bluuebunny/crossref_metadata_2025 huggingface dataset:
Preparation and Thermoelectric Properties of Semiconducting Single-Walled Carbon Nanotubes/Regioregular Poly(3-dodecylthiophene) Composite Films
Authors: Wang Mengdi , Yao Qin , Qu Sanyin , Chen Yanling , Li Hui , Chen Lidong
Published: November 2020

Single-walled carbon nanotubes (SWNTs) have been widely used as leading additives for improving the thermoelectric properties of organic materials, due to their unique structure and excellent electronic transport properties. However, the as-synthesized SWNTs are mixtures (mix-SWNT) of semiconducting (sc-SWNT) and metallic (met-SWNT) carbon nanotubes. The significantly different surface character and transport behavior of sc-SWNT and met-SWNT frequently raise the difficulty of modifying microstructures, and tuning transport properties of SWNTs/organic composites, when using mix-SWNTs as dispersion phase. Herein, we prepared high quality sc-SWNTs/rr-P3DDT composite film by presorting pure sc-SWNT from the raw mix-SWNTs using regioregular poly(3-dodecylthiophene) (rr-P3DDT). Both the smoothness and compactness of sc-SWNTs/rr-P3DDT are great improved, as compared with the mix-SWNTs/rr-P3DDT films, and the sc-SWNTs are well-dispersed and uniformly wrapped by rr-P3DDT with diameter less than 50 nm. The significantly enhanced Seebeck coefficients and power factors are obtained in the sc-SWNT/rr-P3DDT samples. As the result, the maximum power factor of 60 μW/mK2 in 50 wt% sc-SWNTs sample is 70% higher than that of mix-SWNTs/P3DDT sample. This work reveals the effectiveness of pure semiconductor SWNTs as fillers to optimize the thermoelectric properties of CNT/polymer nano-composites.
Insights on Potential Formation Damage Mechanisms Associated with the Use of Gel Breakers in Hydraulic Fracturing
Authors: Almubarak Tariq , Ng Jun Hong C. , AlKhaldi Mohammed , Panda Saroj , Nasr-El-Din Hisham A.
Published: November 2020

Hydraulic fracturing using water-soluble polymers has been extensively used to enhance the productivity of oil and gas wells. However, the production enhancement can be significantly impaired due to polymer residue generated within the proppant pack in the created fractures. This work describes an approach to establish a suitable fracturing fluid cleanup process by characterizing broken polymer residues generated from the use of different gel breaker types. Commonly used gel breakers such as inorganic oxidizers (bromate and persulfate salts), specific enzymes, and acids were evaluated in this work. The influence of each gel breaker was examined using High-Pressure/High-Temperature (HP/HT) rheometer, aging cells, zeta potential, Gel Permeation Chromatography (GPC), and Environmental Scanning Electron Microscope/Energy Dispersive X-ray Spectroscopy (ESEM/EDS). Experiments were performed on a carboxymethylhydroxypropyl guar (CMHPG) fracturing fluid at temperatures up to 300 °F. The developed GPC methodology showed that the size of the broken polymer chains was mainly dependent on the type of gel breakers used. Moreover, laboratory tests have revealed that some gel breakers may negatively influence the performance of polymeric clay stabilizers. Additionally, this work showed damaging precipitations that can be generated due to the interactions of gel breakers with H2S.
Development of Equipment for Injection Molding of Polymer Products Filled with Recycled Polymer Waste
Authors: Synyuk Oleg , Musiał Janusz , Zlotenko Borys , Kulik Tetiana
Published: November 2020

Polymer waste of light industry and other industries is processed by chemical recycling and mechanical grinding. Modern equipment for polymer waste processing has the following drawbacks: significant energy consumption and reduced performance properties of recycled polymer. New technological processes and equipment for polymer waste recycling have been developed for the manufacture of light industry polymer products with increased performance characteristics. The manufacturing of such products was made possible by the development of the mathematical model, which describes the movement of a mixture of main polymer material and particles of recycled polymer waste in the process of filling a mold cavity. The model, in contrast to the existing models, allows observing the formation of the polymer product structure containing recycled waste particles. Improvement in the performance characteristics of shoe soles made by the injection molding of a mixture of polyvinylchloride and particles of recycled polyvinylchloride was confirmed by experimental tests of breaking strength and fatigue life. The results of these tests can be used in the design of processing equipment to obtain waste particles of the required shape and size and in the design of molds to provide the required concentration and orientation of waste particles in light industry polymer products.
Polyurethane/Nanosilver-Doped Halloysite Nanocomposites: Thermal, Mechanical Properties, and Antibacterial Properties
Authors: Sun Jui-Ting , Li Jia-Wun , Tsou Chi-Hui , Pang Jen-Chieh , Chung Ren-Jei , Chiu Chih-Wei
Published: November 2020

