bluuebunny/crossref_metadata_2025 huggingface dataset:
A Review of Polymer Composites Based on Carbon Fillers for Thermal Management Applications: Design, Preparation, and Properties
Authors: Kwon Yeon-Ju , Park Jung-Bin , Jeon Young-Pyo , Hong Jin-Yong , Park Ho-Seok , Lee Jea-Uk
Published: April 2021

With the development of microelectronic devices having miniaturized and integrated electronic components, an efficient thermal management system with lightweight materials, which have outstanding thermal conductivity and processability, is becoming increasingly important. Recently, the use of polymer-based thermal management systems has attracted much interest due to the intrinsic excellent properties of the polymer, such as the high flexibility, low cost, electrical insulation, and excellent processability. However, most polymers possess low thermal conductivity, which limits the thermal management applications of them. To address the low thermal conduction of the polymer materials, many kinds of thermally conductive fillers have been studied, and the carbon-based polymer composite is regarded as one of the most promising materials for the thermal management of the electric and electronic devices. In addition, the next generation electronic devices require composite materials with various additional functions such as flexibility, low density, electrical insulation, and oriented heat conduction, as well as ultrahigh thermal conductivity. In this review, we introduce the latest papers on thermally conductive polymer composites based on carbon fillers with sophisticated structures to meet the above requirements. The topic of this review paper consists of the following four contents. First, we introduce the design of a continuous three-dimensional network structure of carbon fillers to reduce the thermal resistance between the filler–matrix interface and individual filler particles. Second, we discuss various methods of suppressing the electrical conductivity of carbon fillers in order to manufacture the polymer composites that meet both the electrical insulation and thermal conductivity. Third, we describe a strategy for the vertical alignment of carbon fillers to improve the through-plane thermal conductivity of the polymer composite. Finally, we briefly mention the durability of the thermal conductivity performance of the carbon-based composites. This review presents key technologies for a thermal management system of next-generation electronic devices.
Nickel-Aluminum Thermal Spray Coatings as Adhesion Promoter and Susceptor for Inductively Joined Polymer-Metal Hybrids
Authors: Saborowski Erik , Dittes Axel , Lindner Thomas , Lampke Thomas
Published: April 2021

Hybrid joints of metal- and fiber-reinforced-polymer offer great potential for lightweight applications. Thereby, a fast and reliable joining process is mandatory for mass-production applications. To this end, this study assesses inductive spot-joining in combination with prior thermal spray coating of the metal adherent. A nickel–aluminum 95/5 coating was applied to achieve high adhesion through mechanical interlocking and to act as susceptor for the inductive joining process. The joint strength was assessed with lap shear specimens consisting of EN AW-6082 aluminum alloy and glass fiber reinforced polyamide 6 or polypropylene, respectively. The joints were further investigated in terms of heating time and hygrothermal cyclic loading. The results showed that significant time savings for the joining process as well as strong adhesion were achieved due to the coating. Moreover, the high strengths were even preserved under hygrothermal cyclic loading.
Universal Plasma Jet for Droplet Manipulation on a PDMS Surface towards Wall-Less Scaffolds
Authors: Peng Cheng-Yun , Tsai Chia-Hung Dylan
Published: April 2021

Droplet manipulation is important in the fields of engineering, biology, chemistry, and medicine. Many techniques, such as electrowetting and magnetic actuation, have been developed for droplet manipulation. However, the fabrication of the manipulation platform often takes a long time and requires well-trained skills. Here we proposed a novel method that can directly generate and manipulate droplets on a polymeric surface using a universal plasma jet. One of its greatest advantages is that the jet can tremendously reduce the time for the platform fabrication while it can still perform stable droplet manipulation with controllable droplet size and motion. There are two steps for the proposed method. First, the universal plasma jet is set in plasma mode for modifying the manipulation path for droplets. Second, the jet is switched to air-jet mode for droplet generation and manipulation. The jetted air separates and pushes droplets along the plasma-treated path for droplet generation and manipulation. According to the experimental results, the size of the droplet can be controlled by the treatment time in the first step, i.e., a shorter treatment time of plasma results in a smaller size of the droplet, and vice versa. The largest and the smallest sizes of the generated droplets in the results are about 6 µL and 0.1 µL, respectively. Infrared spectra of absorption on the PDMS surfaces with and without the plasma treatment are investigated by Fourier-transform infrared spectroscopy. Tests of generating and mixing two droplets on a PDMS surface are successfully achieved. The aging effect of plasma treatment for the proposed method is also discussed. The proposed method provides a simple, fast, and low-cost way to generate and manipulate droplets on a polymeric surface. The method is expected to be applied to droplet-based cell culture by manipulating droplets encapsulating living cells and towards wall-less scaffolds on a polymeric surface.
Synthesis and Characterization of Diosgenin Encapsulated Poly-ε-Caprolactone-Pluronic Nanoparticles and Its Effect on Brain Cancer Cells
Authors: Rabha Bijuli , Bharadwaj Kaushik Kumar , Baishya Debabrat , Sarkar Tanmay , Edinur Hisham Atan , Pati Siddhartha
Published: April 2021

