bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Alkyl Chain Length in POSS Nanocage on Non-Isothermal Crystallization Behavior of PCL/Amino-POSS Nanocomposites
Authors: Fernández M. Dolores , Guzmán Dailyn J. , Ramos Johnny R. , Fernández M. Jesús
Published: October 2019

The study of the non-isothermal crystallization behavior of polymers is of great importance due to the effect of degree of crystallinity and crystallization process on the polymer properties. The effect of aminopropylisobutyl polyhedral oligomeric silsesquioxane (APIBPOSS) and aminopropylisooctyl polyhedral oligomeric silsesquioxane (APIOPOSS) on poly(ε-caprolactone) (PCL) crystallization is studied by differential scanning calorimetry (DSC) under non-isothermal conditions and polarized optical microscopy (POM). The crystallization kinetics is analyzed using the Avrami and Mo models, and effective activation energies are evaluated by the Friedman isoconversional method. The results show that the compatibility between polyhedral oligomeric silsesquioxanes (POSS) and PCL and POSS loading affect the crystallization process. A higher crystallization temperature, a narrower size distribution of crystallite, and a faster crystallization rate are obtained in the presence of all the studied contents of APIBPOSS and at lower contents of APIOPOSS. At APIOPOSS contents higher than 2 wt %, the crystallization temperature is lowered, the size distribution of crystallite is broadened, and the crystallization process is retarded. The presence of POSS leads to an increase in the number of nucleation sites, and a reduction in the size of the crystallite and the overall degree of crystallinity, as a result of the confinement of PCL chains caused by POSS nanoparticles.
Modeling the Stiffness of Coupled and Uncoupled Recycled Cotton Fibers Reinforced Polypropylene Composites
Authors: Serra Albert , Tarrés Quim , Chamorro Miquel-Àngel , Soler Jordi , Mutjé Pere , Espinach Francesc X. , Vilaseca Fabiola
Published: October 2019

The stiffness of a composite material is mainly affected by the nature of its phases and its contents, the dispersion of the reinforcement, as well as the morphology and mean orientation of such reinforcement. In this paper, recovered dyed cotton fibers from textile industry were used as reinforcement for a polypropylene matrix. The specific dye seems to decrease the hydrophilicity of the fibers and to increase its chemical compatibility with the matrix. The results showed a linear evolution of the Young’s moduli of the composites against the reinforcement contents, although the slope of the regression line was found to be lower than that for other natural strand reinforced polypropylene composites. This was blamed on a growing difficulty to disperse the reinforcements when its content increased. The micromechanics analysis returned a value for the intrinsic Young’s modulus of the cotton fibers that doubled previously published values. The use of two different micromechanics models allowed evaluating the impact of the morphology of the fibers on the Young’s modulus of a composite.
Surface Modification of PET Fiber with Hybrid Coating and Its Effect on the Properties of PP Composites
Authors: Mao Yapeng , Li Qiuying , Wu Chifei
Published: October 2019

Surface modification fundamentally influences the morphology of polyethylene terephthalate (PET) fibers produced from abandoned polyester textiles and improve the compatibility between the fiber and the matrix. In this study, PET fiber was modified through solution dip-coating using a novel synthesized tetraethyl orthosilicate (TEOS)/KH550/ polypropylene (PP)-g-MAH (MPP) hybrid (TMPP). The PET fiber with TMPP modifier was exposed to the air. SiO2 particles would be hydrolyzed from TEOS and become the crystalline cores of MPP. Then, the membrane formed by MPP, SiO2 and KH550 covered the surface of the PET fiber. TMPP powder was investigated and characterized by fourier transform infrared spectroscopy, scanning electron microscope (SEM) and thermogravimetric analysis (TGA). TMPP-modified PET fiber was researched by X-ray diffraction and SEM. Furthermore, tensile strength of single fiber was also tested. PET fiber/PP composites were studied through dynamic mechanical analysis and SEM. Flexural properties of composites were also measured. The interfacial properties of PET fiber and PP matrix were indirectly represented by contact angle analysis. Results showed that the addition of TEOS is helpful in homogenizing the distribution of PP-g-MAH. Furthermore, TMPP generates an organic-inorganic ‘armor’ structure on PET fiber, which can make up for the damage areas on the surface of PET fiber and strengthen each single-fiber by 14.4%. Besides, bending strength and modulus of TMPP-modified PET fiber-reinforced PP composite respectively, increase by 10 and 800 MPa. The compatibility between PET fiber and PP was also confirmed to be increased by TMPP. Predictably, this work supplied a new way for PET fiber modification and exploited its potential applications in composites.
Energetic Analysis of Different Configurations of Power Plants Connected to Liquid Chemical Looping Gasification
Authors: Sarafraz Mohammad , Safaei Mohammad , Leon Arturo , Khaled Usama , Goodarzi Marjan , Meer Rashed
Published: October 2019

