction methods. During the on-site construction stage, the PRC method demonstrates its advantages by reducing CO2 emissions by 44.7%, which is attributed to decreased hoisting frequency and lower mechanical utilization for fewer joining activities. Overall, CO2 emissions can be reduced by 1.24% by adopting the PRC method for high-rise buildings, and it is therefore recommended to adopt PRCs for this purpose. This research studies carbon emissions of PRC and contributes to promoting the sustainable development of prefabricated building techniques.
Measuring Progress in Sustainable Food Cities: An Indicators Toolbox for Action
Authors: Moragues-Faus Ana , Marceau Alizée
Published: December 2018

Despite the growth of urban food policies across the globe, a key challenge remains around measuring the impact of these initiatives in building more sustainable and just cities. The literature identifies as the main barriers to progress food system assessments the lack of clear definitions of sustainability, insufficient data, the low applicability of global conceptualisations to local conditions and vice versa and low levels of actor involvement. We aim to address these gaps by co-developing a sustainability assessment framework to evaluate food systems performance in UK cities. The framework emerging from this collaborative process overcomes key limitations of previous exercises by providing a place-based and participative definition of sustainability aligned with global conceptualisations, building on the experiences and needs of a wide range of practitioners and taking a holistic but non-prescriptive approach to understanding food system outcomes. However, its application to the city of Cardiff reveals new challenges, mostly regarding the need to incorporate underrepresented stakeholders as well as account for multiscalar food system interdependencies and their positive but also negative impacts. Results show the need to embed critical perspectives in sustainable food assessments that actively expand their transformative capacity by developing further inclusive, participatory, place-based and whole-systems approaches.
Do Pre-service Teachers Dance with Wolves? Subject-Specific Teacher Professional Development in A Recent Biodiversity Conservation Issue
Authors: Büssing Alexander Georg , Schleper Maike , Menzel Susanne
Published: December 2018

Biodiversity conservation issues are adequate topics of Education for Sustainable Development (ESD), as they involve ecological, economic and social aspects. But teaching about these topics often challenges teachers due to high factual complexity but also because of additional affective dimensions. As a consequence, teacher professional development in ESD should address these affective components, to better qualify and motivate teachers to integrate conservation issues into their teaching. To investigate behaviourally relevant factors, we selected the context of natural remigration and conservation of the grey wolf (Canis lupus) in Germany and surveyed 120 pre-service biology teachers (M = 23.2 years, SD = 3.3 years) about contextual factors and their motivation to teach about the issue. Participants reported more positive attitudes, higher enjoyment and an increased perceived behavioural control towards teaching the issue in future teachers when they perceived a smaller psychological distance to the issue and an overall higher motivation to protect the species. As this motivation was grounded in more fundamental personality characteristics like wildlife values and attitudes towards wolves, we discuss the central role of these traits as a basis for transformative learning processes and the necessity of a holistic and subject-specific teacher professional development in ESD.
Modeling Spatial Patterns of Humus Forms in Montane and Subalpine Forests: Implications of Local Variability for Upscaling
Authors: Hellwig Niels , Tatti Dylan , Sartori Giacomo , Anschlag Kerstin , Graefe Ulfert , Egli Markus , Gobat Jean-Michel , Broll Gabriele
Published: December 2018

Humus forms are a distinctive morphological indicator of soil organic matter decomposition. The spatial distribution of humus forms depends on environmental factors such as topography, climate and vegetation. In montane and subalpine forests, environmental influences show a high spatial heterogeneity, which is reflected by a high spatial variability of humus forms. This study aims at examining spatial patterns of humus forms and their dependence on the spatial scale in a high mountain forest environment (Val di Sole/Val di Rabbi, Trentino, Italian Alps). On the basis of the distributions of environmental covariates across the study area, we described humus forms at the local scale (six sampling sites), slope scale (60 sampling sites) and landscape scale (30 additional sampling sites). The local variability of humus forms was analyzed with regard to the ground cover type. At the slope and landscape scale, spatial patterns of humus forms were modeled applying random forests and ordinary kriging of the model residuals. The results indicate that the occurrence of the humus form classes Mull, Mullmoder, Moder, Amphi and Eroded Moder generally depends on the topographical position. Local-scale patterns are mostly related to micro-topography (local accumulation and erosion sites) and ground cover, whereas slope-scale patterns are mainly connected with slope exposure and elevation. Patterns at the landscape scale show a rather irregular distribution, as spatial models at this scale do not account for local to slope-scale variations of humus forms. Moreover, models at the slope scale perform distinctly better than at the landscape scale. In conclusion, the results of this study highlight that landscape-scale predictions of humus forms should be accompanied by local- and slope-scale studies in order to enhance the general understanding of humus form patterns.
“BalSim”: A Carbon, Nitrogen and Greenhouse Gas Mass Balance Model for Pastures
Authors: Teixeira Ricardo F.M. , Barão Lúcia , Morais Tiago G. , Domingos Tiago
Published: December 2018