Diosgenin encapsulated PCL-Pluronic nanoparticles (PCL-F68-D-NPs) were developed using the nanoprecipitation method to improve performance in brain cancer (glioblastoma) therapy. The nanoparticles were characterized by dynamic light scattering (DLS)/Zeta potential, Fourier-transform infrared (FTIR) spectra, X-ray diffraction (XRD), Field Emission Scanning Electron Microscopy (FESEM), and Transmission electron microscopy (TEM). The encapsulation efficiency, loading efficiency, and yield were calculated. The in vitro release rate was determined, and the kinetic model of diosgenin release was plotted and ascertained. The cytotoxicity was checked by MTT (3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyl tetrazolium bromide)assay against U87-MG cells (glioblastoma cell lines). The obtained nanoparticles demonstrated good size distribution, stability, morphology, chemical, and mechanical properties. The nanoparticles also possessed high encapsulation efficiency, loading efficiency, and yield. The release rate of Diosgenin was shown in a sustained manner. The in vitro cytotoxicity of PCL-F68-D-NPs showed higher toxicity against U87-MG cells than free Diosgenin.
Delamination and Manufacturing Defects in Natural Fiber-Reinforced Hybrid Composite: A Review
Authors: Suriani M. J. , Rapi Hannah Zalifah , Ilyas R. A. , Petrů Michal , Sapuan S. M.
Published: April 2021

In recent years, most boat fabrication companies use 100% synthetic fiber-reinforced composite materials, due to their high performance of mechanical properties. In the new trend of research on the fabrication of boat structure using natural fiber hybrid with kevlar/fiberglass-reinforced composite, the result of tensile, bending, and impact strength showed that glass fiber-reinforced polyester composite gave high strength with increasing glass fiber contents. At some point, realizing the cost of synthetic fiber is getting higher, researchers today have started to use natural fibers that are seen as a more cost-effective option. Natural fibers, however, have some disadvantages, such as high moisture absorption, due to repelling nature; low wettability; low thermal stability; and quality variation, which lead to the degradation of composite properties. In recent times, hybridization is recommended by most researchers as a solution to natural fiber’s weaknesses and to reduce the use of synthetic fibers that are not environmentally friendly. In addition, hybrid composite has its own special advantages, i.e., balanced strength and stiffness, reduced weight and cost, improved fatigue resistance and fracture toughness, and improved impact resistance. The synthetic–nature fiber hybrid composites are used in a variety of applications as a modern material that has attracted most manufacturing industries’ attention to shift to using the hybrid composite. Some of the previous studies stated that delamination and manufacturing had influenced the performance of the hybrid composites. In order to expand the use of natural fiber as a successful reinforcement in hybrid composite, the factor that affects the manufacturing defects needs to be investigated. In this review paper, a compilation of the reviews on the delamination and a few common manufacturing defect types illustrating the overview of the impact on the mechanical properties encountered by most of the composite manufacturing industries are presented.
Photocatalytic Activity and Filtration Performance of Hybrid TiO2-Cellulose Acetate Nanofibers for Air Filter Applications
Authors: Kwon Miyeon , Kim Juhea , Kim Juran
Published: April 2021

A facile method to prepare hybrid cellulose acetate nanofibers containing TiO2 (TiO2-CA nanofibers) by emulsion electrospinning technique was developed for the denitrification and filtration of particulate matters (PMs). This work found that hybrid TiO2-CA nanofibers mainly contain the anatase form of TiO2, contributing to the photodecomposition of NO gas under UV irradiation. The TiO2-CA nanofibers also showed an excellent filtration efficiency of 99.5% for PM0.5 and a photocatalytic efficiency of 78.6% for NO removal. Furthermore, the results implied that the morphology of the TiO2-CA nanofibers, such as micro-wrinkles and protrusions, increased the surface hydrophobicity up to 140°, with the increased addition of TiO2 nanoparticles. The proposed TiO2-CA nanofibers, as a result, would be promising materials for highly efficient and sustainable air filters for industrial and home appliance systems.
Recovery of Valuable Materials from the Waste Crystalline-Silicon Photovoltaic Cell and Ribbon
Authors: Chen Wei-Sheng , Chen Yen-Jung , Lee Cheng-Han , Cheng Yi-Jin , Chen Yu-An , Liu Fan-Wei , Wang Yi-Chung , Chueh Yu-Lun
Published: April 2021

With the dramatic increase of photovoltaic (PV) module installation in solar energy-based industries, the methods for recovering waste solar generators should be emphasized as the backup of the PV market for environmental protection. Crystalline-silicon accounts for most of the worldwide PV market and it contains valuable materials such as high purity of silicon (Si), silver (Ag), copper (Cu), tin (Sn), and lead (Pb). This study can provide an efficient recycling process for valuable materials resourced from waste crystalline-silicon PV module, including Si in the PV cell, and Ag, Cu, Pb, Sn, in PV ribbon. As tempered glass and Ethylene Vinyl Acetate (EVA) resin were removed, the module was separated into two materials, PV ribbon and PV cell. For PV cell purification, Si with purity at 99.84% was recovered by removing impurities such as aluminum (Al) and Ag by two-step leaching and dissolving the impurities. For PV ribbon recovering, purified metal or metal oxide was obtained through the processes of leaching/polishing, extraction, and chemical precipitation. In the polishing process, 99.5% of copper wire was collected. The purities of final products are 99.7% for CuO, 99.47% for PbO, 99.68% for SnO2, and 98.85% for Ag respectively.
A Molecular Dynamics Study of Heat Transfer Enhancement during Phase Change from a Nanoengineered Solid Surface
Authors: Morshed A. K. M. Monjur , Shahadat Muhammad Rubayat Bin , Roni Md. Rakibul Hasan , Masnoon Ahmed Shafkat , Shamim Saif Al-Afsan , Paul Titan C.
Published: April 2021

