bluuebunny/crossref_metadata_2025 huggingface dataset:
Preparation and Characterization of UV-LED Curable Acrylic Films Containing Biochar and/or Multiwalled Carbon Nanotubes: Effect of the Filler Loading on the Rheological, Thermal and Optical Properties
Authors: Strongone Valentina , Bartoli Mattia , Jagdale Pravin , Arrigo Rossella , Tagliaferro Alberto , Malucelli Giulio
Published: April 2020

UV-LED curable coatings represent an up-to-date attractive field due to the high curing efficiency even in the presence of high filler loadings, as well as to the absence of infrared wavelengths that may negatively impact on heat-sensitive substrates. The addition of carbonaceous materials, such as biochar (BC) and/or multiwalled carbon nanotubes (MWCNTs) could positively improve both the rheological and thermal properties. In this study we report on the synthesis and characterization of carbon-reinforced films containing nanometric (MWCNTs) and micrometric (BC) carbon-based materials. We analyze the rheological properties of the UV-LED curable dispersions, as well as the thermal and optical properties of the resulting films, establishing some correlations between filler dispersion/loading with the main observed properties.
Correction: Tham, P.E., et al. Recovery of Protein from Dairy Milk Waste Product Using Alcohol–Salt Liquid Biphasic Flotation. Processes 2019, 7, 875
Authors: Tham Pei En , Ng Yan Jer , Sankaran Revathy , Khoo Kuan Shiong , Chew Kit Wayne , Yap Yee Jiun , Malahubban Masnindah , Aziz Zakry Fitri Abdul , Show Pau Loke
Published: April 2020

We were not aware of some errors made in the proofreading phase; therefore, we wish to make the following corrections to the mathematical equations in the text [...]
An Optimal Sizing of Stand-Alone Hybrid PV-Fuel Cell-Battery to Desalinate Seawater at Saudi NEOM City
Authors: Rezk Hegazy , Alghassab Mohammed , Ziedan Hamdy A.
Published: April 2020

NEOM City in Saudi Arabia is planned to be the first environmentally friendly city in the world that is powered by renewable energy sources minimizing CO2 emissions to reduce the effect of global warming according to Saudi Arabia’s Vision 2030. In recent years, Saudi Arabia has had a problem with water scarcity. The main factors affecting water security are unequal water distribution, wrong use of water resources and using bad or less efficient irrigation techniques. This paper is aimed to provide a detailed feasibility and techno-economic evaluation of using several scenarios of a stand-alone hybrid renewable energy system to satisfy the electrical energy needs for an environmentally friendly seawater desalination plant which feeds 150 m−3 day−1 of freshwater to 1000 people in NEOM City, Saudi Arabia. The first scenario is based on hybrid solar photovoltaic PV, fuel cells (FC) with a hydrogen storage system and batteries system (BS), while the second and third scenarios are based on hybrid PV/BS and PV/FC with a hydrogen storage system, respectively. HOMER® software was used to obtain the optimal configuration based on techno-economic analysis of each component of the hybrid renewable energy systems and an economic and environmental point of view based on the values of net present cost (NPC) and cost of energy (COE). Based on the obtained results, the best configuration is PV/FC/BS. The optimal size and related costs for the optimal size are 235 kW PV array, 30 kW FC, 144 batteries, 30 kW converter, 130 kW electrolyzer, and 25 kg hydrogen tank is considered the best option for powering a 150 m3 reverse osmosis (RO) desalination plant. The values of net present cost (NPC) and the cost of energy (COE) are $438,657 and $0.117/kWh, respectively. From the authors’ point view, the proposed system is one among the foremost environmentally friendly systems to provide electric energy to the seawater desalination plant, especially when connecting to the utility grid, because it is ready to reduce a large amount of greenhouse gas emissions due to using oil/nature gas in utility generation stations to reduce the effect of global warming.
Evaluating Pre- and Post-Coagulation Configuration of Dissolved Air Flotation Using Response Surface Methodology
Authors: Kweinor Tetteh Emmanuel , Rathilal Sudesh
Published: April 2020

The effects of coagulation-dissolved air flotation (DAF) process configuration was studied on oil refinery wastewater. The configuration was done in two ways: acid-coagulation-DAF (pre-treatment) and acid-DAF-coagulation (post-treatment). Two different cationic and polymeric organic coagulants were employed in this study to compare their treatability performance with the two aforementioned configurations. All the coagulants applied before the DAF were found to be effective, with over 85% more contaminant removal efficiency than their post-treatment. Alum, being the most cost-effective coagulant, was then employed with response surface methodology (RSM) to obtain the optimum conditions. These include a coagulant dosage of 100 mg/L, air saturator pressure of 375 kPa and air–water ratio of 10% vol/vol corresponding to a desirability of 92% for the removal of oily pollutants from a local South Africa oil refinery’s wastewater. With the response quadratic models that were developed, the optimum conditions were tested experimentally, which were consistent with the models predicted results at a 95% confidence level.
Methane Adsorption Interpreting with Adsorption Potential and Its Controlling Factors in Various Rank Coals
Authors: Qiu Feng , Liu Dameng , Cai Yidong , Liu Ning , Qiu Yongkai
Published: April 2020