In this study, the researchers successfully embellished the surface of halloysite (Ag/HNTs) with silver using halloysite, silver nitrate (AgNO3), and polyvinylpyrrolidone (PVP). The researchers then prepared polyurethane that contained pyridine ring by using 4,4′-diphenylmethane diisocyanate (MDI) and polytetramethylene glycol (PTMG) as the hard chain segment and the soft chain segment of polyurethane (PU), as well as 2,6-pyridinedimethanol (2,6-PDM) as the chain extension agent. This was followed by the preparation of Ag/HNTs/PUs nanocomposite thin films, achieved by mixing Ag/HNTs with different ratios into polyurethane that contains pyridine ring. First, the Ag/HNTs powders were analyzed using energy-dispersive X-ray spectroscopy, X-ray diffraction, and transmission electron microscopy. Subsequently, Fourier-transform infrared spectroscopy was used to examine the dispersibility of Ag/HNTs in PU, whereas the thermal stability and the viscoelasticity of Ag/HNTs/PU were examined using thermal gravimetric analysis, differential scanning calorimetry, and dynamic mechanical analysis. When the mechanical properties of Ag/HNTs/PU were tested using a universal strength tester, the results indicated a maximum increase of 109.5% in tensile strength. The researchers then examined the surface roughness and the hydrophobic ability of the Ag/HNTs/PU thin films by using atomic force microscopy and water contact angle. Lastly, antibacterial testing on Escherichia coli revealed that when the additive of Ag/HNTs reached 2.0 wt%, 99.3% of the E. coli were eliminated. These results indicated that the addition of Ag/HNTs into PU could enhance the thermal stability, mechanical properties, and antibacterial properties of PU, implying the potential of Ag/HNTs-02 as biomedicine material.
ALS as Tool to Study Preferred Stem Inclination Directions
Authors: Lamprecht Sebastian , Stoffels Johannes , Udelhoven Thomas
Published: November 2020

Although gravitropism forces trees to grow vertically, stems have shown to prefer specific orientations. Apart from wind deforming the tree shape, lateral light can result in prevailing inclination directions. In recent years a species dependent interaction between gravitropism and phototropism, resulting in trunks leaning down-slope, has been confirmed, but a terrestrial investigation of such factors is limited to small scale surveys. ALS offers the opportunity to investigate trees remotely. This study shall clarify whether ALS detected tree trunks can be used to identify prevailing trunk inclinations. In particular, the effect of topography, wind, soil properties and scan direction are investigated empirically using linear regression models. 299.000 significantly inclined stems were investigated. Species-specific prevailing trunk orientations could be observed. About 58% of the inclination and 19% of the orientation could be explained by the linear models, while the tree species, tree height, aspect and slope could be identified as significant factors. The models indicate that deciduous trees tend to lean down-slope, while conifers tend to lean leeward. This study has shown that ALS is suitable to investigate the trunk orientation on larger scales. It provides empirical evidence for the effect of phototropism and wind on the trunk orientation.
Improving K-Nearest Neighbor Approaches for Density-Based Pixel Clustering in Hyperspectral Remote Sensing Images
Authors: Cariou Claude , Le Moan Steven , Chehdi Kacem
Published: November 2020

We investigated nearest-neighbor density-based clustering for hyperspectral image analysis. Four existing techniques were considered that rely on a K-nearest neighbor (KNN) graph to estimate local density and to propagate labels through algorithm-specific labeling decisions. We first improved two of these techniques, a KNN variant of the density peaks clustering method dpc, and a weighted-mode variant of knnclust, so the four methods use the same input KNN graph and only differ by their labeling rules. We propose two regularization schemes for hyperspectral image analysis: (i) a graph regularization based on mutual nearest neighbors (MNN) prior to clustering to improve cluster discovery in high dimensions; (ii) a spatial regularization to account for correlation between neighboring pixels. We demonstrate the relevance of the proposed methods on synthetic data and hyperspectral images, and show they achieve superior overall performances in most cases, outperforming the state-of-the-art methods by up to 20% in kappa index on real hyperspectral images.
Machine Learning-Aided Sea Ice Monitoring Using Feature Sequences Extracted from Spaceborne GNSS-Reflectometry Data
Authors: Zhu Yongchao , Tao Tingye , Yu Kegen , Qu Xiaochuan , Li Shuiping , Wickert Jens , Semmling Maximilian
Published: November 2020

Two effective machine learning-aided sea ice monitoring methods are investigated using 42 months of spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) data collected by the TechDemoSat-1 (TDS-1). The two-dimensional delay waveforms with different Doppler spread characteristics are applied to extract six features, which are combined to monitor sea ice using the decision tree (DT) and random forest (RF) algorithms. Firstly, the feature sequences are used as input variables and sea ice concentration (SIC) data from the Advanced Microwave Space Radiometer-2 (AMSR-2) are applied as targeted output to train the sea ice monitoring model. Hereafter, the performance of the proposed method is evaluated through comparing with the sea ice edge (SIE) data from the Special Sensor Microwave Imager Sounder (SSMIS) data. The DT- and RF-based methods achieve an overall accuracy of 97.51% and 98.03%, respectively, in the Arctic region and 95.46% and 95.96%, respectively, in the Antarctic region. The DT- and RF-based methods achieve similar accuracies, while the Kappa coefficient of RF-based approach is slightly larger than that of the DT-based approach, which indicates that the RF-based method outperforms the DT-based method. The results show the potential of monitoring sea ice using machine learning-aided GNSS-R approaches.
Sea Echoes for Airborne HF/VHF Radar: Mathematical Model and Simulation
Authors: Ding Fan , Zhao Chen , Chen Zezong , Li Jian
Published: November 2020