Animal production systems are increasingly required to co-produce meat products and other ecosystem services. Sown biodiverse pastures (SBP) were developed in Portugal as an improvement over semi-natural pastures (SNP). SBP increase yields and animal intake during grazing, are substantial carbon sinks, and the abundance of legumes in the mixtures provides plants with a biological source of nitrogen. However, the data available and the data demands of most models make integrated modelling of these effects difficult. Here, we developed “BalSim”, a mass balance approach for the estimation of carbon and nitrogen flows and the direct greenhouse gas (GHG) balance of the two production systems. Results show that, on average, the on-farm GHG balance is −2.6 and 0.8 t CO2e/ha.yr for SBP and SNP, respectively. Ignoring the effects of carbon sequestration, and taking into account only non-CO2 emissions, the systems are responsible for 17.0 and 16.3 kg CO2e/kg live weight.yr. The annual analysis showed that non-CO2 emissions were highest in a drought year due to decreased yield and stocking rate. We also showed through scenario analysis that matching the grazing level to the yield is crucial to minimize emissions and ensure reduced feed supplementation while maintaining high soil carbon stocks.
The Structure and Periodicity of the Chinese Air Passenger Network
Authors: Li Hongqi , Wang Haotian , Bai Ming , Duan Bin
Published: December 2018

China’s air transportation system is evolving with its own unique mechanism. In particular, the structural features of the Chinese air passenger network (CAPN) are of interest. This paper aims to analyze the CAPN from holistic and microcosmic perspectives. Considering that the topological structure and the capacity (i.e., available passenger-seats) flow are important to the air network’s performance, the CAPN structure features from non-weighted and weighted perspectives are analyzed. Subnets extracted by time-scale constraints of one day or every two-hours are used to find the temporal features. This paper provides some valuable conclusions about the structural characteristics and temporal features of the CAPN. The results indicate that the CAPN has a small-world and scale-free structure. The cumulative degree distribution of the CAPN follows a two-regime power-law distribution. The CAPN tends to be disassortative. Some important airports, including national air-hubs and local air-hubs, remarkably affect the CAPN. About 90% of large capacities exist between airports with large degrees. The properties of CAPN subnets extracted by taking two hours as the time-scale interval shed light on the air network performance and the changing rule more accurately and microcosmically. The method of the spectral destiny estimation is used to find the implicit periodicity mathematically. For most indicators, a one-day cycle, two-day cycle, and/or three-day cycle can be found.
A Framework for Automatic Building Detection from Low-Contrast Satellite Images
Authors: Aamir Muhammad , Pu Yi-Fei , Rahman Ziaur , Tahir Muhammad , Naeem Hamad , Dai Qiang
Published: December 2018

Building detection in satellite images has been considered an essential field of research in remote sensing and computer vision. There are currently numerous techniques and algorithms used to achieve building detection performance. Different algorithms have been proposed to extract building objects from high-resolution satellite images with standard contrast. However, building detection from low-contrast satellite images to predict symmetrical findings as of past studies using normal contrast images is considered a challenging task and may play an integral role in a wide range of applications. Having received significant attention in recent years, this manuscript proposes a methodology to detect buildings from low-contrast satellite images. In an effort to enhance visualization of satellite images, in this study, first, the contrast of an image is optimized to represent all the information using singular value decomposition (SVD) based on the discrete wavelet transform (DWT). Second, a line-segment detection scheme is applied to accurately detect building line segments. Third, the detected line segments are hierarchically grouped to recognize the relationship of identified line segments, and the complete contours of the building are attained to obtain candidate rectangular buildings. In this paper, the results from the method above are compared with existing approaches based on high-resolution images with reasonable contrast. The proposed method achieves high performance thus yields more diversified and insightful results over conventional techniques.
Methods for MADM with Picture Fuzzy Muirhead Mean Operators and Their Application for Evaluating the Financial Investment Risk
Authors: Wang Rui , Wang Jie , Gao Hui , Wei Guiwu
Published: December 2018