In this article, a thermodynamic study was conducted on the energetic and exergy performance of a new configuration of liquid chemical looping gasification (LCLG) plant integrated with a power block to assess the overall performance of the system including exergy partitioned in syngas and first law efficiency (FLE). LCLG is a relatively new concept for the production of high-quality synthetic gas from solid feedstock such as biomass. As the temperature and pressure of the looping system are high, there is thermodynamic potential to co-produce chemical products, power and heat. Hence, in the present work, three different configurations of a power cycle were thermodynamically assessed. In the first proposed power cycle, the produced syngas from the gasifier was combusted in a combustion chamber and the exhausted gases were fed into a gas turbine. In the second and third proposed power cycles, the hot air was directly fed into a gas turbine or was used to produce steam for the steam turbine combined cycle. The processes were simulated with Aspen Plus and Outotec HSC chemistry software packages. The influence of different operating parameters including temperature and pressure of the air reactor and type of oxygen carrier on the first law and exergy efficiency (exergy partitioned in synthetic gas) was assessed. Results showed that the FLE for the proposed gas turbine and steam turbine combined cycles was ~33% to 35%, which is within the range of the efficiency obtained for the state-of-the-art power cycles reported in the literature. Results also showed that lead oxide was a suitable oxygen carrier for the LCLG system, which can be integrated into a steam turbine combined cycle with an FLE of 0.45, while copper oxide showed an FLE of 0.43 for the gas turbine combined cycle.
Effects of a Dynamic Injection Flow Rate on Slug Generation in a Cross-Junction Square Microchannel
Authors: Qian Jin-yuan , Chen Min-rui , Wu Zan , Jin Zhi-jiang , Sunden Bengt
Published: October 2019

The injection flow rates of two liquid phases play a decisive role in the slug generation of the liquid-liquid slug flow. However, most injection flow rates so far have been constant. In order to investigate the effects of dynamic injection flow rates on the slug generation, including the slug size, separation distance and slug generation cycle time, a transient numerical model of a cross-junction square microchannel is established. The Volume of Fluid method is adopted to simulate the interface between two phases, i.e., butanol and water. The model is validated by experiments at a constant injection flow rate. Three different types of dynamic injection flow rates are applied for butanol, which are triangle, rectangular and sine wave flow rates. The dynamic injection flow rate cycles, which are related to the constant slug generation cycle time t0, are investigated. Results show that when the cycle of the disperse phase flow rate is larger than t0, the slug generation changes periodically, and the period is influenced by the cycle of the disperse phase flow rate. Among the three kinds of dynamic disperse flow rate, the rectangular wave influences the slug size most significantly, while the triangle wave influences the separation distance and the slug generation time more prominently.
A Time-Sequence Simulation Method for Power Unit’s Monthly Energy-Trade Scheduling with Multiple Energy Sources
Authors: Sun Liang , Zhang Qi , Zhang Na , Song Zhuoran , Liu Xinglong , Li Weidong
Published: October 2019

The uncertainty of new energy output from wind power is rarely considered in the monthly energy-trade scheduling. This causes many problems since the new energy penetration level increases. The fairness of the scheduled energy for the power suppliers is difficult to guarantee. Because the actual power system operation is far away from scheduling when the monthly energy-trade schedule is carried out, unnecessary wind curtailment might occur, and even the feasibility of monthly energy-trade schedule might not be guaranteed. This affects the security and reliability of the power system operation. In this paper, a new time-sequence simulation method for the monthly energy-trade scheduling is proposed, which considers the new energy power forecasting characteristic and the computational load problem of hourly energy-trade simulation in the remaining months. The proposed method is based on a segment modelling strategy. The power generation in the scheduling month is optimized hourly, and the energy generation is optimized in the subsequent months on a monthly basis. For the scheduling month, accurate cost function is applied in the objective function, and detailed short-term operation constraints and the new energy forecasting results are considered, which can guarantee the feasibility of the new monthly energy-trade scheduling and lay a solid foundation for daily dispatching. For the subsequent months, since the load forecast accuracy is lower and no wind power forecasting results could be used, the rough cost function is applied, and only monthly constraints are considered. To ensure a balance in the execution progress of each power generating entity, the simulation time-scale is set as the remainder of the months in the study year. The new approach ensures the fairness of power execution progress and improves the new energy consumption level. A case study was used to verify the feasibility and effectiveness of the proposed method, which provides a theoretical reference for the monthly electrical energy-trade scheduling.
Implementation of Circular Economy Principles in Industrial Solid Waste Management: Case Studies from a Developing Economy (Nigeria)
Authors: Ezeudu Obiora B. , Ezeudu Tochukwu S.
Published: October 2019