Currently, shore-based HF radars are widely used for coastal observations, and airborne radars are utilized for monitoring the ocean with a relatively large coverage offshore. In order to take the advantage of airborne radars, the theoretical mechanism of airborne HF/VHF radar for ocean surface observation has been studied in this paper. First, we describe the ocean surface wave height with the linear and nonlinear parts in a reasonable mathematical form and adopt the small perturbation method (SPM) to compute the HF/VHF radio scattered field induced by the sea surface. Second, the normalized radar cross section (NRCS) of the ocean surface is derived by tackling the field scattered from the random sea as a stochastic process. Third, the NRCS is simulated using the SPM under different sea states, at various radar operating frequencies and incident angles, and then the influences of these factors on radar sea echoes are investigated. At last, a comparison of NRCS using the SPM and the generalized function method (GFM) is done and analyzed. The mathematical model links the sea echoes and the ocean wave height spectrum, and it also offers a theoretical basis for designing a potential airborne HF/VHF radar for ocean surface remote sensing.
The Google Earth Engine Mangrove Mapping Methodology (GEEMMM)
Authors: Yancho J. , Jones Trevor , Gandhi Samir , Ferster Colin , Lin Alice , Glass Leah
Published: November 2020

Mangroves are found globally throughout tropical and sub-tropical inter-tidal coastlines. These highly biodiverse and carbon-dense ecosystems have multi-faceted value, providing critical goods and services to millions living in coastal communities and making significant contributions to global climate change mitigation through carbon sequestration and storage. Despite their many values, mangrove loss continues to be widespread in many regions due primarily to anthropogenic activities. Accessible, intuitive tools that enable coastal managers to map and monitor mangrove cover are needed to stem this loss. Remotely sensed data have a proven record for successfully mapping and monitoring mangroves, but conventional methods are limited by imagery availability, computing resources and accessibility. In addition, the variable tidal levels in mangroves presents a unique mapping challenge, particularly over geographically large extents. Here we present a new tool—the Google Earth Engine Mangrove Mapping Methodology (GEEMMM)—an intuitive, accessible and replicable approach which caters to a wide audience of non-specialist coastal managers and decision makers. The GEEMMM was developed based on a thorough review and incorporation of relevant mangrove remote sensing literature and harnesses the power of cloud computing including a simplified image-based tidal calibration approach. We demonstrate the tool for all of coastal Myanmar (Burma)—a global mangrove loss hotspot—including an assessment of multi-date mapping and dynamics outputs and a comparison of GEEMMM results to existing studies. Results—including both quantitative and qualitative accuracy assessments and comparisons to existing studies—indicate that the GEEMMM provides an accessible approach to map and monitor mangrove ecosystems anywhere within their global distribution.
Dust Dispersion and Its Effect on Vegetation Spectra at Canopy and Pixel Scales in an Open-Pit Mining Area
Authors: Ma Baodong , Li Xuexin , Jiang Ziwei , Pu Ruiliang , Liang Aiman , Che Defu
Published: November 2020

Dust pollution is severe in some mining areas in China due to rapid industrial development. Dust deposited on the vegetation canopy may change its spectra. However, a relationship between canopy spectra and dust amount has not been quantitatively studied, and a pixel-scale condition for remote sensing application has not been considered yet. In this study, the dust dispersion characteristics in an iron mining area were investigated using the American Meteorological Society (AMS) and the U.S. Environmental Protection Agency (EPA) regulatory model (AERMOD). Further, based on the three-dimensional discrete anisotropic radiative transfer (DART) model, the spectral characteristics of vegetation canopy under the dusty condition were simulated, and the influence of dustfall on vegetation canopy spectra was studied. Finally, the dust effect on vegetation spectra at the canopy scale was extended to a pixel scale, and the response of dust effect on vegetation spectra at the pixel scale was determined under different fractional vegetation covers (FVCs). The experimental results show that the dust pollution along a haul road was more severe and extensive than that in a stope. Taking dust dispersion along the road as an example, the variation of vegetation canopy spectra increased with the height of dust deposited on the vegetation canopy. At the pixel scale, a lower vegetation FVC would weaken the influence of dust on the spectra. The results derived from simulation spectral data were tested using satellite remote sensing images. The tested result indicates that the influence of dust retention on the pixel spectra with different FVCs was consistent with that created with the simulated data. The finding could be beneficial for those making decisions on monitoring vegetation under dusty conditions and reducing dust pollution in mining areas using remote sensing technology.
A Hybrid Attention-Aware Fusion Network (HAFNet) for Building Extraction from High-Resolution Imagery and LiDAR Data
Authors: Zhang Peng , Du Peijun , Lin Cong , Wang Xin , Li Erzhu , Xue Zhaohui , Bai Xuyu
Published: November 2020