In this article, we study multiple attribute decision-making (MADM) problems with picture fuzzy numbers (PFNs) information. Afterwards, we adopt a Muirhead mean (MM) operator, a weighted MM (WMM) operator, a dual MM (DMM) operator, and a weighted DMM (WDMM) operator to define some picture fuzzy aggregation operators, including the picture fuzzy MM (PFMM) operator, the picture fuzzy WMM (PFWMM) operator, the picture fuzzy DMM (PFDMM) operator, and the picture fuzzy WDMM (PFWDMM) operator. Of course, the precious merits of these defined operators are investigated. Moreover, we have adopted the PFWMM and PFWDMM operators to build a decision-making model to handle picture fuzzy MADM problems. In the end, we take a concrete instance of appraising a financial investment risk to demonstrate our defined model and to verify its accuracy and scientific merit.
Multiple Parameters Beyond Lipid Binding Affinity Drive Cytotoxicity of Cholesterol-Dependent Cytolysins
Authors: Ray Sucharit , Thapa Roshan , Keyel Peter A.
Published: December 2018

The largest superfamily of bacterial virulence factors is pore-forming toxins (PFTs). PFTs are secreted by both pathogenic and non-pathogenic bacteria. PFTs sometimes kill or induce pro-pathogen signaling in mammalian cells, all primarily through plasma membrane perforation, though the parameters that determine these outcomes are unclear. Membrane binding, calcium influx, pore size, and membrane repair are factors that influence PFT cytotoxicity. To test the contribution of membrane binding to cytotoxicity and repair, we compared the closely related, similarly-sized PFTs Perfringolysin O (PFO) from Clostridium perfringens and Streptolysin O (SLO) from Streptococcus pyogenes. Cell death kinetics for PFO and SLO were different because PFO increased in cytotoxicity over time. We introduced known L3 loop mutations that swap binding affinity between toxins and measured hemolytic activity, nucleated cell death kinetics and membrane repair using viability assays, and live cell imaging. Altered hemolytic activity was directly proportional to toxin binding affinity. In contrast, L3 loop alterations reduced nucleated cell death, and they had limited effects on cytotoxicity kinetics and membrane repair. This suggests other toxin structural features, like oligomerization, drives these parameters. Overall, these findings suggest that repair mechanisms and toxin oligomerization add constraints beyond membrane binding on toxin evolution and activity against nucleated cells.
The 18th Rocky Mountain Virology Association Meeting
Authors: Rovnak Joel , Clair Laura A. St. , Krieger Kirsten , Lian Elena , Perera Rushika , Cohrs Randall J.
Published: December 2018

This autumn, approximately 100 scientists and students from the Rocky Mountain area along with invited speakers attended the 18th annual meeting of the Rocky Mountain Virology Association that was held at the Colorado State University Mountain Campus. The two-day gathering featured 31 talks and 33 posters all of which focused on specific areas of current virology and prion protein research. Since the keynote presentation focused on the oligoadenylate synthetase-ribonuclease L pathway the main area of focus was on host–virus interactions, however other areas of interest included virus vectors, current models of virus infections, prevention and treatment of virus infections, separate sessions on RNA viruses and prion proteins, and a special talk highlighting various attributes of targeted next-generation sequencing. The meeting was held at the peak of the fall Aspen colors surrounded by five mountains >11000 ft (3.3 km) where the secluded campus provided the ideal setting for extended discussions and outdoor exercise. On behalf of the Rocky Mountain Virology Association, this report summarizes 42 selected presentations.
Chickpea chlorotic dwarf virus: An Emerging Monopartite Dicot Infecting Mastrevirus
Authors: Kanakala Surapathrudu , Kuria Paul
Published: December 2018