Water content, metamorphism (coal rank) particle size, and especially pore structure, strongly influence the adsorption capacity of coal to methane. To understand the mechanism of methane adsorption in different rank coals, and its controlling factors, isothermal adsorption experiments with different coal ranks, moisture contents and particle sizes at the temperature of 303.15 K were conducted. In addition, the pore structures of coals were investigated through N2 adsorption/desorption experiments at the low-temperature of 77 K for selected coals from the Junggar Basin of NW China, Qinshui Basin and Ordos Basin of north China. Moreover, the adsorption potential of methane on the surface of the coal matrix was calculated, the controlling factors of which were discussed. The obtained methane isothermal adsorption result shows that the Langmuir volume (VL) of coal is independent of the particle size, and decreases with the increase of moisture content, which decreases first and then increases when the coal rank increases. Combined with the pore structure by the N2 adsorption at 77 K, VL increases with the increase of pore surface area and pore volume of coal pores. Besides, the adsorption potential of all selected coals decreased with the increase of the methane adsorption volume, showing a negative relationship. The interesting phenomena was found that the surface adsorption potential of the coal matrix decreases with the increase of moisture content, and increases with the decrease of particle size at the same pressure. With the same adsorption amount, the adsorption potential on the surface of coal matrix decreases first, and then increases with the increase of coal rank, reaching a minimum at Ro,m of 1.38%, and enlarging with the increase of pore surface area and the pore volume of coal pores. These findings may have significant implications for discovering CBM accumulation areas and enhancing CBM recovery.
Experiments and 3D Molecular Model Construction of Lignite under Different Modification Treatment
Authors: Liu Jihui , Qiu Shuang , He Zhijun , Yu Yaowei
Published: April 2020

In this paper, Huolinhe lignite was selected as the lignite experimental sample, using microwave modification and ultrasonic modification separately as improvement methods. The three-dimensional molecular models of HLH before and after modification were established base on the parameters obtained by 13C NMR, X-ray photoelectron spectroscopy (XPS), Raman spectroscopy (Raman), and Fourier transform infrared (FTIR). After the microwave treatment, the methylene carbon in the HLH coal sample structure mostly exists in the form of long straight chains, and after microwave and ultrasonic treatment, the -OH content of oxygen atoms in the coal sample increases, and form the CO- and the COO-. The proportion is decreasing. The models were adjusted and tested by the covalent bond concentration method and carbon chemical shift spectra calculation using Chemdraw software. A new method is proposed to study the structure and physicochemical properties of lignite modification from the molecular point of view through this study.
A Comparative Study of Virgin Coconut Oil, Coconut Oil and Palm Oil in Terms of Their Active Ingredients
Authors: Suryani Suryani , Sariani Sariani , Earnestly Femi , Marganof Marganof , Rahmawati Rahmawati , Sevindrajuta Sevindrajuta , Mahlia Teuku Meurah Indra , Fudholi Ahmad
Published: April 2020

This research aims to study the unique factors of virgin coconut oil (VCO) compared with coconut oil (i.e., coconut oil processed through heating the coconut milk and palm oil sold on the market). Its novelty is that it (VCO) contains lactic acid bacteria and bacteriocin. Lauric acid content was analyzed by the Chromatographic Gas method. Isolation of lactic acid bacteria (LAB) was conducted by the dilution method using MRSA + 0.5% CaCO3 media. Iodium number, peroxide, and %FFA were analyzed using a general method, and isolation bacteriocin by the deposition method using ammonium sulfate. In addition, macromolecular identification was conducted by 16S rRNA. VCO was distinguished by a higher content of lauric acid (C12:0) 41%–54.5% as compared with 0% coconut and 0, 1% palm oil, respectively. The VCO also contains LAB, namely Lactobacillus plantarum and Lactobacillus paracasei, and can inhibit the growth of pathogenic bacteria, such as Pseudomonas aeruginosa, Klebsiella, Staphylococcus aureus, S. epidermidis, Proteus, Escherichia coli, Listeria monocytogenes, Bacillus cereus, Salmonella typhosa and bacteriocin. Comparison with VCO is based on having a high content of lauric acid, 54%, and LAB content. The difference between VCO and coconut oil and palm oil is fatty acids. In VCO there are lauric acid and stearic acid, namely lauric acid VCO (A) 54.06%, VCO (B) 53.9% and VCO (C) 53.7%. The content of stearic acid VCO (A) is 12.03%, VCO (B) 12.01% and VCO (C) 11.9%. Coconut oil contains a little lauric acid, which is 2.81%, stearic acid 2.65% and palmitic acid 2.31%. Palm oil can be said to have very little lauric acid, namely in palm oil 1, 0.45%, and even in palm oil 2, 0%; in turn, palmitic acid palm oil 1 has 2.88% and palm oil 2 palmitic acid has 24.42%.
Estimation of Biomass Enzymatic Hydrolysis State in Stirred Tank Reactor through Moving Horizon Algorithms with Fixed and Dynamic Fuzzy Weights
Authors: Furlong Vitor B. , Corrêa Luciano J. , Lima Fernando V. , Giordano Roberto C. , Ribeiro Marcelo P. A.
Published: April 2020

