bluuebunny/crossref_metadata_2025 huggingface dataset:
Sustainable Reactive Polyurethane Hot Melt Adhesives Based on Vegetable Polyols for Footwear Industry
Authors: Blasco Maria Pilar Carbonell , Limiñana María Ángeles Pérez , Silvestre Carlos Ruzafa , Calpena Elena Orgilés , Aís Francisca Arán
Published: January 2022

The aim of this work is to develop sustainable reactive polyurethane hot melt adhesives (HMPUR) for footwear applications based on biobased polyols as renewable resources, where ma-croglycol mixtures of polyadipate of 1,4-butanediol, polypropylene and different biobased polyols were employed and further reacted with 4-4′-diphenylmethane diisocyanate. The different reactive polyurethane hot melt adhesives obtained were characterized with different experimental techniques, such as Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), softening temperature and melting viscosity. Finally, their adhesion properties were measured from T-peel tests on leather/HMPUR adhesives/SBR rubber joints in order to establish the viability of the used biobased polyols and the amount of these polyols that could be added to reactive polyurethane hot melt adhesives satisfactorily to meet the quality requirements of footwear joints. All biobased polyols and percentages added to the polyurethane adhesive formulations successfully met the quality requirements of footwear, being comparable to traditional adhesives currently used in footwear joints in terms of final strength. Therefore, these new sustainable polyurethane adhesives can be considered as suitable and sustainable alternatives to the adhesives commonly used in footwear joints.
Evaluation of the Effect of Granite Waste Powder by Varying the Molarity of Activator on the Mechanical Properties of Ground Granulated Blast-Furnace Slag-Based Geopolymer Concrete
Authors: Shilar Fatheali A. , Ganachari Sharanabasava V. , Patil Veerabhadragouda B. , Nisar Kottakkaran Sooppy , Abdel-Aty Abdel-Haleem , Yahia I. S.
Published: January 2022

Industrial waste such as Ground Granulated Blast-Furnace Slag (GGBS) and Granite Waste Powder (GWP) is available in huge quantities in several states of India. These ingredients have no recognized application and are usually shed in landfills. This process and these materials are sources of severe environmental pollution. This industrial waste has been utilized as a binder for geopolymers, which is our primary focus. This paper presents the investigation of the optimum percentage of granite waste powder as a binder, specifically, the effect of molar and alkaline to binder (A/B) ratio on the mechanical properties of geopolymer concrete (GPC). Additionally, this study involves the use of admixture SP-340 for better performance of workability. Current work focuses on investigating the effect of a change in molarity that results in strength development in geopolymer concrete. The limits for the present work were: GGBS partially replaced by GWP up to 30%; molar ranging from 12 to 18 with the interval of 2 M; and A/B ratio of 0.30. For 16 M of GPC, a maximum slump was observed for GWP with 60 mm compared to other molar concentration. For 16 M of GPC, a maximum compressive strength (CS) was observed for GWP with 20%, of 33.95 MPa. For 16 M of GPC, a maximum STS was observed for GWP, with 20%, of 3.15 MPa. For 16 M of GPC, a maximum FS was observed for GWP, with 20%, of 4.79 MPa. Geopolymer concrete has better strength properties than conventional concrete. GPC is $13.70 costlier than conventional concrete per cubic meter.
Anisotropic Composition and Mechanical Behavior of a Natural Thin-Walled Composite: Eagle Feather Shaft
Authors: Cai Siyu , Han Baoshuai , Xu Yanjin , Guo Enyu , Sun Bin , Zeng Yuansong , Hou Hongliang , Wu Sujun
Published: January 2022

Flight feather shafts are outstanding bioinspiration templates due to their unique light weight and their stiff and strong characteristics. As a thin wall of a natural composite beam, the keratinous cortex has evolved anisotropic features to support flight. Here, the anisotropic keratin composition, tensile response, dynamic properties of the cortex, and fracture behaviors of the shafts are clarified. The analysis of Fourier transform infrared (FTIR) spectra indicates that the protein composition of calamus cortex is almost homogeneous. In the middle and distal shafts (rachis), the content of the hydrogen bonds (HBs) and side-chain is the highest within the dorsal cortex and is consistently lower within the lateral wall. The tensile responses, including the properties and dominant damage pattern, are correlated with keratin composition and fiber orientation in the cortex. As for dynamic properties, the storage modulus and damping of the cortex are also anisotropic, corresponding to variation in protein composition and fibrous structure. The fracture behaviors of bent shafts include matrix breakage, fiber dissociation and fiber rupture on compressive dorsal cortex. To clarify, ‘real-time’ damage behaviors, and an integrated analysis between AE signals and fracture morphologies, are performed, indicating that calamus failure results from a straight buckling crack and final fiber rupture. Moreover, in the dorsal and lateral walls of rachis, the matrix breakage initially occurs, and then the propagation of the crack is restrained by ‘ligament-like’ fiber bundles and cross fiber, respectively. Subsequently, the further matrix breakage, interface dissociation and induced fiber rupture in the dorsal cortex result in the final failure.
Lignin Distribution on Cell Wall Micro-Morphological Regions of Fibre in Developmental Phyllostachys pubescens Culms
Authors: Liu Bo , Tang Lina , Chen Qian , Zhu Liming , Zou Xianwu , Li Botao , Zhou Qin , Fu Yuejin , Lu Yun
Published: January 2022