This study investigates the enhancement of the rate of evaporation from a nanoengineered solid surface using non-equilibrium molecular dynamics simulation. Four different types of surface modifications were introduced to examine the thermal transportation behavior. The surface modification includes: (1) transformation of surface wetting condition from hydrophobic to hydrophilic, (2) implementing nanostructures on the smooth surface, (3) cutting nano slots on the smooth surface and (4) introducing nano-level surface roughness. Evaporation behavior from the same effective surface area was also studied. The simulation domain consisted of three distinct zones: solid base wall made of copper, a few layers of liquid argon, and a vapor zone made of argon. All the nano-level surface modifications were introduced on the solid base surface. The few layers of liquid argon representing the liquid zone of the domain take heat from the solid surface and get evaporated. Outside this solid and liquid zone, there is argon vapor. The simulation began at the initial time t = 0 ns and then was allowed to reach equilibrium. Immediately after equilibrium was achieved on all three-phase systems, the temperature of the solid wall was raised to a higher value. In this way, thermal transportation from the solid wall to liquid argon was established. As the temperature of the solid wall was high enough, the liquid argon tended to evaporate. From the simulation results, it is observed that during the transformation from hydrophobic to hydrophilic conditions, enhancement of evaporation takes place due to the improvement of thermal transportation behavior. At the nanostructure surface, the active nucleation sites and effective surface area increase which results in evaporation enhancement. With nano slots and nano-level surface roughness, the rate of evaporation increases due to the increase of solid-liquid contact area and effective surface area.
The Surface Crack Extraction Method Based on Machine Learning of Image and Quantitative Feature Information Acquisition Method
Authors: Zhang Fan , Hu Zhenqi , Yang Kun , Fu Yaokun , Feng Zewei , Bai Mingbo
Published: April 2021

In order to effectively control the damage caused by surface cracks to a geological environment, we need to find a convenient, efficient, and accurate method to obtain crack information. The existing crack extraction methods based on unmanned air vehicle (UAV) images inevitably have some erroneous pixels because of the complexity of background information. At the same time, there are few researches on crack feature information. In view of this, this article proposes a surface crack extraction method based on machine learning of UAV images, the data preprocessing steps, and the content and calculation methods for crack feature information: length, width, direction, location, fractal dimension, number, crack rate, and dispersion rate. The results show that the method in this article can effectively avoid the interference by vegetation and soil crust. By introducing the concept of dispersion rate, the method combining crack rate and dispersion rate can describe the distribution characteristics of regional cracks more clearly. Compared to field survey data, the calculation result of the crack feature information in this article is close to the true value, which proves that this is a reliable method for obtaining quantitative crack feature information.
Coupling Analysis of Ecosystem Services Value and Economic Development in the Yangtze River Economic Belt: A Case Study in Hunan Province, China
Authors: Chen Wanxu , Zeng Jie , Zhong Mingxing , Pan Sipei
Published: April 2021

Sound ecosystems are a precondition for the sustainable survival and development of human society. However, ecological deterioration caused by socioeconomic activities can result in increasing pressure on ecosystems. Exploration of the spatial interaction between ecosystem and economic development under the background of high-quality and green development is, therefore, necessary. In this study, we analyzed the spatial interaction between the ecosystem services value (ESV) and economic development with the economic and ecological coupling index method based on high-resolution remote-sensing land-use data and socioeconomic statistical data in Hunan Province from 2000 to 2018. The results revealed that the ESV provided by the ecosystems in Hunan Province decreased by US$1256.166 million from 2000 to 2018. The areas with high ESV per unit area were distributed in the mountainous areas, while the areas with low ESV per unit area were distributed in the major cities and their surroundings. The bivariate spatial autocorrelation analysis showed that the ESV had significant spatial dependence on the economic development. In addition, the coupling analysis documented that the relationship between the ESV and economic density was mostly in the low conflict and potential crisis states. These results provide important guidance for the coordinated development of the regional economy and ecosystem conservation.
Toward More Integrated Utilizations of Geostationary Satellite Data for Disaster Management and Risk Mitigation
Authors: Higuchi Atsushi
Published: April 2021