Automated extraction of buildings from earth observation (EO) data has long been a fundamental but challenging research topic. Combining data from different modalities (e.g., high-resolution imagery (HRI) and light detection and ranging (LiDAR) data) has shown great potential in building extraction. Recent studies have examined the role that deep learning (DL) could play in both multimodal data fusion and urban object extraction. However, DL-based multimodal fusion networks may encounter the following limitations: (1) the individual modal and cross-modal features, which we consider both useful and important for final prediction, cannot be sufficiently learned and utilized and (2) the multimodal features are fused by a simple summation or concatenation, which appears ambiguous in selecting cross-modal complementary information. In this paper, we address these two limitations by proposing a hybrid attention-aware fusion network (HAFNet) for building extraction. It consists of RGB-specific, digital surface model (DSM)-specific, and cross-modal streams to sufficiently learn and utilize both individual modal and cross-modal features. Furthermore, an attention-aware multimodal fusion block (Att-MFBlock) was introduced to overcome the fusion problem by adaptively selecting and combining complementary features from each modality. Extensive experiments conducted on two publicly available datasets demonstrated the effectiveness of the proposed HAFNet for building extraction.
Characterization of Stratospheric Smoke Particles over the Antarctica by Remote Sensing Instruments
Authors: González Ramiro , Toledano Carlos , Román Roberto , Mateos David , Asmi Eija , Rodríguez Edith , Lau Ian C. , Ferrara Jonathan , D’Elia Raúl , Antuña-Sánchez Juan Carlos , Cachorro Victoria E. , Calle Abel , de Frutos Ángel M.
Published: November 2020

Australian smoke from the extraordinary biomass burning in December 2019 was observed over Marambio, Antarctica from the 7th to the 10th January, 2020. The smoke plume was transported thousands of kilometers over the Pacific Ocean, and reached the Antarctic Peninsula at a hight of 13 km, as determined by satellite lidar observations. The proposed origin and trajectory of the aerosol are supported by back-trajectory model analyses. Ground-based Sun–Sky–Moon photometer belonging to the Aerosol Robotic Network (AERONET) measured aerosol optical depth (500 nm wavelength) above 0.3, which is unprecedented for the site. Inversion of sky radiances provide the optical and microphysical properties of the smoke over Marambio. The AERONET data near the fire origin in Tumbarumba, Australia, was used to investigate the changes in the measured aerosol properties after transport and ageing. The analysis shows an increase in the fine mode particle radius and a reduction in absorption (increase in the single scattering albedo). The available long-term AOD data series at Marambio suggests that smoke particles could have remained over Antarctica for several weeks after the analyzed event.
Optimization and Analytical Behavior of Electrochemical Sensors Based on the Modification of Indium Tin Oxide (ITO) Using PANI/MWCNTs/AuNPs for Mercury Detection
Authors: Bohari Noor Aini , Siddiquee Shafiquzzaman , Saallah Suryani , Misson Mailin , Arshad Sazmal Effendi
Published: November 2020

In the present study, indium tin oxide (ITO) was used as a transparent working electrode for the development of an electrochemical sensor for the detection of mercury (II) ions (Hg2+). The electrode was modified by direct electrodeposition of polyaniline (PANI), multiwalled carbon nanotubes (MWCNTs) and gold nanoparticles (AuNPs) followed by optimization of the analyte and operating conditions, aiming to improve the selectivity, sensitivity and reliability of the electrode for mercury detection. Successful immobilization of the PANI and nanomaterials (MWCNTs and AuNPs) on the ITO electrode was confirmed by Scanning Electron Microscope (SEM), Energy Dispersive X-ray (EDX) and Fourier Transform Infrared Spectroscopy (FTIR) analyses. The optimum conditions for mercury detection using the modified ITO electrode were pH 7.0 of Tris-HCl buffer (50 mM) in the presence of 1 mM methylene blue (MB) as a redox indicator, a scan rate of 0.10 V·s−1 and a 70 s interaction time. The electrochemical behavior of the modified electrode under the optimized conditions indicated a high reproducibility and high sensitivity of mercury detection. It is therefore suggested that the PANI/MWCNT/AuNP-modified ITO electrode could be a promising material for the development of on-site mercury detection tools for applications in fields such as diagnostics, the environment, safety and security controls or other industries.
Vital Sign Monitoring Using FMCW Radar in Various Sleeping Scenarios
Authors: Turppa Emmi , Kortelainen Juha M. , Antropov Oleg , Kiuru Tero
Published: November 2020