Bamboo is a natural fibre reinforced composite with excellent performance which is, to a certain extent, an alternative to the shortage of wood resources. The heterogeneous distribution and molecular structure of lignin is one of the factors that determines its performance, and it is the key and most difficult component in the basic research into the chemistry of bamboo and in bamboo processing and utilization. In this study, the distribution of lignin components and lignin content in micro-morphological regions were measured in semi-quantitative level by age and radial location by means of visible-light microspectrophotometry (VLMS) coupled with the Wiesner and Maule reaction. There as guaiacyl lignin and syringyl lignin in the cell wall of the fibre. Lignin content of the secondary cell wall and cell corner increased at about 10 days, reached a maximum at 1 year, and then decreased gradually. From 17 days to 4 years, the lignin content of the secondary cell wall in the outer part of bamboo is higher than that in the middle part (which is, in turn, higher than that in the inner part of the bamboo). VLSM results of the micro-morphological regions showed that bamboo lignification developed by aging. Guaiacyl and syringl lignin units can be found in the cell wall of the fibre, parenchyma, and vessel. There was a difference in lignin content among different ages, different radial location, and different micro-morphological regions of the cell wall. The fibre walls were rich in guaiacyl lignin in the early stage of lignification and rich in syringyl units in the later stage of lignification. The guaiacyl and syringyl lignin deposition of bamboo green was earlier than that of the middle part of bamboo culm, and that of the middle part of bamboo culm was earlier than that of bamboo yellow. The single molecule lignin content of the thin layer is higher than that of thick layers, while the primary wall is higher than the secondary cell wall, showing that lignin deposition is consistent with the rules of cell wall formation. The obtained cytological information is helpful to understand the origin of the anisotropic, physical, mechanical, chemical, and machining properties of bamboo.
Effect of Graphene Addition on Polycaprolactone Scaffolds Fabricated Using Melt-Electrowriting
Authors: Chung Johnson H. Y. , Sayyar Sepidar , Wallace Gordon G.
Published: January 2022

Melt-electrowriting (MEW) is an emerging method that combines electrospinning and extrusion printing, allowing the fabrication of micron-scale structures suitable for tissue engineering. Compared to other additive fabrication methods, melt-electro written structures can offer more appropriate substrates for cell culture due to filament size and mechanical characteristics of the fabricated scaffolds. In this study, polycaprolactone (PCL)/graphene composites were investigated for fabrication of micron-size scaffolds through MEW. It was demonstrated that the addition of graphene can considerably improve the processability of PCL to fabricate micron-scale scaffolds with enhanced resolution. The tensile strength of the scaffold prepared from PCL/graphene composite (with only 0.5 wt.% graphene) was proved significantly (by more than 270%), better than that of the pristine PCL scaffold. Furthermore, graphene was demonstrated to be a suitable material for tailoring the degradation process to avoid undesirable bulk degradation, rapid mass loss and damage to the internal matrix of the polymer. The findings of this study offer a promising route for the fabrication of high-resolution scaffolds with micron-scale resolution for tissue engineering.
Blending the Subjective and Objective Realms of Sacred Architecture at the Pantheon: Creating a Comparative Framework for Evaluating Transformative Experiences in Ritual Contexts
Authors: Ro Brandon Richard
Published: January 2022

This paper seeks to create a comparative framework for evaluating transformative experiences for different types of ritual contexts found in sacred architecture by bridging the gap between the phenomenology of human experience and architecture’s built conditions. The methodology creates a framework for statistical analysis, whereby evidence of people’s actual (i.e., real, lived) “subjective” experiences can be evaluated against the “objective” architectural conditions. The comparative framework is put to the test by comparing the experiential and environmental conditions found at the Pantheon in Rome. Experiential data for the Pantheon is extracted from Julio Bermudez’s large survey database (N = 2872) of “extraordinary architectural experiences” for this study. This data is compared against “objective” graphical architecture analysis using Lindsay Jones’ “morphology of ritual-architectural priorities” with a specific focus on ritual contexts. The quantitative and qualitative data reveals that the Pantheon produces transformative experiences for visitors that are related to the expected outcomes of specific design features. The percentages from the “objective” and “subjective” analysis both rank the priorities of theatre, contemplation, and sanctuary in the same order. This study concludes that built environments possessing a higher presence and quality of “ritual-architectural priorities” are more likely to be perceived as sacred and produce transformative experiences.
From Old Habits to New Routines—A Case Study of Food Waste Generation and Reduction in Four Swedish Schools
Authors: Persson Osowski Christine , Osowski Dariusz , Johansson Kristina , Sundin Niina , Malefors Christopher , Eriksson Mattias
Published: January 2022