Third-generation geostationary meteorological satellites (GEOs), such as Himawari-8/9 Advanced Himawari Imager (AHI), Geostationary Operational Environmental Satellites (GOES)-R Series Advanced Baseline Imager (ABI), and Meteosat Third Generation (MTG) Flexible Combined Imager (FCI), provide advanced imagery and atmospheric measurements of the Earth’s weather, oceans, and terrestrial environments at high-frequency intervals. Third-generation GEOs also significantly improve capabilities by increasing the number of observation bands suitable for environmental change detection. This review focuses on the significantly enhanced contribution of third-generation GEOs for disaster monitoring and risk mitigation, focusing on atmospheric and terrestrial environment monitoring. In addition, to demonstrate the collaboration between GEOs and Low Earth orbit satellites (LEOs) as supporting information for fine-spatial-resolution observations required in the event of a disaster, the landfall of Typhoon No. 19 Hagibis in 2019, which caused tremendous damage to Japan, is used as a case study.
Interannual Variability of GPS Heights and Environmental Parameters over Europe and the Mediterranean Area
Authors: Elia Letizia , Zerbini Susanna , Raicich Fabio
Published: April 2021

Vertical deformations of the Earth’s surface result from a host of geophysical and geological processes. Identification and assessment of the induced signals is key to addressing outstanding scientific questions, such as those related to the role played by the changing climate on height variations. This study, focused on the European and Mediterranean area, analyzed the GPS height time series of 114 well-distributed stations with the aim of identifying spatially coherent signals likely related to variations of environmental parameters, such as atmospheric surface pressure (SP) and terrestrial water storage (TWS). Linear trends and seasonality were removed from all the time series before applying the principal component analysis (PCA) to identify the main patterns of the space/time interannual variability. Coherent height variations on timescales of about 5 and 10 years were identified by the first and second mode, respectively. They were explained by invoking loading of the crust. Single-value decomposition (SVD) was used to study the coupled interannual space/time variability between the variable pairs GPS height–SP and GPS height–TWS. A decadal timescale was identified that related height and TWS variations. Features common to the height series and to those of a few climate indices—namely, the Arctic Oscillation (AO), the North Atlantic Oscillation (NAO), the East Atlantic (EA), and the multivariate El Niño Southern Oscillation (ENSO) index (MEI)—were also investigated. We found significant correlations only with the MEI. The first height PCA mode of variability, showing a nearly 5-year fluctuation, was anticorrelated (−0.23) with MEI. The second mode, characterized by a decadal fluctuation, was well correlated (+0.58) with MEI; the spatial distribution of the correlation revealed, for Europe and the Mediterranean area, height decrease till 2015, followed by increase, while Scandinavian and Baltic countries showed the opposite behavior.
Making the Invisible Visible: Underwater Malta—A Virtual Museum for Submerged Cultural Heritage
Authors: Gambin Timmy , Hyttinen Kari , Sausmekat Maja , Wood John
Published: April 2021

The seabed can be considered as the world’s largest museum, and underwater sites explored and studied so far provide priceless information on human interaction with the sea. In recognition of the importance of this cultural resource, UNESCO, in its 2001 Convention on the Protection of the Underwater Cultural Heritage, determined that objects/sites should be preserved in situ, whilst also advocating for public access and sharing. The implementation of these principles is not without difficulties. Some states have opened up underwater sites to the public—mainly through diving, yet the vast majority of the world’s population does not dive. In Malta, 7000 years of human occupation is reflected in and on the landscape, and recent offshore surveys show that the islands’ long and complex history has also left an indelible mark on the seabed. Besides difficulties related to their protection and management, these sites also present a challenge with regard to sharing and communicating. Recent advances in underwater imaging and processing software have accelerated the development of 3D photogrammetry of submerged sites and the idea for a virtual museum was born. The virtual museum, UnderwaterMalta, was created out of a need to share the plethora of underwater sites located on the seabed of the Maltese Islands. A multitude of digital tools are used to share and communicate these sites, offering visitors a dry dive into submerged sites that would otherwise remain invisible to the vast majority of the public. This paper discusses the basic principle of the sharing of underwater cultural heritage and the difficulties that beset the implementation of such a principle. A detailed explanation and evaluation of the methods used to gather the raw data needed is set in the context of the particular and unique working conditions related to deep water sites. The workings of this paper are based on first-hand experiences garnered through the recording of numerous wrecks over the years and the creation and launch of The Virtual Museum-Underwater Malta—a comprehensive virtual museum specifically built for “displaying” underwater archaeological sites that are otherwise invisible to the general public.
Topside Ionosphere and Plasmasphere Modelling Using GNSS Radio Occultation and POD Data
Authors: Prol Fabricio S. , Hoque M. Mainul
Published: April 2021