Second generation ethanol faces challenges before profitable implementation. Biomass hydrolysis is one of the bottlenecks, especially when this process occurs at high solids loading and with enzymatic catalysts. Under this setting, kinetic modeling and reaction monitoring are hindered due to the conditions of the medium, while increasing the mixing power. An algorithm that addresses these challenges might improve the reactor performance. In this work, a soft sensor that is based on agitation power measurements that uses an Artificial Neural Network (ANN) as an internal model is proposed in order to predict free carbohydrates concentrations. The developed soft sensor is used in a Moving Horizon Estimator (MHE) algorithm to improve the prediction of state variables during biomass hydrolysis. The algorithm is developed and used for batch and fed-batch hydrolysis experimental runs. An alteration of the classical MHE is proposed for improving prediction, using a novel fuzzy rule to alter the filter weights online. This alteration improved the prediction when compared to the original MHE in both training data sets (tracking error decreased 13%) and in test data sets, where the error reduction obtained is 44%.
Experimental Validation of a Cascade Control Strategy for Continuously Perfused Animal Cell Cultures
Authors: Abbate Thomas , Sbarciog Mihaela , Dewasme Laurent , Vande Wouwer Alain
Published: April 2020

This paper is dedicated to the experimental validation of a cascade control strategy for simultaneously regulating the glucose and biomass levels in continuously perfused HEK-293 cell cultures. The inner loop consists of a partial feedback linearization, which requires the estimation of the biomass specific growth rate and glucose uptake rate. This latter task is achieved by sliding mode observers, which do not require a priori process knowledge in the form of a process model. The linearized process is then regulated by the outer loop, including two classical PI controllers with autotuning. The four manipulated variables are a feed flow rate with low glucose concentration, another feed flow with a higher glucose content, a bleed flow, and a perfusion stream. The experimental results demonstrate the ability of the control strategy to reach and regulate the prescribed setpoints. The main advantage of the strategy is that it can be applied in a plug and play manner and shows satisfactory robustness. To the best of our knowledge, this is the first time that such a multivariable control strategy, together with sliding mode observers, is applied at the lab scale to an industrial process in the pharmaceutical sector.
Bioelectrochemical Methane Production from Food Waste in Anaerobic Digestion Using a Carbon-Modified Copper Foam Electrode
Authors: An Zhengkai , Feng Qing , Zhao Rusong , Wang Xiaoli
Published: April 2020

Anaerobic bioelectrochemical digestion (ABD) is widely used for treating wastewater and recovering energy. The electrode is the key point for ABD system, which was sparsely studied with food waste. In this study, a carbon-modified copper foam was fabricated with copper foam and multiple wall carbon nanotubes (MWCNT) through electrophoretic deposition and screen-printing methods. The carbon-modified copper foam electrode was investigated in an ABD reactor for food waste. The features of bioelectrochemical methane production, process stability, and electrochemical characterization were evaluated in the ABD reactor, and were compared to the control reactor without equipping electrode. The ultimate methane production reached 338.1 mL CH4/L in the ABD reactor, which was significantly higher than the 181.0 mL CH4/L of the control reactor. The methane produced from the electrode was 137.8 mL CH4/L, which was up to 40.8% of total methane production in the ABD reactor. It was attributed to the electroactive bacteria that were enriched and activated by the carbon-modified copper foam electrode, further activating the direct interspecies electron transfer (DIET) pathways for methane production. The cyclic voltammetry (CV) analysis showed higher redox peaks, which is one of the pieces of evidence for the enrichment of electroactive bacteria. The carbon-modified copper foam electrode has the advantages of both carbon and metal materials, and demonstrated a high possibility for use in bioelectrochemical methane production for food waste.
Preparation and Characterization of Environmentally Friendly Controlled Release Fertilizers Coated by Leftovers-Based Polymer
Authors: Jia Cong , Lu Panfang , Zhang Min
Published: April 2020

In this work, a novel bio-based polyurethane (PU) was synthesized by using a leftovers (SF)-based polyol and isocyanate for controlled release fertilizers (CRFs). Its chemical structure, surface elemental compositions and distribution were examined by Fourier transform infrared (FTIR), energy dispersive spectroscopy (EDX) and a multifunctional imaging electron spectrometer (XPS). The microstructure morphology of CRFs were examined by SEM. The nutrient release behaviors of CRFs were observed in water. The results demonstrated that SF-based PU-coated urea (FPU) had a denser structure and better nutrient releasing ability. Findings from this work indicated that the use of SF as a coating material of environment-friendly CRFs had great potential, and would hopefully be used for horticultural and agricultural applications.
Simultaneous Adsorption of 4,6-Dimethyldibenzothiophene and Quinoline over Nickel and Boron Modified Gamma-Al2O3 Adsorbent
Authors: Camu Esteban , Pasten Barbara , Matus Camila , Ramirez Fernanda , Ojeda Juan , Aguila Gonzalo , Baeza Patricio
Published: April 2020