Public food service organizations are large producers of food waste, which leads to greenhouse gas emissions and the waste of natural resources. The aim of the present article was to gain insight into reasons for food waste and possible solutions for lowering food waste in schools in Sweden. In order to do so, food waste quantification in school canteens in two Swedish municipalities and nine qualitative interviews with key actors were conducted. Both municipalities displayed a high degree of variation in food waste, but the common pattern was that serving waste constituted the largest fraction of food waste, followed by plate waste and storage waste, as well as a gradual decrease in food waste over time. Food waste was mainly a result of old, disadvantageous habits, such as overproduction due to forecasting difficulties, whereas new, better routines such as serving fewer options, better planning, and a less stressful environment are the key to lowering food waste. Because food waste varies from one case to the next, it becomes important to identify and measure the causes of food waste in each school in order to be able to establish tailor-made, conscious, and flexible food waste mitigation routines.
Morphological and Physiological Screening to Predict Lettuce Biomass Production in Controlled Environment Agriculture
Authors: Kim Changhyeon , van Iersel Marc W.
Published: January 2022

Fast growth and rapid turnover is an important crop trait in controlled environment agriculture (CEA) due to its high cost. An ideal screening approach for fast-growing cultivars should detect desirable phenotypes non-invasively at an early growth stage, based on morphological and/or physiological traits. Hence, we established a rapid screening protocol based on a simple chlorophyll fluorescence imaging (CFI) technique to quantify the projected canopy size (PCS) of plants, combined with electron transport rate (ETR) measurements using a chlorophyll fluorometer. Eleven lettuce cultivars (Lactuca sativa), selected based on morphological differences, were grown in a greenhouse and imaged twice a week. Shoot dry weight (DW) of green cultivars at harvest 51 days after germination (DAG) was correlated with PCS at 13 DAG (R2 = 0.74), when the first true leaves had just appeared and the PCS was <8.5 cm2. However, early PCS of high anthocyanin (red) cultivars was not predictive of DW. Because light absorption by anthocyanins reduces the amount of photons available for photosynthesis, anthocyanins lower light use efficiency (LUE; DW/total incident light on canopy over the cropping cycle) and reduce growth. Additionally, the total incident light on the canopy throughout the cropping cycle explained 90% and 55% of variability in DW within green and red cultivars, respectively. Estimated leaf level ETR at a photosynthetic photon flux density (PPFD) of 200 or 1000 µmol m−2 s−1 were not correlated with DW in either green or red cultivars. In conclusion, early PCS quantification is a useful tool for the selection of fast-growing green lettuce phenotypes. However, this approach may not work in cultivars with high anthocyanin content because anthocyanins direct excitation energy away from photosynthesis and growth, weakening the correlation between incident light and growth.
Object-Based High-Rise Building Detection Using Morphological Building Index and Digital Map
Authors: Jung Sejung , Lee Kirim , Lee Won Hee
Published: January 2022

High-rise buildings (HRBs) as modern and visually unique land use continue to increase due to urbanization. Therefore, large-scale monitoring of HRB is very important for urban planning and environmental protection. This paper performed object-based HRB detection using high-resolution satellite image and digital map. Three study areas were acquired from KOMPSAT-3A, KOMPSAT-3, and WorldView-3, and object-based HRB detection was performed using the direction according to relief displacement by satellite image. Object-based multiresolution segmentation images were generated, focusing on HRB in each satellite image, and then combined with pixel-based building detection results obtained from MBI through majority voting to derive object-based building detection results. After that, to remove objects misdetected by HRB, the direction between HRB in the polygon layer of the digital map HRB and the HRB in the object-based building detection result was calculated. It was confirmed that the direction between the two calculated using the centroid coordinates of each building object converged with the azimuth angle of the satellite image, and results outside the error range were removed from the object-based HRB results. The HRBs in satellite images were defined as reference data, and the performance of the results obtained through the proposed method was analyzed. In addition, to evaluate the efficiency of the proposed technique, it was confirmed that the proposed method provides relatively good performance compared to the results of object-based HRB detection using shadows.
Combining Spectral and Texture Features of UAS-Based Multispectral Images for Maize Leaf Area Index Estimation
Authors: Zhang Xuewei , Zhang Kefei , Sun Yaqin , Zhao Yindi , Zhuang Huifu , Ban Wei , Chen Yu , Fu Erjiang , Chen Shuo , Liu Jinxiang , Hao Yumeng
Published: January 2022