A 3D-model approach has been developed to describe the electron density of the topside ionosphere and plasmasphere based on Global Navigation Satellite System (GNSS) measurements onboard low Earth orbit satellites. Electron density profiles derived from ionospheric Radio Occultation (RO) data are extrapolated to the upper ionosphere and plasmasphere based on a linear Vary-Chap function and Total Electron Content (TEC) measurements. A final update is then obtained by applying tomographic algorithms to the slant TEC measurements. Since the background specification is created with RO data, the proposed approach does not require using any external ionospheric/plasmaspheric model to adapt to the most recent data distributions. We assessed the model accuracy in 2013 and 2018 using independent TEC data, in situ electron density measurements, and ionosondes. A systematic better specification was obtained in comparison to NeQuick, with improvements around 15% in terms of electron density at 800 km, 26% at the top-most region (above 10,000 km) and 26% to 55% in terms of TEC, depending on the solar activity level. Our investigation shows that the developed model follows a known variation of electron density with respect to geographic/geomagnetic latitude, altitude, solar activity level, season, and local time, revealing the approach as a practical and useful tool for describing topside ionosphere and plasmasphere using satellite-based GNSS data.
Development of a Mobile Platform for Field-Based High-Throughput Wheat Phenotyping
Authors: Khak Pour Majid , Fotouhi Reza , Hucl Pierre , Zhang Qianwei
Published: April 2021

Designing and implementing an affordable High-Throughput Phenotyping Platform (HTPP) for monitoring crops’ features in different stages of their growth can provide valuable information for crop-breeders to study possible correlation between genotypes and phenotypes. Conducting automatic field measurements can improve crop productions. In this research, we have focused on development of a mechatronic system, hardware and software, for a mobile, field-based HTPP for autonomous crop monitoring for wheat field. The system can measure canopy’s height, temperature, and vegetation indices and is able to take high quality photos of crops. The system includes. developed software for data and image acquisition. The main contribution of this study is autonomous, reliable, and fast data collection for wheat and similar crops.
Generating a Baseline Map of Surface Fuel Loading Using Stratified Random Sampling Inventory Data through Cokriging and Multiple Linear Regression Methods
Authors: Lin Chinsu , Ma Siao-En , Huang Li-Ping , Chen Chung-I , Lin Pei-Ting , Yang Zhih-Kai , Lin Kuan-Ting
Published: April 2021

Surface fuel loading is a key factor in controlling wildfires and planning sustainable forest management. Spatially explicit maps of surface fuel loading can highlight the risks of a forest fire. Geospatial information is critical in enabling careful use of deliberate fire setting and also helps to minimize the possibility of heat conduction over forest lands. In contrast to lidar sensing and/or optical sensing based methods, an approach of integrating in-situ fuel inventory data, geospatial interpolation techniques, and multiple linear regression methods provides an alternative approach to surface fuel load estimation and mapping over mountainous forests. Using a stratified random sampling based inventory and cokriging analysis, surface fuel loading data of 120 plots distributed over four kinds of fuel types were collected in order to develop a total surface fuel loading model (lntSFL-BioTopo model) and a fine surface fuel model (lnfSFL-BioTopo model) for generating tSFL and fSFL maps. Results showed that the combination of topographic parameters such as slope, aspect, and their cross products and the fuel types such as pine stand, non-pine conifer stand, broadleaf stand, and conifer–broadleaf mixed stand was able to appropriately describe the changes in surface fuel loads over a forest with diverse terrain morphology. Based on a cross-validation method, the estimation of tSFL and fSFL of the study site had an RMSE of 3.476 tons/ha and 3.384 tons/ha, respectively. In contrast to the average loading of all inventory plots, the estimation for tSFL and fSFL had a relative error of 38% (PRMSE). The reciprocal of estimation bias of both SFL-BioTopo models tended to be an exponential growth function of the amount of surface fuel load, indicating that the estimation accuracy of the proposed method is likely to be improved with further study. In the regression modeling, a natural logarithm transformation of the surface fuel loading prevented the outcome of negative estimates and thus improved the estimation. Based on the results, this paper defined a minimum sampling unit (MSU) as the area for collecting surface fuels for interpolation using a cokriging model. Allocating the MSUs at the boundary and center of a plot improved surface fuel load prediction and mapping.
Estimating Agricultural Soil Moisture Content through UAV-Based Hyperspectral Images in the Arid Region
Authors: Ge Xiangyu , Ding Jianli , Jin Xiuliang , Wang Jingzhe , Chen Xiangyue , Li Xiaohang , Liu Jie , Xie Boqiang
Published: April 2021

Unmanned aerial vehicle (UAV)-based hyperspectral remote sensing is an important monitoring technology for the soil moisture content (SMC) of agroecological systems in arid regions. This technology develops precision farming and agricultural informatization. However, hyperspectral data are generally used in data mining. In this study, UAV-based hyperspectral imaging data with a resolution o 4 cm and totaling 70 soil samples (0–10 cm) were collected from farmland (2.5 × 104 m2) near Fukang City, Xinjiang Uygur Autonomous Region, China. Four estimation strategies were tested: the original image (strategy I), first- and second-order derivative methods (strategy II), the fractional-order derivative (FOD) technique (strategy III), and the optimal fractional order combined with the optimal multiband indices (strategy IV). These strategies were based on the eXtreme Gradient Boost (XGBoost) algorithm, with the aim of building the best estimation model for agricultural SMC in arid regions. The results demonstrated that FOD technology could effectively mine information (with an absolute maximum correlation coefficient of 0.768). By comparison, strategy IV yielded the best estimates out of the methods tested (R2val = 0.921, RMSEP = 1.943, and RPD = 2.736) for the SMC. The model derived from the order of 0.4 within strategy IV worked relatively well among the different derivative methods (strategy I, II, and III). In conclusion, the combination of FOD technology and the optimal multiband indices generated a highly accurate model within the XGBoost algorithm for SMC estimation. This research provided a promising data mining approach for UAV-based hyperspectral imaging data.
A Real-Time GNSS/PDR Navigation System for Mobile Devices
Authors: Basso Michele , Martinelli Alessio , Morosi Simone , Sera Fabrizio
Published: April 2021