Remote monitoring of vital signs for studying sleep is a user-friendly alternative to monitoring with sensors attached to the skin. For instance, remote monitoring can allow unconstrained movement during sleep, whereas detectors requiring a physical contact may detach and interrupt the measurement and affect sleep itself. This study evaluates the performance of a cost-effective frequency modulated continuous wave (FMCW) radar in remote monitoring of heart rate and respiration in scenarios resembling a set of normal and abnormal physiological conditions during sleep. We evaluate the vital signs of ten subjects in different lying positions during various tasks. Specifically, we aim for a broad range of both heart and respiration rates to replicate various real-life scenarios and to test the robustness of the selected vital sign extraction methods consisting of fast Fourier transform based cepstral and autocorrelation analyses. As compared to the reference signals obtained using Embla titanium, a certified medical device, we achieved an overall relative mean absolute error of 3.6% (86% correlation) and 9.1% (91% correlation) for the heart rate and respiration rate, respectively. Our results promote radar-based clinical monitoring by showing that the proposed radar technology and signal processing methods accurately capture even such alarming vital signs as minimal respiration. Furthermore, we show that common parameters for heart rate variability can also be accurately extracted from the radar signal, enabling further sleep analyses.
Study of the Vertical Structure of the Coastal Boundary Layer Integrating Surface Measurements and Ground-Based Remote Sensing
Authors: Lo Feudo Teresa , Calidonna Claudia Roberta , Avolio Elenio , Sempreviva Anna Maria
Published: November 2020

The understanding of the atmospheric processes in coastal areas requires the availability of quality datasets describing the vertical and horizontal spatial structure of the Atmospheric Boundary Layer (ABL) on either side of the coastline. High-resolution Numerical Weather Prediction (NWP) models can provide this information and the main ingredients for good simulations are: an accurate description of the coastline and a correct subgrid process parametrization permitting coastline discontinuities to be caught. To provide an as comprehensive as possible dataset on Mediterranean coastal area, an intensive experimental campaign was realized at a near-shore Italian site, using optical and acoustic ground-based remote sensing and surface instruments, under different weather characteristic and stability conditions; the campaign is also fully simulated by a NWP model. Integrating information from instruments responding to different atmospheric properties allowed for an explanation of the development of various patterns in the vertical structure of the atmosphere. Wind LiDAR measurements provided information of the internal boundary layer from the value of maximum height reached by the wind profile; a height between 80 and 130 m is often detected as an interface between two different layers. The NWP model was able to simulate the vertical wind profiles and the eight of the ABL.
Research on the eLoran Differential Timing Method
Authors: Li Yun , Hua Yu , Yan Baorong , Guo Wei
Published: November 2020

An enhanced long-range navigation (eLoran) system was selected as the backup of Global Navigation Satellite Systems (GNSS), and experts and scholars are committed to improving the accuracy of the eLoran system such that its accuracy is close to the GNSS system. A differential method called eLoran differential timing technology is applied to the eLoran system, which has been used in maritime applications of eLoran. In this study, an application of eLoran differential timing technology in a terrestrial medium is carried out. Based on the eLoran timing service error, the correlation of the timing service error is analyzed in theory quantitatively to obtain the range of the difference station in the ground. The results show that to satisfy the timing accuracy of 100 ns, the action range of eLoran difference station on the land needs to be less than 55 km. Therefore, the eLoran differential method is proposed, and in the difference station, the theoretical calculation is combined with the measurement of the signal delay to obtain the difference information, which is sent to the users to adjust the prediction delay and improve the eLoran timing precision. The experiment was carried out in the Guan Zhong Plain, and the timing error of the user decreased from 394.7287 ns (pre-difference) to 19.5890 ns (post-difference). The proposed method is found to effectively enhance the timing precision of the eLoran system within the scope of action.
An Automated Planning Model for HRI: Use Cases on Social Assistive Robotics
Authors: Fuentetaja Raquel , García-Olaya Angel , García Javier , González José Carlos , Fernández Fernando
Published: November 2020

Using Automated Planning for the high level control of robotic architectures is becoming very popular thanks mainly to its capability to define the tasks to perform in a declarative way. However, classical planning tasks, even in its basic standard Planning Domain Definition Language (PDDL) format, are still very hard to formalize for non expert engineers when the use case to model is complex. Human Robot Interaction (HRI) is one of those complex environments. This manuscript describes the rationale followed to design a planning model able to control social autonomous robots interacting with humans. It is the result of the authors’ experience in modeling use cases for Social Assistive Robotics (SAR) in two areas related to healthcare: Comprehensive Geriatric Assessment (CGA) and non-contact rehabilitation therapies for patients with physical impairments. In this work a general definition of these two use cases in a unique planning domain is proposed, which favors the management and integration with the software robotic architecture, as well as the addition of new use cases. Results show that the model is able to capture all the relevant aspects of the Human-Robot interaction in those scenarios, allowing the robot to autonomously perform the tasks by using a standard planning-execution architecture.
State-Transition Modeling of Human–Robot Interaction for Easy Crowdsourced Robot Control
Authors: Iwasaki Masaya , Ikeda Mizuki , Kawamura Tatsuyuki , Nakanishi Hideyuki
Published: November 2020