The leaf area index (LAI) is of great significance for crop growth monitoring. Recently, unmanned aerial systems (UASs) have experienced rapid development and can provide critical data support for crop LAI monitoring. This study investigates the effects of combining spectral and texture features extracted from UAS multispectral imagery on maize LAI estimation. Multispectral images and in situ maize LAI were collected from test sites in Tongshan, Xuzhou, Jiangsu Province, China. The spectral and texture features of UAS multispectral remote sensing images are extracted using the vegetation indices (VIs) and the gray-level co-occurrence matrix (GLCM), respectively. Normalized texture indices (NDTIs), ratio texture indices (RTIs), and difference texture indices (DTIs) are calculated using two GLCM-based textures to express the influence of two different texture features on LAI monitoring at the same time. The remote sensing features are prescreened through correlation analysis. Different data dimensionality reduction or feature selection methods, including stepwise selection (ST), principal component analysis (PCA), and ST combined with PCA (ST_PCA), are coupled with support vector regression (SVR), random forest (RF), and multiple linear regression (MLR) to build the maize LAI estimation models. The results reveal that ST_PCA coupled with SVR has better performance, in terms of the VIs + DTIs (R2 = 0.876, RMSE = 0.239) and VIs + NDTIs (R2 = 0.877, RMSE = 0.236). This study introduces the potential of different texture indices for maize LAI monitoring and demonstrates the promising solution of using ST_PCA to realize the combining of spectral and texture features for improving the estimation accuracy of maize LAI.
A Combination of Spatial Domain Filters to Detect Surface Ocean Current from Multi-Sensor Remote Sensing Data
Authors: AS Mohammed Abdul Athick , Lee Shih-Yu
Published: January 2022

This research investigates the applicability of combining spatial filter’s algorithm to extract surface ocean current. Accordingly, the raster filters were tested on 80–13,505 daily images to detect Kuroshio Current (KC) on weekly, seasonal, and climatological scales. The selected raster filters are convolution, Laplacian, north gradient, sharpening, min/max, histogram equalization, standard deviation, and natural break. In addition, conventional data set of sea surface currents, sea surface temperature (SST), sea surface height (SSH), and non-conventional data such as total heat flux, surface density (SSD), and salinity (SSS) were employed. Moreover, controversial data on ocean color are included because very few studies revealed that chlorophyll-α is a proxy to SST in the summer to extract KC. Interestingly, the performance of filters is uniform and thriving for seasonal and on a climatological scale only by combining the algorithms. In contrast, the typical scenario of identifying Kuroshio signatures using an individual filter and by designating a value spectrum is inapplicable for specific seasons and data set. Furthermore, the KC’s centerlines computed from SST, SSH, total heat flux, SSS, SSD, and chlorophyll-α correlate with sea surface currents. Deviations are observed in the various segments of Kuroshio’s centerline extracted from heat flux, chlorophyll-α, and SSS flowing across Tokara Strait from northeast Taiwan to the south of Japan.
Assessment of Aquatic Reed Stands from Airborne Photogrammetric 3K Data
Authors: Baier Simon , Corti Meneses Nicolás , Geist Juergen , Schneider Thomas
Published: January 2022

Aquatic reed beds provide important ecological functions, yet their monitoring by remote sensing methods remains challenging. In this study, we propose an approach of assessing aquatic reed stand status indicators based on data from the airborne photogrammetric 3K-system of the German Aerospace Center (DLR). By a Structure from Motion (SfM) approach, we computed stand surface models of aquatic reeds for each of the 14 areas of interest (AOI) investigated at Lake Chiemsee in Bavaria, Germany. Based on reed heights, we subsequently calculated the reed area, surface structure homogeneity and shape of the frontline. For verification, we compared 3K aquatic reed heights against reed stem metrics obtained from ground-based infield data collected at each AOI. The root mean square error (RMSE) for 1358 reference points from the 3K digital surface model and the field-measured data ranged between 39 cm and 104 cm depending on the AOI. Considering strong object movements due to wind and waves, superimposed by water surface effects such as sun glint altering 3K data, the results of the aquatic reed surface reconstruction were promising. Combining the parameter height, area, density and frontline shape, we finally calculated an indicator for status determination: the aquatic reed status index (aRSI), which is based on metrics, and thus is repeatable and transferable in space and time. The findings of our study illustrate that, even under the adverse conditions given by the environment of the aquatic reed, aerial photogrammetry can deliver appropriate results for deriving objective and reconstructable parameters for aquatic reed status (Phragmites australis) assessment.
An Operational Analysis Ready Radar Backscatter Dataset for the African Continent
Authors: Yuan Fang , Repse Marko , Leith Alex , Rosenqvist Ake , Milcinski Grega , Moghaddam Negin F. , Dhar Tishampati , Burton Chad , Hall Lisa , Jorand Cedric , Lewis Adam
Published: January 2022

Digital Earth Africa is now providing an operational Sentinel-1 normalized radar backscatter dataset for Africa. This is the first free and open continental scale analysis ready data of this kind that has been developed to be compliant with the CEOS Analysis Ready Data for Land (CARD4L) specification for normalized radar backscatter (NRB) products. Partnership with Sinergise, a European geospatial company and Earth observation data provider, has ensured this dataset is produced efficiently in the cloud infrastructure and can be sustained in the long term. The workflow applies radiometric terrain correction (RTC) to the Sentinel-1 ground range detected (GRD) product, using the Copernicus 30 m digital elevation model (DEM). The method is used to generate data for a range of sites around the world and has been validated as producing good results. This dataset over Africa is made available publicly as a AWS public dataset and can be accessed through the Digital Earth Africa platform and its Open Data Cube API. We expect this dataset to support a wide range of applications, including natural resource monitoring, agriculture, and land cover mapping across Africa.
Automatic Position Estimation Based on Lidar × Lidar Data for Autonomous Aerial Navigation in the Amazon Forest Region
Authors: Salles Roberto Neves , Campos Velho Haroldo Fraga de , Shiguemori Elcio Hideiti
Published: January 2022