In this article, a smart pedestrian navigation system is developed to be implemented in a common smartphone. The main phases that characterize a pedestrian navigation system that is based on dead reckoning are introduced. A suitable Phase-Locked Loop is designed and the algorithm to estimate the direction of the user’s motion between one step and the next is developed. Finally, a suitable multi-rate Kalman filter (KF) is considered to merge the information from the pedestrian dead reckoning (PDR) navigation with the data provided by the global navigation satellite systems (GNSS). The proposed GNSS/PDR navigation system is implemented in Simulink as a finite-state machine and allows to define a trade-off between energy-saving and performance improvement in terms of position accuracy. The presented pedestrian navigation system is independent of the body-worn location of the smartphone and implements a compensation strategy of the systematic errors that are committed on the step-length estimation and the determination of the motion direction. Moreover, several tests are performed by walking in urban and suburban environments: the results show that a suitable trade-off between energy-saving and position accuracy can be reached by switching the GNSS receiver on and off.
Ku- and Ka-Band Ocean Surface Radar Backscatter Model Functions at Low-Incidence Angles Using Full-Swath GPM DPR Data
Authors: Hossan Alamgir , Jones William Linwood
Published: April 2021

This paper presents the results of the first characterization of coincident Ku- and Ka-band ocean surface normalized radar cross section measurements at earth incidence angles 0°–18° using one year of wide swath Global Precipitation Measurement (GPM) mission dual frequency precipitation radar (DPR) data. Empirical geophysical model functions were derived for both bands, isotropic and directorial sensitivity were assessed, and finally, sea surface temperature (SST) dependence of radar backscatter, at both bands, were investigated. The Ka-band exhibited higher vector wind sensitivity for a low-to-moderate wind speeds regime, and the SST effects were also observed to be substantially larger at Ka-band than at Ku-band.
Surface Freshwater Fluxes in the Arctic and Subarctic Seas during Contrasting Years of High and Low Summer Sea Ice Extent
Authors: Hall Sarah B. , Subrahmanyam Bulusu , Nyadjro Ebenezer S. , Samuelsen Annette
Published: April 2021

Freshwater (FW) flux between the Arctic Ocean and adjacent waterways, predominantly driven by wind and oceanic currents, influences halocline stability and annual sea ice variability which further impacts global circulation and climate. The Arctic recently experienced anomalous years of high and low sea ice extent in the summers of 2013/2014 and 2012/2016, respectively. Here we investigate the interannual variability of oceanic surface FW flux in relation to spatial and temporal variability in sea ice concentration (SIC), sea surface salinity (SSS), and sea surface temperature (SST), focusing on years with summer sea–ice extremes. Our analysis between 2010–2018 illustrate high parameter variability, especially within the Laptev, Kara, and Barents seas, as well as an overall decreasing trend of FW flux through the Fram Strait. We find that in 2012, a maximum average FW flux of 0.32 × 103 ms−1 in October passed over a large portion of the Northeast Atlantic Ocean at 53°N. This study highlights recent changes in the Arctic and Subarctic Seas and the importance of continued monitoring of key variables through remote sensing to understand the dynamics behind these ongoing changes. Observations of FW fluxes through major Arctic routes will be increasingly important as the polar regions become more susceptible to warming, with major impacts on global climate.
Comparing Luojia 1-01 and VIIRS Nighttime Light Data in Detecting Urban Spatial Structure Using a Threshold-Based Kernel Density Estimation
Authors: Wang Yuping , Shen Zehao
Published: April 2021

Nighttime light (NTL) data are increasingly used in urban studies and urban planning owing to their strong connection with human activities, although the detection capacity is limited by the spatial resolution of older data. In the present study, we comparedthe results of extractions of urban built-up areas using data obtained from the first professional NTL satellite Luojia 1-01 with a resolution of 130 m and the Visible Infrared Imaging Radiometer Suite (VIIRS). We applied an analyzing framework combing kernel density estimation (KDE) under different search radii and threshold-based extraction to detect the boundary and spatial structure of urban areas. The results showed that: (1) Benefiting from a higher spatial resolution, Luojia 1-01 data was more sensitive in detecting new emerging urban built-up areas, thus better reflected the spatial structure of urban system, and can achieve a higher extraction accuracy than that of VIIRS data; (2) Combining with a proper threshold, KDE improves the extraction accuracy of NTL data by making use of the spatial autocorrelation of nighttime light, thus better detects the scale of the spatial pattern of urban built-up areas; (3) A proper searching radius for KDE is critical for achieving the optimal result, which was 1000 m for Luojia 1-01 and 1600 m for VIIRS in this study. Our findings indicate the usefulness of the KDE method in applying the upcoming high-resolution NTL data such as Luojia 1-01 data in urban spatial analysis and planning.
Long-Term and Emergency Monitoring of Zhongbao Landslide Using Space-Borne and Ground-Based InSAR
Authors: Xiao Ting , Huang Wei , Deng Yunkai , Tian Weiming , Sha Yonglian
Published: April 2021