The existing solid waste management principles are increasingly being replaced with discussions on circular economy (CE) principles in contemporary deliberations on solid waste handling. This shift is supported by the global adoption of the concept of sustainable development. The CE offers better prospects to solid waste management and has been implemented successfully in its full theory, practice, and policies in some developed locations of the world. The socio-economic disadvantages, insufficient expert knowledge and a lack of information have hindered its appropriateness and implementation in low and middle-income countries. Hence, the current research study examines the challenges and opportunities of implementing the circularity principle at the industrial sector level of a typical developing economy—Nigeria. Four different industries were selected for this case study—telecommunications, water packaging, pulp and paper and the food industry. These industries represent the major waste streams in an urban solid waste mix (waste electrical and electronic equipment (WEEE), plastic, paper and organic). This study discovered several barriers and existing pre-conditions in place that could either foster or militate against the smooth and successful application of a CE model as a simple modification of the generic model. This study also discussed future directions on the implementation of the model.
Particle Size Distribution in Municipal Solid Waste Pre-Treated for Bioprocessing
Authors: Zhang Yue , Kusch-Brandt Sigrid , Gu Shiyan , Heaven Sonia
Published: October 2019

While it is well known that particle size reduction impacts the performance of bioprocessing such as anaerobic digestion or composting, there is a relative lack of knowledge about particle size distribution (PSD) in pre-treated organic material, i.e., the distribution of particles across different size ranges. PSD in municipal solid waste (MSW) pre-treated for bioprocessing in mechanical–biological treatment (MBT) was researched. In the first part of this study, the PSD in pre-treated waste at two full-scale MBT plants in the UK was determined. The main part of the study consisted of experimental trials to reduce particle sizes in MSW destined for bioprocessing and to explore the obtained PSD patterns. Shredders and a macerating grinder were used. For shear shredders, a jaw opening of 20 mm was found favourable for effective reduction of particle sizes, while a smaller jaw opening rather compressed the wet organic waste into balls. Setting the shredder jaw opening to 20 mm does not mean that in the output all particles will be 20 mm or below. PSD profiles revealed that different particle sizes were present in each trial. Using different types of equipment in series was effective in reducing the presence of larger particles. Maceration yielded a PSD dominated by very fine particles, which is unsuitable for composting and potentially also for anaerobic digestion. It was concluded that shredding, where equipment is well selected, is effective in delivering a material well suited for anaerobic digestion or composting.
Crop Yield Estimation Using Time-Series MODIS Data and the Effects of Cropland Masks in Ontario, Canada
Authors: Liu Jiangui , Shang Jiali , Qian Budong , Huffman Ted , Zhang Yinsuo , Dong Taifeng , Jing Qi , Martin Tim
Published: October 2019

This study investigated the estimation of grain yields of three major annual crops in Ontario (corn, soybean, and winter wheat) using MODIS reflectance data extracted with a general cropland mask and crop-specific masks. Time-series two-band enhanced vegetation index (EVI2) was derived from the 8 day composite 250 m MODIS reflectance data from 2003 to 2016. Using a general cropland mask, the strongest positive linear correlation between crop yields and EVI2 was observed at the end of July to early August, whereas a negative correlation was observed in spring. Using crop-specific masks, the time of the strongest positive linear correlation for winter wheat was found between mid-May and early June, corresponding to peak growth stages of the crop. EVI2 derived at peak growth stages of a crop provided good predictive capability for grain yield estimation, with considerable inter-annual variation. A multiple linear regression model was established for county-level yield estimation using EVI2 at peak growth stages and the year as independent variables. The model accounted for the spatiotemporal variability of grain yields of about 30% and 47% for winter wheat, 63% and 65% for corn, and 59% and 64% for soybean using the general cropland mask and crop-specific masks, respectively. A negative correlation during the spring indicated that vegetation index extracted using a general cropland mask should be used with caution in regions with mixed crops, as factors other than the growth conditions of the targeted crops may also be captured by remote sensing data.
Morphological Characteristics of Tidal Creeks in the Central Coastal Region of Jiangsu, China, Using LiDAR
Authors: Zhao Bingxue , Liu Yongxue , Xu Wenxuan , Liu Yongchao , Sun Jiaqi , Wang Lei
Published: October 2019