The simultaneous adsorption of quinoline and 4,6-dimethyldibenzothiophene over adsorbents, based on alumina modified with boron and nickel under ambient temperature and pressure, was studied. The adsorbents were characterized by BET specific surface area, a potentiometric method for the determination of acid strength, electrophoretic migration, and X-ray diffraction. The results showed that the adsorbent containing nickel had better adsorption capacity than the adsorbent modified with nickel and boron, which was attributed to its greater acidity and ability to generate π-complexation between the adsorbent and the molecules. In terms of selectivity, quinoline was more adsorbed than 4,6-dimethyldibenzothiophene in all systems, due to the basic nature of quinoline. The experimental data in all cases were adjusted by three kinetic models (Yoon–Nelson, Yan and Thomas), and the regression coefficients in all models were close to one. Finally, the values of the kinetic constant obtained by the Thomas model were used to relate the adsorption capacity results.
Early Stage of Corrosion Formation on Pipeline Steel X70 Under Oxyfuel Atmosphere at Low Temperature
Authors: Kratzig Andreas , Quynh Hoa Le , Bettge Dirk , Menneken Martina , Bäßler Ralph
Published: April 2020

The early stage of corrosion formation on X70 pipeline steel under oxyfuel atmosphere was investigated by applying a simulated gas mixture (CO2 containing 6700 ppmv O2, 100 ppmv NO2, 70 ppmv SO2 and 50 ppmv H2O) for 15 h at 278 K and ambient pressure. Short-term tests (6 h) revealed that the corrosion starts as local spots related to grinding marks progressing by time and moisture until a closed layer was formed. Acid droplets (pH 1.5), generated in the gas atmosphere, containing a mixture of H2SO4 and HNO3, were identified as corrosion starters. After 15 h of exposure, corrosion products were mainly X-ray amorphous and only partially crystalline. In-situ energy-dispersive X-ray diffraction (EDXRD) results showed that the crystalline fractions consist primarily of water-bearing iron sulfates. Applying Raman spectroscopy, water-bearing iron nitrates were detected as subordinated phases. Supplementary long-term tests exhibited a significant increase in the crystalline fraction and formation of additional water-bearing iron sulfates. All phases of the corrosion layer were intergrown in a nanocrystalline network. In addition, numerous globular structures have been detected above the corrosion layer, which were identified as hydrated iron sulphate and hematite. As a type of corrosion, shallow pit formation was identified, and the corrosion rate was about 0.1 mma−1. In addition to in-situ EDXRD, SEM/EDS, TEM, Raman spectroscopy and interferometry were used to chemically and microstructurally analyze the corrosion products.
Design and Optimization of Fluidized Bed Reactor Operating Conditions for Struvite Recovery Process from Swine Wastewater
Authors: Shim Soomin , Won Seunggun , Reza Arif , Kim Seungsoo , Ahmed Naveed , Ra Changsix
Published: April 2020

Struvite crystallization using fluidized bed reactors (FBRs) is one of the most commonly used methods for nutrient recovery from different waste streams. However, struvite recovery from swine wastewater containing much higher solids using FBR has not been studied extensively. In this study, we therefore designed and optimized the key operating conditions parameters, i.e., pH (9.0, 9.5, and 10.0), circulation rate (CR) (1.5, 3.0, and 4.5 L/Lreactor·h), and hydraulic retention time (HRT) (1, 3, and 5 h) of FBR to ensure efficient nutrient removal and struvite crystallization from swine wastewater using response surface methodology (RSM) with central composite design (CCD) as experimental design. A magnesium/phosphorus (Mg/P) molar ratio of 1.3 was maintained with MgCl2 according to ortho-phosphate (O-P) concentration of influent and an air diffuser was set to supply air with 0.03 L air/Lreactor·min. The O-P recovery efficiency of over 91% was achieved through the entire runs. Among the operational parameters, pH did not show any significant effect on NH4-N recovery, particle size, and struvite production rate (SPR). The optimal CR over 2.94 L/Lreactor·h was found to be appropriate for efficient removal of nutrients and struvite crystallization. While optimizing the HRT, priority of the process operation such as the production of larger struvite particles or increased struvite productivity should be considered. Therefore, the optimal operational parameters of pH 9.0, CR > 2.94 L/Lreactor·h, and HRT of 1 or 5 h were chosen to obtain better responses through RSM analyses. The findings of this study would be useful in designing and operating either pilot- or full-scale FBR for struvite crystallization from swine wastewater.
Remote Monitoring of Floating Covers Using UAV Photogrammetry
Authors: Wong Leslie , Vien Benjamin Steven , Ma Yue , Kuen Thomas , Courtney Frank , Kodikara Jayantha , Chiu Wing Kong
Published: April 2020

High-density polyethylene (HDPE) is commonly the material of choice for covered anaerobic lagoons (CAL) at wastewater treatment plants. The membrane floats on the wastewater, and hence is called a “floating cover”, and is used for odour control and to harvest the methane-rich biogas as a renewable resource to generate electricity. The floating cover is an expensive and high-value asset that demands an efficient methodology for the determination of a set of engineering quantities for structural integrity assessment. Given the dynamics of the anaerobic activities under the floating cover, the state of deformation of the floating cover is an engineering measurand that is useful for its structural health assessment. A non-contact measurement strategy is preferred as it offers practical and safety-related benefits over other methods. In collaboration with Melbourne Water Corporation (MWC), an unmanned aerial vehicle (UAV) assisted photogrammetry approach was developed to address this need. Following the definition of the appropriate flight parameters required to quantify the state of deformation of the cover, a series of periodic flights were operated over the very large floating covers at MWC’s Western Treatment Plant (WTP) at Werribee, Victoria, Australia. This paper aims to demonstrate the effectiveness and practicality of this inspection technique to determine the state of deformation of the floating covers measured over a ten-month period.
New Downscaling Approach Using ESA CCI SM Products for Obtaining High Resolution Surface Soil Moisture
Authors: Kovačević Jovan , Cvijetinović Željko , Stančić Nikola , Brodić Nenad , Mihajlović Dragan
Published: April 2020