Robotic salespeople are often ignored by people due to their weak social presence, and thus have difficulty facilitating sales autonomously. However, for robots that are remotely controlled by humans, there is a need for experienced and trained operators. In this paper, we suggest crowdsourcing to allow general users on the internet to operate a robot remotely and facilitate customers’ purchasing activities while flexibly responding to various situations through a user interface. To implement this system, we examined how our developed remote interface can improve a robot’s social presence while being controlled by a human operator, including first-time users. Therefore, we investigated the typical flow of a customer–robot interaction that was effective for sales promotion, and modeled it as a state transition with automatic functions by accessing the robot’s sensor information. Furthermore, we created a user interface based on the model and examined whether it was effective in a real environment. Finally, we conducted experiments to examine whether the user interface could be operated by an amateur user and enhance the robot’s social presence. The results revealed that our model was able to improve the robot’s social presence and facilitate customers’ purchasing activity even when the operator was a first-time user.
Estimating Energy Dissipation Rate from Breaking Waves Using Polarimetric SAR Images
Authors: Viana Rafael D. , Lorenzzetti João A. , Carvalho Jonas T. , Nunziata Ferdinando
Published: November 2020

The total energy dissipation rate on the ocean surface, ϵt (W m−2), provides a first-order estimation of the kinetic energy input rate at the ocean–atmosphere interface. Studies on the spatial and temporal distribution of the energy dissipation rate are important for the improvement of climate and wave models. Traditional oceanographic research normally uses remote measurements (airborne and platforms sensors) and in situ data acquisition to estimate ϵt; however, those methods cover small areas over time and are difficult to reproduce especially in the open oceans. Satellite remote sensing has proven the potential to estimate some parameters related to breaking waves on a synoptic scale, including the energy dissipation rate. In this paper, we use polarimetric Synthetic Aperture Radar (SAR) data to estimate ϵt under different wind and sea conditions. The used methodology consisted of decomposing the backscatter SAR return in terms of two contributions: a polarized contribution, associated with the fast response of the local wind (Bragg backscattering), and a non-polarized (NP) contribution, associated with wave breaking (Non-Bragg backscattering). Wind and wave parameters were estimated from the NP contribution and used to calculate ϵt from a parametric model dependent of these parameters. The results were analyzed using wave model outputs (WAVEWATCH III) and previous measurements documented in the literature. For the prevailing wind seas conditions, the ϵt estimated from pol-SAR data showed good agreement with dissipation associated with breaking waves when compared to numerical simulations. Under prevailing swell conditions, the total energy dissipation rate was higher than expected. The methodology adopted proved to be satisfactory to estimate the total energy dissipation rate for light to moderate wind conditions (winds below 10 m s−1), an environmental condition for which the current SAR polarimetric methods do not estimate ϵt properly.
IMSC-EIoTD: Identity Management and Secure Communication for Edge IoT Devices
Authors: Sadique Kazi Masum , Rahmani Rahim , Johannesson Paul
Published: November 2020

The Internet of things (IoT) will accommodate several billions of devices to the Internet to enhance human society as well as to improve the quality of living. A huge number of sensors, actuators, gateways, servers, and related end-user applications will be connected to the Internet. All these entities require identities to communicate with each other. The communicating devices may have mobility and currently, the only main identity solution is IP based identity management which is not suitable for the authentication and authorization of the heterogeneous IoT devices. Sometimes devices and applications need to communicate in real-time to make decisions within very short times. Most of the recently proposed solutions for identity management are cloud-based. Those cloud-based identity management solutions are not feasible for heterogeneous IoT devices. In this paper, we have proposed an edge-fog based decentralized identity management and authentication solution for IoT devices (IoTD) and edge IoT gateways (EIoTG). We have also presented a secure communication protocol for communication between edge IoT devices and edge IoT gateways. The proposed security protocols are verified using Scyther formal verification tool, which is a popular tool for automated verification of security protocols. The proposed model is specified using the PROMELA language. SPIN model checker is used to confirm the specification of the proposed model. The results show different message flows without any error.
Time Difference of Arrival Passive Localization Sensor Selection Method Based on Tabu Search
Authors: Li Qian , Chen Baixiao , Yang Minglei
Published: November 2020

This paper proposes a time difference of arrival (TDOA) passive positioning sensor selection method based on tabu search to balance the relationship between the positioning accuracy of the sensor network and system consumption. First, the passive time difference positioning model, taking into account the sensor position errors, is considered. Then, an approximate closed-form constrained total least-squares (CTLS) solution and a covariance matrix of the positioning error are provided. By introducing a Boolean selection vector, the sensor selection problem is transformed into an optimization problem that minimizes the trace of the positioning error covariance matrix. Thereafter, the tabu search method is employed to solve the transformed sensor selection problem. The simulation results show that the performance of the proposed sensor optimization method considerably approximates that of the exhaustive search method. Moreover, it can significantly reduce the running time and improve the timeliness of the algorithm.
Frequency-Temporal Disagreement Adaptation for Robotic Terrain Classification via Vibration in a Dynamic Environment
Authors: Cheng Chen , Chang Ji , Lv Wenjun , Wu Yuping , Li Kun , Li Zerui , Yuan Chenhui , Ma Saifei
Published: November 2020