In this paper we post-process and evaluate the position estimation of pairs of template windows and geo-referenced images generated from LiDAR cloud point data using the Normalized Cross-Correlation (NCC) method. We created intensity, surface and terrain pairs of images for use with template matching, with 5 m pixel spacing, through binning. We evaluated square and circular binning approaches, without filtering the original data. Template matching achieved approximately 7 m root mean square error (RMSE) on intensity and surface templates on the respective geo-referenced images, while on terrain templates it had many mismatches due to insufficient terrain features over the assumed flight transect. Analysis of NCC showed the possibility of rejecting bad matches of intensity and surface templates, but terrain templates required an additional criteria of flatness for rejection. The combined NCC of intensity, surface and terrain proved stable for rejection of bad matches and had the lowest RMSE. Filtering outliers from surface images changed very little the accuracy of the matches, but greatly improved correlation values, indicating that the forest canopy might have the best features for geo-localization with template matching. Position estimation is essential for autonomous navigation of aerial vehicles and the these experiments with LiDAR data show potential for localization over densely forested regions where methods using optical camera data may fail to acquire distinguishable features.
A Quantifying Approach to Soil Salinity Based on a Radar Feature Space Model Using ALOS PALSAR-2 Data
Authors: Muhetaer Nuerbiye , Nurmemet Ilyas , Abulaiti Adilai , Xiao Sentian , Zhao Jing
Published: January 2022

In arid and semi-arid areas, timely and effective monitoring and mapping of salt-affected areas is essential to prevent land degradation and to achieve sustainable soil management. The main objective of this study is to make full use of synthetic aperture radar (SAR) polarization technology to improve soil salinity mapping in the Keriya Oasis, Xinjiang, China. In this study, 25 polarization features are extracted from ALOS PALSAR-2 images, of which four features are selected. In addition, three soil salinity inversion models, named the RSDI1, RSDI2, and RSDI3, are proposed. The analysis and comparison results of inversion accuracy show that the overall correlation values of the RSDI1, RSDI2, and RSDI3 models are 0.63, 0.61, and 0.62, respectively. This result indicates that the radar feature space models have the potential to extract information on soil salinization in the Keriya Oasis.
Linking the Spectra of Decomposing Litter to Ecosystem Processes: Tandem Close-Range Hyperspectral Imagery and Decomposition Metrics
Authors: Proctor Cameron , Pereira Cedelle , Jin Tian , Lim Gloria , He Yuhong
Published: January 2022

Efforts to monitor terrestrial decomposition dynamics at broad spatial scales are hampered by the lack of a cost-effective and scalable means to track the decomposition process. Recent advances in remote sensing have enabled the simulation of litter spectra throughout decomposition for grasses in general, yet unique decomposition pathways are hypothesized to create subtly different litter spectral signatures with unique ecosystem functional significance. The objectives of this study were to improve spectra–decomposition linkages and thereby enable the more comprehensive monitoring of ecosystem processes such as nutrient and carbon cycles. Using close-range hyperspectral imaging, litter spectra and multiple decomposition metrics were concurrently monitored in four classes of naturally decayed litter under four decomposition treatments. The first principal component accounted for approximately 94% of spectral variation in the close-range imagery and was attributed to the progression of decomposition. Decomposition-induced spectral changes were moderately correlated with the leaf carbon to nitrogen ratio (R2 = 0.52) and sodium hydroxide extractables (R2 = 0.45) but had no correlation with carbon dioxide flux. Temperature and humidity strongly influenced the decomposition process but did not influence spectral variability or the patterns of surface decomposition. The outcome of the study is that litter spectra are linked to important metrics of decomposition and thus remote sensing could be utilized to assess decomposition dynamics and the implications for nutrient recycling at broad spatial scales. A secondary study outcome is the need to resolve methodological challenges related to inducing unique decomposition pathways in a lab environment. Improving decomposition treatments that mimic real-world conditions of temperature, humidity, insolation, and the decomposer community will enable an improved understanding of the impacts of climatic change, which are expected to strongly affect microbially mediated decomposition.
Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part II: Results Using Optimal Error Statistics
Authors: Voshtani Sina , Ménard Richard , Walker Thomas W. , Hakami Amir
Published: January 2022

We applied the parametric variance Kalman filter (PvKF) data assimilation designed in Part I of this two-part paper to GOSAT methane observations with the hemispheric version of CMAQ to obtain the methane field (i.e., optimized analysis) with its error variance. Although the Kalman filter computes error covariances, the optimality depends on how these covariances reflect the true error statistics. To achieve more accurate representation, we optimize the global variance parameters, including correlation length scales and observation errors, based on a cross-validation cost function. The model and the initial error are then estimated according to the normalized variance matching diagnostic, also to maintain a stable analysis error variance over time. The assimilation results in April 2010 are validated against independent surface and aircraft observations. The statistics of the comparison of the model and analysis show a meaningful improvement against all four types of available observations. Having the advantage of continuous assimilation, we showed that the analysis also aims at pursuing the temporal variation of independent measurements, as opposed to the model. Finally, the performance of the PvKF assimilation in capturing the spatial structure of bias and uncertainty reduction across the Northern Hemisphere is examined, indicating the capability of analysis in addressing those biases originated, whether from inaccurate emissions or modelling error.
The Orientation of the Kofun Tombs
Authors: Baratta Norma Camilla , Magli Giulio , Picotti Arianna
Published: January 2022