ESA CCI SM products have provided remotely-sensed surface soil moisture (SSM) content with the best spatial and temporal coverage thus far, although its output spatial resolution of 25 km is too coarse for many regional and local applications. The downscaling methodology presented in this paper improves ESA CCI SM spatial resolution to 1 km using two-step approach. The first step is used as a data engineering tool and its output is used as an input for the Random forest model in the second step. In addition to improvements in terms of spatial resolution, the approach also considers the problem of data gaps. The filling of these gaps is the initial step of the procedure, which in the end produces a continuous product in both temporal and spatial domains. The methodology uses combined active and passive ESA CCI SM products in addition to in situ soil moisture observations and the set of auxiliary downscaling predictors. The research tested several variants of Random forest models to determine the best combination of ESA CCI SM products. The conclusion is that synergic use of all ESA CCI SM products together with the auxiliary datasets in the downscaling procedure provides better results than using just one type of ESA CCI SM product alone. The methodology was applied for obtaining SSM maps for the area of California, USA during 2016. The accuracy of tested models was validated using five-fold cross-validation against in situ data and the best variation of model achieved RMSE, R2 and MAE of 0.0518 m3/m3, 0.7312 and 0.0374 m3/m3, respectively. The methodology proved to be useful for generating high-resolution SSM products, although additional improvements are necessary.
Creation of One Excavator as an Obstacle in C-Space for Collision Avoidance during Remote Control of the Two Excavators Using Pose Sensors
Authors: Sun Dongik , Hwang Seunghoon , Kim Byeol , Ahn Yonghan , Lee Joosung , Han Jeakweon
Published: April 2020

Many solutions about the teleoperation of unmanned robotic excavators have been studied continuously. However, if excavators that are remotely controlled were employed, the probability of an accident would be higher. For this reason, there have been many ways proposed to attempt to reduce accidents in these dangerous situations. In this paper, a novel methodology will be introduced with a focus on the multiple excavators themselves. The proposed method details how one excavator can be generated or expressed as an obstacle in the Configuration-Space (C-space) with respect to another excavator’s side for collision avoidance each other. This method is based on kinematics information which is measurable and given. Therefore, this method can be used or applied independently by using widely used pose sensors and wireless communication devices. The phase of mathematical derivation about obstacle sets is described in detail. The results are shown in accompanying figures and tables for demonstrating that the proposed method detected the proximity and found the collision-free zone accurately. The proposed system can be powerful when applied to a teleoperation system, where it would be particularly useful and helpful to the operator.
A 20-Year MODIS-Based Snow Cover Dataset for Svalbard and Its Link to Phenological Timing and Sea Ice Variability
Authors: Vickers Hannah , Karlsen Stein Rune , Malnes Eirik
Published: April 2020

The climate in Svalbard has been warming dramatically compared with the global average for the last few decades. Seasonal snow cover, which is sensitive to temperature and precipitation changes, is therefore expected to undergo both spatial and temporal changes in response to the changing climate in Svalbard. This will in turn have implications for timing of terrestrial productivity, which is closely linked to the disappearance of seasonal snow. We have produced a 20-year snow cover fraction time series for the Svalbard archipelago, derived from MODIS (Moderate Resolution Imaging Spectroradiometer) Terra data to map and identify changes in the timing of the first snow-free day (FSFD) for the period 2000–2019. Moreover, we investigate the influence of sea ice concentration (SIC) variations on FSFD and how FSFD is related to the start of the phenological growing season in Svalbard. Our results revealed clear patterns of earlier FSFD in the southern and central parts of the archipelago, while the northernmost parts exhibit little change or trend toward later FSFD, resulting in weaker trends in summer and winter duration. We found that FSFD preceded the onset of the phenological growing season with an average difference of 12.4 days for the entire archipelago, but with large regional variations that are indicative of temperature dependence. Lastly, we found a significant correlation between variations of time-integrated SIC and variations in FSFD, which maximizes when correlating SIC northeast of Svalbard with FSFD averaged over Nordaustlandet. Prolonged sea ice cover in the spring was correlated with late snow disappearance, while lower-than-average sea ice cover correlated with early snow disappearance, indicating that proximity to sea ice plays an important role in regulating the timing of snow disappearance on land through influencing the regional air temperature and therefore rate of spring snowmelt.
An Improved Res-UNet Model for Tree Species Classification Using Airborne High-Resolution Images
Authors: Cao Kaili , Zhang Xiaoli
Published: April 2020