This work presents the ideal combination of space-borne and ground-based (GB) Interferometric Synthetic Aperture Radar (InSAR) applications. In the absence of early investigation reporting and specialized monitoring, the Zhongbao landslide unexpectedly occurred on 25 July 2020, forming a barrier lake that caused an emergency. As an emergency measure, the GB-InSAR system was installed 1.8 km opposite the landslide to assess real-time cumulative deformation with a monitoring frequency of 3 min. A zone of strong deformation was detected, with 178 mm deformation accumulated within 15 h, and then a successful emergency warning was issued to evacuate on-site personnel. Post-event InSAR analysis of 19 images acquired by the ESA Sentinel-1 from December 2019 to August 2020 revealed that the landslide started in March 2020. However, the deformation time series obtained from satellite InSAR did not show any signs that the landslide had occurred. The results suggest that satellite InSAR is effective for mapping unstable areas but is not qualified for rapid landslide monitoring and timely warning. The GB-InSAR system performs well in monitoring and providing early warning, even with dense vegetation on the landslide. The results show the shortcomings of satellite InSAR and GB-InSAR and a clearer understanding of the necessity of combining multiple monitoring methods.
A User Centered Methodology for the Design of Smart Apparel for Older Users
Authors: Imbesi Silvia , Scataglini Sofia
Published: April 2021

Smart clothing plays a big role to foster innovation and to. boost health and well-being, improving the quality of the life of people, especially when addressed to niche users with particular needs related to their health. Designing smart apparel, in order to monitor physical and physiological functions in older users, is a crucial asset that user centered design is exploring, balancing needs expressed by the users with technological requirements related to the design process. In this paper, the authors describe a user centered methodology for the design of smart garments based on the evaluation of users’ acceptance of smart clothing. This comparison method can be considered as similar to a simplified version of the quality function deployment tool, and is used to evaluate the general response of each garment typology to different categories of requirements, determining the propensity of the older user to the utilization of the developed product. The suggested methodology aims at introducing in the design process a tool to evaluate and compare developed solutions, reducing complexity in design processes by providing a tool for the comparison of significant solutions, correlating quantitative and qualitative factors.
Multiscale Analysis of Solar Loading Thermographic Signals for Wall Structure Inspection
Authors: Tu Katherine , Ibarra-Castanedo Clemente , Sfarra Stefano , Yao Yuan , Maldague Xavier P. V.
Published: April 2021

Infrared thermography has been widely adopted in many applications for material structure inspection, where data analysis methods are often implemented to elaborate raw thermal data and to characterize material structural properties. Herein, a multiscale thermographic data analysis framework is proposed and applied to building structure inspection. In detail, thermograms are first collected by conducting solar loading thermography, which are then decomposed into several intrinsic mode functions under different spatial scales by multidimensional ensemble empirical mode decomposition. At each scale, principal component analysis (PCA) is implemented for feature extraction. By visualizing the loading vectors of PCA, the important building structures are highlighted. Compared with principal component thermography that applies PCA directly to raw thermal data, the proposed multiscale analysis method is able to zoom in on different types of structural features.
Estimation of the Continuous Walking Angle of Knee and Ankle (Talocrural Joint, Subtalar Joint) of a Lower-Limb Exoskeleton Robot Using a Neural Network
Authors: Lee Taehoon , Kim Inwoo , Lee Soo-Hong
Published: April 2021

A lower-limb exoskeleton robot identifies the wearer′s walking intention and assists the walking movement through mechanical force; thus, it is important to be able to identify the wearer′s movement in real-time. Measurement of the angle of the knee and ankle can be difficult in the case of patients who cannot move the lower-limb joint properly. Therefore, in this study, the knee angle as well as the angles of the talocrural and subtalar joints of the ankle were estimated during walking by applying the neural network to two inertial measurement unit (IMU) sensors attached to the thigh and shank. First, for angle estimation, the gyroscope and accelerometer data of the IMU sensor were obtained while walking at a treadmill speed of 1 to 2.5 km/h while wearing an exoskeleton robot. The weights according to each walking speed were calculated using a neural network algorithm programmed in MATLAB software. Second, an appropriate weight was selected according to the walking speed through the IMU data, and the knee angle and the angles of the talocrural and subtalar joints of the ankle were estimated in real-time during walking through a feedforward neural network using the IMU data received in real-time. We confirmed that the angle estimation error was accurately estimated as 1.69° ± 1.43 (mean absolute error (MAE) ± standard deviation (SD)) for the knee joint, 1.29° ± 1.01 for the talocrural joint, and 0.82° ± 0.69 for the subtalar joint. Therefore, the proposed algorithm has potential for gait rehabilitation as it addresses the difficulty of estimating angles of lower extremity patients using torque and EMG sensors.
Lightweight Digital Certificate Management and Efficacious Symmetric Cryptographic Mechanism over Industrial Internet of Things
Authors: Ahmed Adel A.
Published: April 2021