The Kofun period of the history of Japan—between the 3rd and the 7th century AD—bears its name from the construction of huge, earth mound tombs called Kofun. Among them, the largest have a keyhole shape and are attributed to the first, semi-legendary emperors. The study of the orientation of ancient tombs is usually a powerful tool to better understand the cognitive aspects of religion and power in ancient societies. This study has never been carried out in Japan due to the very large number of Kofun and to the fact that access to the perimeter is usually forbidden. For these reasons, to investigate Kofun orientations, simple tools of satellite imagery are used here. Our results strongly point to a connection of all Kofun entrance corridors with the arc of the sky where the Sun and the Moon are visible every day of the year; additionally, these show an orientation of the keyhole Kofun to the arc of the rising/shining Sun, the goddess that the Japanese emperors put at the mythical origin of their dynasty.
Vibration Separation Methodology Compensated by Time-Varying Transfer Function for Fault Diagnosis of Non-Hunting Tooth Planetary Gearbox
Authors: Tong Shuiguang , Li Junjie , Cong Feiyun , Fu Zilong , Tong Zheming
Published: January 2022

Due to planetary movement of planet gears, the vibration signal perceived by a stationary sensor is modulated and difficult to diagnose. This paper proposed a vibration separation methodology compensated by a time-varying transfer function (TVTF-VS), which is a further development of the vibration separation (VS) method in the diagnosis of non-hunting tooth planetary gearboxes. On the basis of VS, multi-teeth VS is proposed to extract and synthesize the meshing signal of a planet gear using a single transducer. Considering the movement regularity of a planetary gearbox, the time-varying transfer function (TVTF) is represented by a generalized expression. The TVTF is constructed using a segment of healthy signal and an evaluation indicator is established to optimize the parameters of the TVTF. The constructed TVTF is applied to overcome the amplitude modulation effect and highlight fault characteristics. After that, experiments with baseline, pitting, and compound localized faults planet gears were conducted on a non-hunting tooth planetary gearbox test rig, respectively. The results demonstrate that incipient failure on a planet gear can be detected effectively, and relative location of the local faults can be determined accurately.
Providing Fault Detection from Sensor Data in Complex Machines That Build the Smart City
Authors: Gascón Alberto , Casas Roberto , Buldain David , Marco Álvaro
Published: January 2022

Household appliances, climate control machines, vehicles, elevators, cash counting machines, etc., are complex machines with key contributions to the smart city. Those devices have limited memory and processing power, but they are not just actuators; they embed tens of sensors and actuators managed by several microcontrollers and microprocessors communicated by control buses. On the other hand, predictive maintenance and the capability of identifying failures to avoid greater damage of machines is becoming a topic of great relevance in Industry 4.0, and the large amount of data to be processed is a concern. This article proposes a layered methodology to enable complex machines with automatic fault detection or predictive maintenance. It presents a layered structure to perform the collection, filtering and extraction of indicators, along with their processing. The aim is to reduce the amount of data to work with, and to optimize them by generating indicators that concentrate the information provided by data. To test its applicability, a prototype of a cash counting machine has been used. With this prototype, different failure cases have been simulated by introducing defective elements. After the extraction of the indicators, using the Kullback–Liebler divergence, it has been possible to visualize the differences between the data associated with normal and failure operation. Subsequently, using a neural network, good results have been obtained, being able to correctly classify the failure in 90% of the cases. The result of this application demonstrates the proper functioning of the proposed approach in complex machines.
Design and Implementation of an Indoor Warning System with Physiological Signal Monitoring for People Isolated at Home
Authors: Hung Chi-Huang , Fanjiang Yong-Yi , Lee Yi-Shiune , Wu Yi-Chao
Published: January 2022

Due to the recent COVID-19 pandemic, many people have faced in-home isolation, as every suspected patient must stay at home. The behavior of such isolated people needs to be monitored to ensure that they are staying at home. Using a camera is a very practical method. However, smart bracelets are more convenient when personal privacy is a concern or when the blood oxygen value or heart rate must be monitored. In this study, a low-cost indoor positioning system that uses a Bluetooth beacon, a smart bracelet, and an embedded system is proposed. In addition to monitoring whether a person living alone is active in a specific environment and tracking the heart rate or blood oxygen value under particular conditions, this system can also send early warning signals to specific observation units or relatives through instant messaging software.
Reinforced Palmprint Reconstruction Attacks in Biometric Systems
Authors: Sun Yue , Leng Lu , Jin Zhe , Kim Byung-Gyu
Published: January 2022