Tree species classification is important for the management and sustainable development of forest resources. Traditional object-oriented tree species classification methods, such as support vector machines, require manual feature selection and generally low accuracy, whereas deep learning technology can automatically extract image features to achieve end-to-end classification. Therefore, a tree classification method based on deep learning is proposed in this study. This method combines the semantic segmentation network U-Net and the feature extraction network ResNet into an improved Res-UNet network, where the convolutional layer of the U-Net network is represented by the residual unit of ResNet, and linear interpolation is used instead of deconvolution in each upsampling layer. At the output of the network, conditional random fields are used for post-processing. This network model is used to perform classification experiments on airborne orthophotos of Nanning Gaofeng Forest Farm in Guangxi, China. The results are then compared with those of U-Net and ResNet networks. The proposed method exhibits higher classification accuracy with an overall classification accuracy of 87%. Thus, the proposed model can effectively implement forest tree species classification and provide new opportunities for tree species classification in southern China.
A Review of Remote Sensing for Environmental Monitoring in China
Authors: Li Jun , Pei Yanqiu , Zhao Shaohua , Xiao Rulin , Sang Xiao , Zhang Chengye
Published: April 2020

The natural environment is essential for human survival and development since it provides water resources, land resources, biological resources and climate resources etc. As a developing country, China has witnessed a significant change in the natural environment in recent decades; and therefore, monitoring and mastering the status of the environment is of great significance. Due to the characteristics of large-scale and dynamic observation, remote sensing technology has been an indispensable approach for environmental monitoring. This paper reviews the satellite resources, institutions and policies for environmental monitoring in China, and the advances in research and application of remote sensing from five aspects: ecological index retrieval, environmental monitoring in protected areas, rural areas, urban areas and mining areas. The remote sensing models and methods for various types of environmental monitoring, and the specific applications in China are comprehensively summarized. This paper also points out major challenges existing at the current stage: satellite sensor problems, integrated use challenges of datasets, uncertainty in the retrieval process of ecological variables, scaling effect problems, a low degree of automation, the weak ability of forecasting and comprehensive analysis, and a lack of computational power for massive datasets. Finally, the development trend and future directions are put forward to direct the research and application of environmental monitoring and protection in the new era.
Spatially Variable Relationships between Karst Landscape Pattern and Vegetation Activities
Authors: Hou Wenjuan , Gao Jiangbo
Published: April 2020

Based on the theories of structure–function correlation in Geography, and landscape pattern-ecological function correlation in Landscape Ecology, the correlation between land use fragmentation and vegetation activity was quantified. Effective mesh size (meff) was calculated to represent landscape fragmentation for land use, and the normalized difference vegetation index (NDVI) was used to reflect vegetation activity. The geographically weighted regression (GWR) model was applied to explore the spatial non-stationary relationship between meff and NDVI in a karst basin of the southwestern China, where environmental factors (i.e., climate, topography, and vegetation) are spatially heterogeneous. The spatial variation and scale dependence of landscape fragmentation and its relationship with vegetation activity, as well as the influence of lithology types and landforms relief, were considered. Firstly, the optimal ‘slide window’ size for landscape fragmentation was determined to be 500 m, and spatial pattern of meff displayed clear heterogeneity with a serious degree of fragmentation. Landscape fragmentation was more severe in carbonate areas than non-carbonate areas, reflecting the influence of landforms relief. More serious fragmentation in dolomite areas meant that the impact of human activities on the landscape morphological characteristics was much more significant than that in the limestone areas with steeper slope. Multi-scale analysis was used to verify a neighborhood size of 7 km for GWR in the study area. Negative effects on vegetation activity from landscape structural changes were more significant in limestone areas, which may be due to the more vulnerable ecosystems there. This research can provide scientific guidance for landscape management in karst regions as it considers the multi-scaled and spatially heterogeneous effects of lithology, geomorphology, and human factors on landscape structure and its correlation with vegetation activity.
Quantifying the Sensitivity of NDVI-Based C Factor Estimation and Potential Soil Erosion Prediction using Spaceborne Earth Observation Data
Authors: Ayalew Dawit A. , Deumlich Detlef , Šarapatka Bořivoj , Doktor Daniel
Published: April 2020

The Normalized Difference Vegetation Index (NDVI), has been increasingly used to capture spatiotemporal variations in cover factor (C) determination for erosion prediction on a larger landscape scale. However, NDVI-based C factor (Cndvi) estimation per se is sensitive to various biophysical variables, such as soil condition, topographic features, and vegetation phenology. As a result, Cndvi often results in incorrect values that affect the quality of soil erosion prediction. The aim of this study is to multi-temporally estimate Cndvi values and compare the values with those of literature values (Clit) in order to quantify discrepancies between C values obtained via NDVI and empirical-based methods. A further aim is to quantify the effect of biophysical variables such as slope shape, erodibility, and crop growth stage variation on Cndvi and soil erosion prediction on an agricultural landscape scale. Multi-temporal Landsat 7, Landsat 8, and Sentinel 2 data, from 2013 to 2016, were used in combination with high resolution agricultural land use data of the Integrated Administrative and Control System, from the Uckermark district of north-eastern Germany. Correlations between Cndvi and Clit improved in data from spring and summer seasons (up to r = 0.93); nonetheless, the Cndvi values were generally higher compared with Clit values. Consequently, modelling erosion using Cndvi resulted in two times higher rates than modelling with Clit. The Cndvi values were found to be sensitive to soil erodibility condition and slope shape of the landscape. Higher erodibility condition was associated with higher Cndvi values. Spring and summer taken images showed significant sensitivity to heterogeneous soil condition. The Cndvi estimation also showed varying sensitivity to slope shape variation; values on convex-shaped slopes were higher compared with flat slopes. Quantifying the sensitivity of Cndvi values to biophysical variables may help improve capturing spatiotemporal variability of C factor values in similar landscapes and conditions.
Spatially Quantifying Forest Loss at Landscape-scale Following a Major Storm Event
Authors: St. Peter Joseph , Anderson Chad , Drake Jason , Medley Paul
Published: April 2020