The accurate terrain classification in real time is of great importance to an autonomous robot working in field, because the robot could avoid non-geometric hazards, adjust control scheme, or improve localization accuracy, with the aid of terrain classification. In this paper, we investigate the vibration-based terrain classification (VTC) in a dynamic environment, and propose a novel learning framework, named DyVTC, which tackles online-collected unlabeled data with concept drift. In the DyVTC framework, the exterior disagreement (ex-disagreement) and interior disagreement (in-disagreement) are proposed novely based on the feature diversity and intrinsic temporal correlation, respectively. Such a disagreement mechanism is utilized to design a pseudo-labeling algorithm, which shows its compelling advantages in extracting key samples and labeling; and consequently, the classification accuracy could be retrieved by incremental learning in a changing environment. Since two sets of features are extracted from frequency and time domain to generate disagreements, we also name the proposed method feature-temporal disagreement adaptation (FTDA). The real-world experiment shows that the proposed DyVTC could reach an accuracy of 89.5%, but the traditional time- and frequency-domain terrain classification methods could only reach 48.8% and 71.5%, respectively, in a dynamic environment.
Reduction in Irradiation Dose in Aperture Coded Enhanced Computed Tomography Imager Using Super-Resolution Techniques
Authors: Danan Yossef , Avraham Doron , Zalevsky Zeev
Published: November 2020

One of the main concerns regarding medical imaging is the danger tissue’s ionizing due to the applied radiation. Many medical procedures are based on this ionizing radiation (such as X-rays and Gamma radiation). This radiation allows the physician to perform diagnosis inside the human body. Still, the main concern is stochastic effects to the DNA, particularly the cause of cancer. The radiation dose endangers not only the patient but also the medical staff, who might be close to the patient and be exposed to this dangerous radiation in a daily manner. This paper presents a novel concept of radiation reduced Computed Tomography (CT) scans. The proposed concept includes two main methods: minification to enhance the energy concertation per pixel and subpixel resolution enhancement, using shifted images, to preserve resolution. The proposed process uses several pinhole masks as the base of the imaging modality. The proposed concept was validated numerically and experimentally and has demonstrated the capability of reducing the radiation efficiency by factor 4, being highly significant to the world of radiology and CT scans. This dose reduction allows a safer imaging process for the patient and the medical staff. This method simplifies the system and improves the obtained image quality. The proposed method can contribute additively to standard existing dose reduction or super-resolution techniques to achieve even better performance.
Head-Mounted Display-Based Application for Cognitive Training
Authors: Varela-Aldás José , Palacios-Navarro Guillermo , Amariglio Rebecca , García-Magariño Iván
Published: November 2020

Virtual Reality (VR) has had significant advances in rehabilitation, due to the gamification of cognitive activities that facilitate treatment. On the other hand, Immersive Virtual Reality (IVR) produces outstanding results due to the interactive features with the user. This work introduces a VR application for memory rehabilitation by walking through a maze and using the Oculus Go head-mounted display (HMD) technology. The mechanics of the game require memorizing geometric shapes while the player progresses in two modes, autonomous or manual, with two levels of difficulty depending on the number of elements to remember. The application is developed in the Unity 3D video game engine considering the optimization of computational resources to improve the performance in the processing and maintaining adequate benefits for the user, while the generated data is stored and sent to a remote server. The maze task was assessed with 29 subjects in a controlled environment. The obtained results show a significant correlation between participants’ response accuracy in both the maze task and a face–pair test. Thus, the proposed task is able to perform memory assessments.
Probabilistic Evaluation of 3D Surfaces Using Statistical Shape Models (SSM)
Authors: Pérez Javier , Guardiola Jose-Luis , Perez Alberto J. , Perez-Cortes Juan-Carlos
Published: November 2020

Inspecting a 3D object which shape has elastic manufacturing tolerances in order to find defects is a challenging and time-consuming task. This task usually involves humans, either in the specification stage followed by some automatic measurements, or in other points along the process. Even when a detailed inspection is performed, the measurements are limited to a few dimensions instead of a complete examination of the object. In this work, a probabilistic method to evaluate 3D surfaces is presented. This algorithm relies on a training stage to learn the shape of the object building a statistical shape model. Making use of this model, any inspected object can be evaluated obtaining a probability that the whole object or any of its dimensions are compatible with the model, thus allowing to easily find defective objects. Results in simulated and real environments are presented and compared to two different alternatives.
Maturity Prediction in Yellow Peach (Prunus persica L.) Cultivars Using a Fluorescence Spectrometer
Authors: Scalisi Alessio , Pelliccia Daniele , O’Connell Mark Glenn
Published: November 2020