Tidal creeks are an important component of the intertidal zone and are essential for maintaining the balance between sedimentary processes and the hydrodynamic environment. A quantitative analysis of the morphological characteristics of tidal creeks is essential for understanding their processes of evolution and to evaluate the stability of tidal flats. This study describes the morphological characteristics of tidal creeks using a high-resolution airborne LiDAR DEM. The parameters include the number, order, length, width, depth, and width/depth ratio. The results show that the number and degree of development tidal creeks along the central coast of Jiangsu are higher than those in the radial sandbanks, and the mean width and length increase with the increasing tidal creek order. The number, length, and depth of tidal creeks in the salt marsh zone with well-developed vegetation are higher than those areas with little vegetation cover. The number of tidal creeks in the mid-upper intertidal zone is the largest, while the length and width of tidal creeks in the lower intertidal zone are the greatest. The differences in these characteristics are mainly related to the vegetation distribution, tidal flat width, and hydrodynamic conditions. Our findings potentially provide guidelines for coastal management and the evaluation of tidal flat stability.
Mitigation of Radio Frequency Interference in Synthetic Aperture Radar Data: Current Status and Future Trends
Authors: Tao Mingliang , Su Jia , Huang Yan , Wang Ling
Published: October 2019

Radio frequency interference (RFI) is a major issue in accurate remote sensing by a synthetic aperture radar (SAR) system, which poses a great hindrance to raw data collection, image formation, and subsequent interpretation process. This paper provides a comprehensive study of the RFI mitigation techniques applicable for an SAR system. From the view of spectrum allocation, possible terrestrial and spaceborne RFI sources to SAR system and their geometry are analyzed. Typical signal models for various RFI types are provided, together with many illustrative examples from real measured data. Then, advanced signal processing techniques for removing RFI are reviewed. Advantages and drawbacks of each approach are discussed in terms of their applicability. Discussion on the future trends are provided from the perspective of cognitive, integrated, and adaptive. This review serves as a reference for future work on the implementation of the most suitable RFI mitigation scheme for an air-borne or space-borne SAR system.
Semi-Automated Data Analysis for Ion-Selective Electrodes and Arrays Using the R Package ISEtools
Authors: Dillingham Peter W. , Alsaedi Basim S.O. , Radu Aleksandar , McGraw Christina M.
Published: October 2019

A new software package, ISEtools, is introduced for use within the popular open-source programming language R that allows Bayesian statistical data analysis techniques to be implemented in a straightforward manner. Incorporating all collected data simultaneously, this Bayesian approach naturally accommodates sensor arrays and provides improved limit of detection estimates, including providing appropriate uncertainty estimates. Utilising >1500 lines of code, ISEtools provides a set of three core functions—loadISEdata, describeISE, and analyseISE— for analysing ion-selective electrode data using the Nikolskii–Eisenman equation. The functions call, fit, and extract results from Bayesian models, automatically determining data structures, applying appropriate models, and returning results in an easily interpretable manner and with publication-ready figures. Importantly, while advanced statistical and computationally intensive methods are employed, the functions are designed to be accessible to non-specialists. Here we describe basic features of the package, demonstrated through a worked environmental application.
Outdoor Scene Understanding Based on Multi-Scale PBA Image Features and Point Cloud Features
Authors: Liu Yisha , Gu Yufeng , Yan Fei , Zhuang Yan
Published: October 2019

Outdoor scene understanding based on the results of point cloud classification plays an important role in mobile robots and autonomous vehicles equipped with a light detection and ranging (LiDAR) system. In this paper, a novel model named Panoramic Bearing Angle (PBA) images is proposed which is generated from 3D point clouds. In a PBA model, laser point clouds are projected onto the spherical surface to establish the correspondence relationship between the laser ranging point and the image pixels, and then we use the relative location relationship of the laser point in the 3D space to calculate the gray value of the corresponding pixel. To extract robust features from 3D laser point clouds, both image pyramid model and point cloud pyramid model are utilized to extract multiple-scale features from PBA images and original point clouds, respectively. A Random Forest classifier is used to accomplish feature screening on extracted high-dimensional features to obtain the initial classification results. Moreover, reclassification is carried out to correct the misclassification points by remapping the classification results into the PBA images and using superpixel segmentation, which makes full use of the contextual information between laser points. Within each superpixel block, the reclassification is carried out again based on the results of the initial classification results, so as to correct some misclassification points and improve the classification accuracy. Two datasets published by ETH Zurich and MINES ParisTech are used to test the classification performance, and the results show the precision and recall rate of the proposed algorithms.
Efficient Parameter Estimation for Sparse SAR Imaging Based on Complex Image and Azimuth-Range Decouple
Authors: Liu Mingqian , Zhang Bingchen , Xu Zhongqiu , Wu Yirong
Published: October 2019