Chickpea stunt disease (CSD), caused by Chickpea chlorotic dwarf virus (CpCDV) is a threat to chickpea production leading to yield losses of 75–95%. Chickpea chlorotic dwarf virus is a monopartite, single-stranded circular DNA virus in the genus Mastrevirus and family Geminiviridae. It is transmitted by Orosius albicinctus in a circulative (persistent) and nonpropagative manner. Symptoms of CSD include very small leaves, intense discoloration (yellowing (kabuli type) and reddening (desi type)), and bushy stunted appearance of the plant. Presently, CpCDVs occurs in Africa, Asia, Australia, and the Middle East, causing extensive losses on economically important crops in in the families Fabaceae, Asteraceae, Amaranthaceae, Brassicaceae, Cucurbitaceae, Caricaceae, Chenopodiaceae, Leguminosae, Malvaceae, Pedaliaceae, and Solanaceae. High frequency of recombinations has played a significant role in the wide host range, diversification, and rapid evolution of CpCDVs. This review highlights the extensive research on the CpCDV genome diversity, host range, plant–virus–insect interactions, and RNA interference-based resistance of CpCDV, providing new insights into the host adaptation and virus evolution.
Building an Intelligent Hydroinformatics Integration Platform for Regional Flood Inundation Warning Systems
Authors: Chang Li-Chiu , Chang Fi-John , Yang Shun-Nien , Kao I-Feng , Ku Ying-Yu , Kuo Chun-Ling , Amin Ir. Mohd Zaki bin Mat
Published: December 2018

Flood disasters have had a great impact on city development. Early flood warning systems (EFWS) are promising countermeasures against flood hazards and losses. Machine learning (ML) is the kernel for building a satisfactory EFWS. This paper first summarizes the ML methods proposed in this special issue for flood forecasts and their significant advantages. Then, it develops an intelligent hydroinformatics integration platform (IHIP) to derive a user-friendly web interface system through the state-of-the-art machine learning, visualization and system developing techniques for improving online forecast capability and flood risk management. The holistic framework of the IHIP includes five layers (data access, data integration, servicer, functional subsystem, and end-user application) and one database for effectively dealing with flood disasters. The IHIP provides real-time flood-related data, such as rainfall and multi-step-ahead regional flood inundation maps. The interface of Google Maps fused into the IHIP significantly removes the obstacles for users to access this system, helps communities in making better-informed decisions about the occurrence of floods, and alerts communities in advance. The IHIP has been implemented in the Tainan City of Taiwan as the study case. The modular design and adaptive structure of the IHIP could be applied with similar efforts to other cities of interest for assisting the authorities in flood risk management.
Drought Characteristics and Its Response to the Global Climate Variability in the Yangtze River Basin, China
Authors: Huang Tao , Xu Ligang , Fan Hongxiang
Published: December 2018

The frequent occurrence of drought events in humid and semi-humid regions is closely related to the global climate variability (GCV). In this study, the Standard Precipitation Evapotranspiration Index (SPEI) was taken as an index to investigate the drought in the Yangtze River Basin (YRB), a typical humid and semi-humid region in China. Furthermore, nine GCV indices, such as North Atlantic Oscillation (NAO) were taken to characterize the GCV. Correlation analysis and a joint probability distribution model were used to explore the relationship between the drought events and the GCV. The results demonstrated that there were six significant spatiotemporal modes revealed by SPEI3 (i.e., seasonal drought), which were consistent with the distribution of the main sub basins in the YRB, indicating a heterogeneity of drought regime. However, the SPEI12 (i.e., annual drought) can only reveal five modes. Precipitation Indices and El Niño/Southern Oscillation (ENSO) Indices were more closely related to the drought events. A causal relationship existed between ENSO precipitation index (ESPI), NAO, East Central Tropical Pacific Sea Surface Temperature (Nino3.4) and Northern Oscillation Index (NOI) and drought in the YRB, respectively. Drought events were most sensitive to the low NAO and high NOI events. This study shows a great significance for the understanding of spatiotemporal characteristics of meteorological drought and will provide a reference for the further formulation of water resources policy and the prevention of drought disasters.
Long-Term Management Policies of Reservoirs: Possible Re-Use of Dredged Sediments for Coastal Nourishment
Authors: De Vincenzo Annamaria , Covelli Carmine , Molino Antonio Jacopo , Pannone Marilena , Ciccaglione Margherita , Molino Bruno
Published: December 2018

This paper proposes a methodological approach to the re-use of reservoir sediments for coastal nourishment. The proposed approach represents a point of convergence between water and sediment management, coastal protection from erosion and the re-use of sediments dredged from reservoirs. In particular, this study indicates a general protocol of actions and a reference legislative scenario for the use of sediment from reservoirs for beach nourishment as an alternative to sediment from sea caves or land caves. Quantitative characterization of reservoir sediments and their qualitative characterization are the fundamental steps to define the compatibility between reservoir sediment and beach sand. The study was applied to a real case of Southern Italy known as the Guardialfiera Reservoir.
Effect of Particle Size and Shape on Separation in a Hydrocyclone
Authors: Tang Zhaojia , Yu Liming , Wang Fenghua , Li Na , Chang Liuhong , Cui Ningbo
Published: December 2018