The certificate authority, a trusted entity, issues digital certificates which contain identity credentials to help Industrial Internet of Things (IIoT) devices to represent their authenticity in a secure means. The crucial challenge of a digital certificate is to how design a secure certification authority management system that can counteract cyberattacks on the IIoT network. Moreover, current IIoT systems are not capable of implementing complex mathematical operations due to their constrained power capacity and processing capability. This paper proposes an effective, secure symmetric cryptographic mechanism (ESSC) based on the certificate authority management and Elliptic Curve Diffie Hellman (ECDH) to share a digital certificate among IIoT devices. The proposed certificate authority is used to securely exchange the shared secret key and to resolve the problem of spoofing attacks that may be used to impersonate the identity of the certificate authority. Also, ESSC uses the shared secret key to encrypt the sensitive data during transmission through the insecure communication channel. This research studies the adversary model for ESSC on IIoT and analyzes the cybersecurity of ESSC in the random oracle model. The findings that result from the experiments show that ESSC outperforms the baseline in terms of communication, computation, and storage costs. ESSC thus provides an adequate lightweight digital certificate management and cryptographic scheme which can help in the detection and prevention of several cyberattacks that can harm IIoT networks.
Introspective False Negative Prediction for Black-Box Object Detectors in Autonomous Driving
Authors: Yang Qinghua , Chen Hui , Chen Zhe , Su Junzhe
Published: April 2021

Object detection plays a critical role in autonomous driving, but current state-of-the-art object detectors will inevitably fail in many driving scenes, which is unacceptable for safety-critical automated vehicles. Given the complexity of the real traffic scenarios, it is impractical to guarantee zero detection failure; thus, online failure prediction is of crucial importance to mitigate the risk of traffic accidents. Of all the failure cases, False Negative (FN) objects are most likely to cause catastrophic consequences, but little attention has been paid to the online FN prediction. In this paper, we propose a general introspection framework that can make online prediction of FN objects for black-box object detectors. In contrast to existing methods which rely on empirical assumptions or handcrafted features, we facilitate the FN feature extraction by an introspective FN predictor we designed in this framework. For this purpose, we extend the original concept of introspection to object-wise FN predictions, and propose a multi-branch cooperation mechanism to address the distinct foreground-background imbalance problem of FN objects. The effectiveness of the proposed framework is verified through extensive experiments and analysis, and the results show that our method successfully predicts the FN objects with 81.95% precision for 88.10% recall on the challenging KITTI Benchmark, and effectively improves object detection performance by taking FN predictions into consideration.
Experimental Characterization of Spurious Signals in Magnetic Nanoparticles Enhanced Microwave Imaging of Cancer
Authors: Bucci Ovidio M. , Bellizzi Gennaro , Costanzo Sandra , Crocco Lorenzo , Di Massa Giuseppe , Scapaticci Rosa
Published: April 2021

Magnetic nanoparticles enhanced microwave imaging relies on the capability of modulating the response of such nanocomponents at microwaves by means of a (low frequency) polarizing magnetic field. In medical imaging, this capability allows for the detection and imaging of tumors loaded with nanoparticles. As the useful signal is the one which arises from nanoparticles, it is crucial to remove sources of undesired disturbance to enable the diagnosis of early-stage tumors. In particular, spurious signals arise from instrumental drift, as well as from the unavoidable interaction between the polarizing field and the imaging system. In this paper, we experimentally assess and characterize such spurious effects in order to set the optimal working conditions for magnetic nanoparticles enhanced microwave imaging of cancer. To this end, simple test devices, which include all components typically comprised in a microwave imaging system, have been realized and exploited. The experiment’s results allow us to derive design formulas and guidelines useful for limiting the impact of unwanted magnetic effects, as well as that relative to the instrumental drift on the signal generated by the magnetic nanoparticles-loaded tumor.
Magnesium Zirconate Titanate Thin Films Used as an NO2 Sensing Layer for Gas Sensor Applications Developed Using a Sol–Gel Method
Authors: Huang Pei-Shan , Lee Ke-Jing , Wang Yeong-Her
Published: April 2021

Magnesium zirconate titanate (MZT) thin films, used as a sensing layer on Al interdigitated electrodes prepared using a sol–gel spin-coating method, are demonstrated in this study. The p-type MZT/Al/SiO2/Si structure for sensing NO2 is also discussed. The results indicated that the best sensitivity of the gas sensor occurred when it was operating at a temperature ranging from 100 to 150 °C. The detection limit of the sensor was as low as 250 ppb. The sensitivity of the MZT thin film was 8.64% and 34.22% for 0.25 ppm and 5 ppm of NO2 gas molecules at a working temperature of 150 °C, respectively. The gas sensor also exhibited high repeatability and selectivity for NO2. The response values to 250, 500, 1000, 1500, 2000, 2500, and 5000 ppb NO2 at 150 °C were 8.64, 9.52, 12, 16.63, 20.3, 23, and 34.22%, respectively. Additionally, we observed a high sensing linearity in NO2 gas molecules. These results indicate that MZT-based materials have potential applications for use as gas sensors.