Large scale forest disturbances are becoming more frequent across the world, and remote sensing must play a role in informing and prioritizing immediate, short-term and long-term disaster response and recovery. However, such evaluations from remote sensing are currently limited (e.g., burned area severity and change NDVI) and do not always explicitly relate to change in resources of interest. Herein we demonstrate a novel method to predict basal area loss, validated by independent field evaluations. Hurricane Michael made landfall on Mexico Beach in the Florida panhandle as a Category 5 storm on October 10th, 2018. The storm affected roughly 2 million hectares of largely forested land in the area. In this study, we use Sentinel-2 imagery and 248 forest plots collected prior to landfall in 2018 in the forests impacted by Hurricane Michael to build a general linear model of tree basal area across the landscape. The basal area model was constrained to areas where trees were present using a tree presence model as a hurdle. We informed the model with post-hurricane Sentinel-2 imagery and compared the pre- and post- hurricane basal area maps to assess the loss of basal area following the hurricane. The basal area model had an r-squared value of 0.508. Plots were revisited to ground truth the modelled results; this showed that the model performed well at categorizing forest hurricane damage. Our results validate a novel method to create a landscape scale spatial dataset showing the location and intensity of basal area loss at 10-m spatial resolution which can be used for quantifying forest disturbances worldwide.
An Auto-Tuning Continuous-Time Bandpass Sigma-Delta Modulator with Signal Observation for MEMS Gyroscope Readout Systems
Authors: Ju Chunge , Li Xiang , Zou Junjun , Wei Qi , Zhou Bin , Zhang Rong
Published: April 2020

This paper presents the design and implementation of an auto-tuning continuous-time bandpass sigma-delta (ΣΔ) modulator for micro-electromechchanical systems (MEMS) gyroscope readout systems. Its notch frequency can well match the input signal frequency by adding a signal observation to the traditional ΣΔ modulator. The filter of the observation adopts the same architecture as that of the traditional ΣΔ modulator, allowing the two filters to have the same response to input signal change, which is converted into a control voltage on metal-oxide semiconductor (MOS) resistance in the filters. The automatic tuning not only works to solve the mismatch problem caused by process error and temperature variation, but can also be applied to the interface circuit of gyroscopes with different resonant frequencies. The circuit is implemented in a 0.18-μm complementary metal-oxide semiconductor (CMOS) process with a core area of 2.4 mm2. The improved modulator achieves a dynamic range of 106 dB, a noise floor below 120 dB and a maximum signal-to-noise and distortion ratio (SNDR) of 86.4 dB. The tuning capability of the chip is relatively stable under input signals from 6 to 15 kHz at temperatures ranging from −45 to 60 °C.
A Compact Convolutional Neural Network for Surface Defect Inspection
Authors: Huang Yibin , Qiu Congying , Wang Xiaonan , Wang Shijun , Yuan Kui
Published: April 2020

The advent of convolutional neural networks (CNNs) has accelerated the progress of computer vision from many aspects. However, the majority of the existing CNNs heavily rely on expensive GPUs (graphics processing units). to support large computations. Therefore, CNNs have not been widely used to inspect surface defects in the manufacturing field yet. In this paper, we develop a compact CNN-based model that not only achieves high performance on tiny defect inspection but can be run on low-frequency CPUs (central processing units). Our model consists of a light-weight (LW) bottleneck and a decoder. By a pyramid of lightweight kernels, the LW bottleneck provides rich features with less computational cost. The decoder is also built in a lightweight way, which consists of an atrous spatial pyramid pooling (ASPP) and depthwise separable convolution layers. These lightweight designs reduce the redundant weights and computation greatly. We train our models on groups of surface datasets. The model can successfully classify/segment surface defects with an Intel i3-4010U CPU within 30 ms. Our model obtains similar accuracy with MobileNetV2 while only has less than its 1/3 FLOPs (floating-point operations per second) and 1/8 weights. Our experiments indicate CNNs can be compact and hardware-friendly for future applications in the automated surface inspection (ASI).
Portable Ultrasound-Based Device for Detecting Older Adults’ Sit-to-Stand Transitions in Unsupervised 30-Second Chair–Stand Tests
Authors: Cobo Antonio , Villalba-Mora Elena , Hayn Dieter , Ferre Xavier , Pérez-Rodríguez Rodrigo , Sánchez-Sánchez Alberto , Bernabé-Espiga Raquel , Sánchez-Sánchez Juan-Luis , López-Diez-Picazo Andrea , Moral Cristian , Rodriguez-Mañas Leocadio
Published: April 2020