Given the complex separation mechanisms of the particulate mixture in a hydrocyclone and the uncertain effects of particle size and shape on separation, this study explored the influence of the maximum projected area of particles on the separation effect as well as single and mixed separations based on CFD–DEM (Computational Fluid Dynamics and Discrete Element Method) coupling and experimental test methods. The results showed that spherical particles flowed out more easily from the downstream as their sizes increased. Furthermore, with the enlargement of maximum projected area, the running space of the particles with the same volume got closer to the upward flow and particles tended to be separated from the upstream. The axial velocity of the combined separation of 60 µm particles and 120 µm particles increased by 25.74% compared with that of single separation of 60 µm particles near the transition section from a cylinder to a cone. The concentration of 60 µm particles near the running space of 120 µm particles increased by 20.73% and those separated from the downstream increased by 4.1%. This study showed the influence of particle size and maximum projected area on the separation effect and the separation mechanism of mixed sand particles in a hydrocyclone, thereby providing a theoretical basis for later studies on the effect of particle size and shape on sedimentation under the cyclone action in a hydrocyclone.
Evaluating Factors for Controlling Sediment Connectivity of Landslide Materials: A Flume Experiment
Authors: Kharismalatri Hefryan Sukma , Ishikawa Yoshiharu , Gomi Takashi , Sidle Roy C. , Shiraki Katsushige
Published: December 2018

Connectivity of landslide sediment to and within fluvial systems is a key factor affecting the extent of mobilization of hillslope material. In particular, the formation of landslide dams and the transformation into landslide-induced debris flows represent “end members” of landslide sediment mobility. To quantify sediment connectivity, we developed a two-segment flume representing tributary inflow and the main channel. Mobility of sediment was examined by combinations of various topographic factors, such as tributary inflow angle (0 to 90° in 30° increments) and main channel gradient (10° and 15°), as well as water content of sediment (0 to 100% in 20% increments). We also examined differences of mobility among sediments derived from various lithologies (sand and shale, pyroclastic sediment, weathered granite, and weathered sedimentary rock). Mobility of sediment differed, depending on the water content of sediment, particularly less than saturation or greater than saturation. When all types of unsaturated landslide sediments entered the channel at inflow angles of 60° and 90°, substantial deposition occurred, suggesting the formation of landslide dams. At low inflow angles (0° and 30°) in a steep channel (15°), >50% of landslide sediment was transported downstream, indicating the occurrence of a debris flow. The amount of sediment deposited at the junction angle was greater for pyroclastic sediment followed by weathered granite, weathered sedimentary rock, and finally, sand and shale. Our connectivity index suggests that a threshold exists between landslide dam formation and debris flow occurrence associated with topographic conditions, water content, and types of sediment.
The AquaNES Project: Coupling Riverbank Filtration and Ultrafiltration in Drinking Water Treatment
Authors: Haas Robert , Opitz Ruediger , Grischek Thomas , Otter Philipp
Published: December 2018

Natural water treatment techniques combined with engineered solutions were investigated at demonstration sites in Europe within the AquaNES project. Ultrafiltration is well-established in water treatment, but is not feasible for many water utilities due to its high operational costs compared to conventional treatment. These differences in cost are caused by membrane fouling and the associated cleaning required. This study aims to assess the economic and energetic operation factors based on studies of an out/in ultrafiltration treatment plant for river water and bank filtrate. The fouling potential of both raw water sources was investigated as well as the quality of the resulting water. In addition, the results show the potential utility of a combined approach utilizing bank filtration followed by ultrafiltration in drinking water treatment. In a separate consideration of the treatment process, the water quality does not fulfill the requirements of the German drinking water ordinance. A new method for the removal of dissolved manganese from the bank filtrate is presented by inline electrolysis. While this improves water quality, this also has a significant influence on fouling potential and, thus, on operating costs of ultrafiltration. These aspects lead to a fundamental decision for operators to choose between more costly ultrafiltration with enhanced microbiological safety compared to cost-effective but less stringent drinking water treatment via open filtration.