Technology for rapid, non-invasive and accurate determination of fruit maturity is increasingly sought after in horticultural industries. This study investigated the ability to predict fruit maturity of yellow peach cultivars using a prototype non-destructive fluorescence spectrometer. Collected spectra were analysed to predict flesh firmness (FF), soluble solids concentration (SSC), index of absorbance difference (IAD), skin and flesh colour attributes (i.e., a* and H°) and maturity classes (immature, harvest-ready and mature) in four yellow peach cultivars—‘August Flame’, ‘O’Henry’, ‘Redhaven’ and ‘September Sun’. The cultivars provided a diverse range of maturity indices. The fluorescence spectrometer consistently predicted IAD and skin colour in all the cultivars under study with high accuracy (Lin’s concordance correlation coefficient > 0.85), whereas flesh colour’s estimation was always accurate apart from ‘Redhaven’. Except for ‘September Sun’, good prediction of FF and SSC was observed. Fruit maturity classes were reliably predicted with a high likelihood (F1-score = 0.85) when samples from the four cultivars were pooled together. Further studies are needed to assess the performance of the fluorescence spectrometer on other fruit crops. Work is underway to develop a handheld version of the fluorescence spectrometer to improve the utility and adoption by fruit growers, packhouses and supply chain managers.
Estimating Surgical Blood Loss Volume Using Continuously Monitored Vital Signs
Authors: Chen Yang , Hong Chengcheng , Pinsky Michael R. , Ma Ting , Clermont Gilles
Published: November 2020

Background: There are currently no effective and accurate blood loss volume (BLV) estimation methods that can be implemented in operating rooms. To improve the accuracy and reliability of BLV estimation and facilitate clinical implementation, we propose a novel estimation method using continuously monitored photoplethysmography (PPG) and invasive arterial blood pressure (ABP). Methods: Forty anesthetized York Pigs (31.82 ± 3.52 kg) underwent a controlled hemorrhage at 20 mL/min until shock development was included. Machine-learning-based BLV estimation models were proposed and tested on normalized features derived by vital signs. Results: The results showed that the mean ± standard deviation (SD) for estimating BLV against the reference BLV of our proposed random-forest-derived BLV estimation models using PPG and ABP features, as well as the combination of ABP and PPG features, were 11.9 ± 156.2, 6.5 ± 161.5, and 7.0 ± 139.4 mL, respectively. Compared with traditional hematocrit computation formulas (estimation error: 102.1 ± 313.5 mL), our proposed models outperformed by nearly 200 mL in SD. Conclusion: This is the first attempt at predicting quantitative BLV from noninvasive measurements. Normalized PPG features are superior to ABP in accurately estimating early-stage BLV, and normalized invasive ABP features could enhance model performance in the event of a massive BLV.
Recognition of Typical Locomotion Activities Based on the Sensor Data of a Smartphone in Pocket or Hand
Authors: Ebner Markus , Fetzer Toni , Bullmann Markus , Deinzer Frank , Grzegorzek Marcin
Published: November 2020

With the ubiquity of smartphones, the interest in indoor localization as a research area grew. Methods based on radio data are predominant, but due to the susceptibility of these radio signals to a number of dynamic influences, good localization solutions usually rely on additional sources of information, which provide relative information about the current location. Part of this role is often taken by the field of activity recognition, e.g., by estimating whether a pedestrian is currently taking the stairs. This work presents different approaches for activity recognition, considering the four most basic locomotion activities used when moving around inside buildings: standing, walking, ascending stairs, and descending stairs, as well as an additional messing around class for rejections. As main contribution, we introduce a novel approach based on analytical transformations combined with artificially constructed sensor channels, and compare that to two approaches adapted from existing literature, one based on codebooks, the other using statistical features. Data is acquired using accelerometer and gyroscope only. In addition to the most widely adopted use-case of carrying the smartphone in the trouser pockets, we will equally consider the novel use-case of hand-carried smartphones. This is required as in an indoor localization scenario, the smartphone is often used to display a user interface of some navigation application and thus needs to be carried in hand. For evaluation the well known MobiAct dataset for the pocket-case as well as a novel dataset for the hand-case were used. The approach based on analytical transformations surpassed the other approaches resulting in accuracies of 98.0% for pocket-case and 81.8% for the hand-case trained on the combination of both datasets. With activity recognition in the supporting role of indoor localization, this accuracy is acceptable, but has room for further improvement.
How to Create Walking Friendly Cities. A Multi-Criteria Analysis of the Central Open Market Area of Rijeka
Authors: Campisi Tiziana , Basbas Socrates , Tesoriere Giovanni , Trouva Mirto , Papas Thomas , Mrak Iva
Published: November 2020

Current mobility strategies tend to pursue sustainable solutions with low environmental and economic impact, such as the disincentive to the use of private vehicles. Mobility on foot is among the most advantageous forms for short distances, especially if different technological and infrastructural solutions are inserted in the urban context such as underpasses that limit the likely conflicts with motor vehicles. These solutions, however, are not easily perceived as positive because people often do not like to change their usual routes or because they feel psychological discomfort when they pass through closed places. This research work focuses on the evaluation of the benefits of including a small underpass in the city of Rijeka, Croatia and through an Analytical Hierarchy Process (AHP), a multi-criteria analysis, it was possible to prioritize a number of decision-making alternatives, related to qualitative and quantitative evaluations, otherwise not directly comparable, and combining multidimensional measurement scales into a single priority scale. This analysis allows to provide cues for local and non-local urban planning, encouraging through the participatory form an active comparison between the population and local authorities and at the same time allows to assess which multidisciplinary processes (psychological/engineering) are possible to put in place to encourage the research on pedestrian behavior.