Lower-limb strength is a marker of functional decline in elders. This work studies the feasibility of using the quasi-periodic nature of the distance between a subjects’ back and the chair backrest during a 30-s chair–stand test (CST) to carry out unsupervised measurements based on readings from a low-cost ultrasound sensor. The device comprises an ultrasound sensor, an Arduino UNO board, and a Bluetooth module. Sit-to-stand transitions are identified by filtering the signal with a moving minimum filter and comparing the output to an adaptive threshold. An inter-rater reliability (IRR) study was carried out to validate the device ability to count the same number of valid transitions as the gold-standard manual count. A group of elders (age: mean (m) = 80.79 years old, SD = 5.38; gender: 21 female and seven male) were asked to perform a 30-s CST using the device while a trained nurse manually counted valid transitions. Ultimately, a moving minimum filter was necessary to cancel the effect of outliers, likely produced because older people tend to produce more motion artefacts and, thus, noisier signals. While the intra-class correlation coefficient (ICC) for this study was good (ICC = 0.86, 95% confidence interval (CI) = 0.73, 0.93), it is not yet clear whether the results are sufficient to support clinical decision-making.
An Effective Simulation Analysis of Transient Electromagnetic Multiple Faults
Authors: Dong Liang , Zhang Hongxin , Sun Shaofei , Zhu Lei , Cui Xiaotong , Ghosh Bablu K.
Published: April 2020

Embedded encryption devices and smart sensors are vulnerable to physical attacks. Due to the continuous shrinking of chip size, laser injection, particle radiation and electromagnetic transient injection are possible methods that introduce transient multiple faults. In the fault analysis stage, the adversary is unclear about the actual number of faults injected. Typically, the single-nibble fault analysis encounters difficulties. Therefore, in this paper, we propose novel ciphertext-only impossible differentials that can analyze the number of random faults to six nibbles. We use the impossible differentials to exclude the secret key that definitely does not exist, and then gradually obtain the unique secret key through inverse difference equations. Using software simulation, we conducted 32,000 random multiple fault attacks on Midori. The experiments were carried out to verify the theoretical model of multiple fault attacks. We obtain the relationship between fault injection and information content. To reduce the number of fault attacks, we further optimized the fault attack method. The secret key can be obtained at least 11 times. The proposed ciphertext-only impossible differential analysis provides an effective method for random multiple faults analysis, which would be helpful for improving the security of block ciphers.
Communication Aspects of Visible Light Positioning (VLP) Systems Using a Quadrature Angular Diversity Aperture (QADA) Receiver
Authors: Mohammed Mohammed M. A. , He Cuiwei , Cincotta Stefanie , Neild Adrian , Armstrong Jean
Published: April 2020

Visible light positioning (VLP) is a promising indoor localization system in which light emitting diode (LED) luminaires are used as positioning beacons. Data communication is an essential aspect of any VLP system, as each luminaire must transmit information about its own location to the receiver. The quadrature angular diversity aperture (QADA) is a new receiver designed specifically for VLP systems using angle-of-arrival estimation. Previous QADA research has focused only on positioning and assumed error-free communication. In this paper, we investigate, via simulations and experiment, the actual communication characteristics of a VLP system that uses a QADA receiver. We calculate the signal-to-noise ratio and bit-error-rates for a range of scenarios and demonstrate the impact of the dimensions of the receiver. We show that reliable communication is assured in typical operating scenarios, proving that communication will not be a limiting factor when using QADA in VLP systems.
Multi-Scale Spatio-Temporal Feature Extraction and Depth Estimation from Sequences by Ordinal Classification
Authors: Liu Yang
Published: April 2020

Depth estimation is a key problem in 3D computer vision and has a wide variety of applications. In this paper we explore whether deep learning network can predict depth map accurately by learning multi-scale spatio-temporal features from sequences and recasting the depth estimation from a regression task to an ordinal classification task. We design an encoder-decoder network with several multi-scale strategies to improve its performance and extract spatio-temporal features with ConvLSTM. The results of our experiments show that the proposed method has an improvement of almost 10% in error metrics and up to 2% in accuracy metrics. The results also tell us that extracting spatio-temporal features can dramatically improve the performance in depth estimation task. We consider to extend this work to a self-supervised manner to get rid of the dependence on large-scale labeled data.
Seismic Model Parameter Optimization for Building Structures
Authors: Károly Lengyel , Stan Ovidiu , Miclea Liviu
Published: April 2020

Structural dynamic modeling is a key element in the analysis of building behavior for different environmental factors. Having this in mind, the authors propose a simple nonlinear model for studying the behavior of buildings in the case of earthquakes. Structural analysis is a key component of seismic design and evaluation. It began more than 100 years ago when seismic regulations adopted static analyzes with lateral loads of about 10% of the weight of the structure. Due to the dynamics and non-linear response of the structures, advanced analytical procedures were implemented over time. The authors’ approach is the following: having a nonlinear dynamic model (in this case, a multi-segment inverted pendulum on a cart with mass-spring-damper rotational joints) and at least two datasets of a building, the parameters of the building’s model are estimated using optimization algorithms: Particle Swarm Optimization (PSO) and Differential Evolution (DE). Not having much expertise on structural modeling, the present paper is focused on two aspects: the proposed model’s performance and the optimization algorithms performance. Results show that among these algorithms, the DE algorithm outperformed its counterpart in most situations. As for the model, the results show us that it performs well in prediction scenarios.