Biometric signals can be acquired with different sensors and recognized in secure identity management systems. However, it is vulnerable to various attacks that compromise the security management in many applications, such as industrial IoT. In a real-world scenario, the target template stored in the database of a biometric system can possibly be leaked, and then used to reconstruct a fake image to fool the biometric system. As such, many reconstruction attacks have been proposed, yet unsatisfactory naturalness, poor visual quality or incompleteness remains as major limitations. Thus, two reinforced palmprint reconstruction attacks are proposed. Any palmprint image, which can be easily obtained, is used as the initial image, and the region of interest is iteratively modified with deep reinforcement strategies to reduce the matching distance. In the first attack, Modification Constraint within Neighborhood (MCwN) limits the modification extent and suppresses the reckless modification. In the second attack, Batch Member Selection (BMS) selects the significant pixels (SPs) to compose the batch, which are simultaneously modified to a slighter extent to reduce the matching number and the visual-quality degradation. The two reinforced attacks can satisfy all the requirements, which cannot be simultaneously satisfied by the existing attacks. The thorough experiments demonstrate that the two attacks have a highly successful attack rate for palmprint systems based on the most state-of-the-art coding-based methods.
Above-Ground Biomass Estimation in Oats Using UAV Remote Sensing and Machine Learning
Authors: Sharma Prakriti , Leigh Larry , Chang Jiyul , Maimaitijiang Maitiniyazi , Caffé Melanie
Published: January 2022

Current strategies for phenotyping above-ground biomass in field breeding nurseries demand significant investment in both time and labor. Unmanned aerial vehicles (UAV) can be used to derive vegetation indices (VIs) with high throughput and could provide an efficient way to predict forage yield with high accuracy. The main objective of the study is to investigate the potential of UAV-based multispectral data and machine learning approaches in the estimation of oat biomass. UAV equipped with a multispectral sensor was flown over three experimental oat fields in Volga, South Shore, and Beresford, South Dakota, USA, throughout the pre- and post-heading growth phases of oats in 2019. A variety of vegetation indices (VIs) derived from UAV-based multispectral imagery were employed to build oat biomass estimation models using four machine-learning algorithms: partial least squares (PLS), support vector machine (SVM), Artificial neural network (ANN), and random forest (RF). The results showed that several VIs derived from the UAV collected images were significantly positively correlated with dry biomass for Volga and Beresford (r = 0.2–0.65), however, in South Shore, VIs were either not significantly or weakly correlated with biomass. For Beresford, approximately 70% of the variance was explained by PLS, RF, and SVM validation models using data collected during the post-heading phase. Likewise for Volga, validation models had lower coefficient of determination (R2 = 0.20–0.25) and higher error (RMSE = 700–800 kg/ha) than training models (R2 = 0.50–0.60; RMSE = 500–690 kg/ha). In South Shore, validation models were only able to explain approx. 15–20% of the variation in biomass, which is possibly due to the insignificant correlation values between VIs and biomass. Overall, this study indicates that airborne remote sensing with machine learning has potential for above-ground biomass estimation in oat breeding nurseries. The main limitation was inconsistent accuracy in model prediction across locations. Multiple-year spectral data, along with the inclusion of textural features like crop surface model (CSM) derived height and volumetric indicators, should be considered in future studies while estimating biophysical parameters like biomass.
Analysis Method of Bending Effect on Transmission Characteristics of Ultra-Low-Profile Rectangular Microstrip Antenna
Authors: Zhang Jiaying , Huang Jin , Sun Peng , Meng Fanbo , Zhang Jie , Zhao Pengbing
Published: January 2022

With the advent of wearable communication devices, microstrip antennas have developed multiple applications due to their ultra-low-profile properties. Therefore, it is essential to analyze the problem of frequency shift and impedance mismatch when the antenna is bent. For the case of a rectangular patch antenna E-plane bent on the cylindrical surface, (1) this paper introduces the effective dielectric constant into the cavity model, which can accurately predict the resonance frequency of the antenna, and (2) according to the equivalent circuit model of the antenna resonance mode, the lumped element parameters are calculated based on the above effective dielectric constant, so that impedance characteristics and the S-parameter matching the port can be quickly constructed. From the perspective of circuit frequency characteristics, it explains the change in the transmission performance of the curved antenna. The experimental results show that the maximum difference between the experimental and theoretical calculation frequencies is less than 1%. These results verify the validity and applicability of the theory in the analysis of ultra-low-profile patch antennas and wearable electronic communication devices. It provides a theoretical basis for the fast impedance matching of patch antennas under different working conditions.
Assessing the Spectral Characteristics of Dye- and Pigment-Based Inkjet Prints by VNIR Hyperspectral Imaging
Authors: Krauz Lukáš , Páta Petr , Kaiser Jan
Published: January 2022

Fine art photography, paper documents, and other parts of printing that aim to keep value are searching for credible techniques and mediums suitable for long-term archiving purposes. In general, long-lasting pigment-based inks are used for archival print creation. However, they are very often replaced or forged by dye-based inks, with lower fade resistance and, therefore, lower archiving potential. Frequently, the difference between the dye- and pigment-based prints is hard to uncover. Finding a simple tool for countrified identification is, therefore, necessary. This paper assesses the spectral characteristics of dye- and pigment-based ink prints using visible near-infrared (VNIR) hyperspectral imaging. The main aim is to show the spectral differences between these ink prints using a hyperspectral camera and subsequent hyperspectral image processing. Two diverse printers were exploited for comparison, a hobby dye-based EPSON L1800 and a professional pigment-based EPSON SC-P9500. The identical prints created via these printers on three different types of photo paper were recaptured by the hyperspectral camera. The acquired pixel values were studied in terms of spectral characteristics and principal component analysis (PCA). In addition, the obtained spectral differences were quantified by the selected spectral metrics. The possible usage for print forgery detection via VNIR hyperspectral imaging is discussed in the results.
Hash-Chain Fog/Edge: A Mode-Based Hash-Chain for Secured Mutual Authentication Protocol Using Zero-Knowledge Proofs in Fog/Edge
Authors: Pardeshi Mayuresh , Sheu Ruey-Kai , Yuan Shyan-Ming
Published: January 2022

Authentication is essential for the prevention of various types of attacks in fog/edge computing. So, a novel mode-based hash chain for secure mutual authentication is necessary to address the Internet of Things (IoT) devices’ vulnerability, as there have been several years of growing concerns regarding their security. Therefore, a novel model is designed that is stronger and effective against any kind of unauthorized attack, as IoT devices’ vulnerability is on the rise due to the mass production of IoT devices (embedded processors, camera, sensors, etc.), which ignore the basic security requirements (passwords, secure communication), making them vulnerable and easily accessible. Furthermore, crackable passwords indicate that the security measures taken are insufficient. As per the recent studies, several applications regarding its requirements are the IoT distributed denial of service attack (IDDOS), micro-cloud, secure university, Secure Industry 4.0, secure government, secure country, etc. The problem statement is formulated as the “design and implementation of dynamically interconnecting fog servers and edge devices using the mode-based hash chain for secure mutual authentication protocol”, which is stated to be an NP-complete problem. The hash-chain fog/edge implementation using timestamps, mode-based hash chaining, the zero-knowledge proof property, a distributed database/blockchain, and cryptography techniques can be utilized to establish the connection of smart devices in large numbers securely. The hash-chain fog/edge uses blockchain for identity management only, which is used to store the public keys in distributed ledger form, and all these keys are immutable. In addition, it has no overhead and is highly secure as it performs fewer calculations and requires minimum infrastructure. So, we designed the hash-chain fog/edge (HCFE) protocol, which provides a novel mutual authentication scheme for effective session key agreement (using ZKP properties) with secure protocol communications. The experiment outcomes proved that the hash-chain fog/edge is more efficient at interconnecting various devices and competed favorably in the benchmark comparison.
TrackInk: An IoT-Enabled Real-Time Object Tracking System in Space
Authors: Aume Cameron , Andrews Keith , Pal Shantanu , James Alice , Seth Avishkar , Mukhopadhyay Subhas
Published: January 2022

Nowadays, there is tremendous growth in the Internet of Things (IoT) applications in our everyday lives. The proliferation of smart devices, sensors technology, and the Internet makes it possible to communicate between the digital and physical world seamlessly for distributed data collection, communication, and processing of several applications dynamically. However, it is a challenging task to monitor and track objects in real-time due to the distinct characteristics of the IoT system, e.g., scalability, mobility, and resource-limited nature of the devices. In this paper, we address the significant issue of IoT object tracking in real time. We propose a system called ‘TrackInk’ to demonstrate our idea. TrackInk will be capable of pointing toward and taking pictures of visible satellites in the night sky, including but not limited to the International Space Station (ISS) or the moon. Data will be collected from sensors to determine the system’s geographical location along with its 3D orientation, allowing for the system to be moved. Additionally, TrackInk will communicate with and send data to ThingSpeak for further cloud-based systems and data analysis. Our proposed system is lightweight, highly scalable, and performs efficiently in a resource-limited environment. We discuss a detailed system’s architecture and show the performance results using a real-world hardware-based experimental setup.
Nanomaterials for IoT Sensing Platforms and Point-of-Care Applications in South Korea
Authors: Choi Seung-Ho , Lee Joon-Seok , Choi Won-Jun , Seo Jae-Woo , Choi Seon-Jin
Published: January 2022

Herein, state-of-the-art research advances in South Korea regarding the development of chemical sensing materials and fully integrated Internet of Things (IoT) sensing platforms were comprehensively reviewed for verifying the applicability of such sensing systems in point-of-care testing (POCT). Various organic/inorganic nanomaterials were synthesized and characterized to understand their fundamental chemical sensing mechanisms upon exposure to target analytes. Moreover, the applicability of nanomaterials integrated with IoT-based signal transducers for the real-time and on-site analysis of chemical species was verified. In this review, we focused on the development of noble nanostructures and signal transduction techniques for use in IoT sensing platforms, and based on their applications, such systems were classified into gas sensors, ion sensors, and biosensors. A future perspective for the development of chemical sensors was discussed for application to next-generation POCT systems that facilitate rapid and multiplexed screening of various analytes.