Sparse signal processing theory has been applied to synthetic aperture radar (SAR) imaging. In compressive sensing (CS), the sparsity is usually considered as a known parameter. However, it is unknown practically. For many functions of CS, we need to know this parameter. Therefore, the estimation of sparsity is crucial for sparse SAR imaging. The sparsity is determined by the size of regularization parameter. Several methods have been presented for automatically estimating the regularization parameter, and have been applied to sparse SAR imaging. However, these methods are deduced based on an observation matrix, which will entail huge computational and memory costs. In this paper, to enhance the computational efficiency, an efficient adaptive parameter estimation method for sparse SAR imaging is proposed. The complex image-based sparse SAR imaging method only considers the threshold operation of the complex image, which can reduce the computational costs significantly. By utilizing this feature, the parameter is pre-estimated based on a complex image. In order to estimate the sparsity accurately, adaptive parameter estimation is then processed in the raw data domain, combining with the pre-estimated parameter and azimuth-range decouple operators. The proposed method can reduce the computational complexity from a quadratic square order to a linear logarithm order, which can be used in the large-scale scene. Simulated and Gaofen-3 SAR data processing results demonstrate the validity of the proposed method.
Assessing Older Adults’ Daily Mobility: A Comparison of GPS-Derived and Self-Reported Mobility Indicators
Authors: Fillekes Michelle Pasquale , Kim Eun-Kyeong , Trumpf Rieke , Zijlstra Wiebren , Giannouli Eleftheria , Weibel Robert
Published: October 2019

Interest in global positioning system (GPS)-based mobility assessment for health and aging research is growing, and with it the demand for validated GPS-based mobility indicators. Time out of home (TOH) and number of activity locations (#ALs) are two indicators that are often derived from GPS data, despite lacking consensus regarding thresholds to be used to extract those as well as limited knowledge about their validity. Using 7 days of GPS and diary data of 35 older adults, we make the following three main contributions. First, we perform a sensitivity analysis to investigate how using spatial and temporal thresholds to compute TOH and #ALs affects the agreement between self-reported and GPS-based indicators. Second, we show how daily self-reported and GPS-derived mobility indicators are compared. Third, we explore whether the type and duration of self-reported activity events are related to the degree of correspondence between reported and GPS event. Highest indicator agreement was found for temporal interpolation (Tmax) of up to 5 h for both indicators, a radius (Dmax) to delineate home between 100 and 200 m for TOH, and for #ALs a spatial extent (Dmax) between 125 and 200 m, and temporal extent (Tmin) between 5 and 6 min to define an activity location. High agreement between self-reported and GPS-based indicators is obtained for TOH and moderate agreement for #ALs. While reported event type and duration impact on whether a reported event has a matching GPS event, indoor and outdoor events are detected at equal proportions. This work will help future studies to choose optimal threshold settings and will provide knowledge about the validity of mobility indicators.
Infrared and Visible Image Fusion through Details Preservation
Authors: Liu Yaochen , Dong Lili , Ji Yuanyuan , Xu Wenhai
Published: October 2019

In many actual applications, fused image is essential to contain high-quality details for achieving a comprehensive representation of the real scene. However, existing image fusion methods suffer from loss of details because of the error accumulations of sequential tasks. This paper proposes a novel fusion method to preserve details of infrared and visible images by combining new decomposition, feature extraction, and fusion scheme. For decomposition, different from the most decomposition methods by guided filter, the guidance image contains only the strong edge of the source image but no other interference information so that rich tiny details can be decomposed into the detailed part. Then, according to the different characteristics of infrared and visible detail parts, a rough convolutional neural network (CNN) and a sophisticated CNN are designed so that various features can be fully extracted. To integrate the extracted features, we also present a multi-layer features fusion strategy through discrete cosine transform (DCT), which not only highlights significant features but also enhances details. Moreover, the base parts are fused by weighting method. Finally, the fused image is obtained by adding the fused detail and base part. Different from the general image fusion methods, our method not only retains the target region of source image but also enhances background in the fused image. In addition, compared with state-of-the-art fusion methods, our proposed fusion method has many advantages, including (i) better visual quality of fused-image subjective evaluation, and (ii) better objective assessment for those images.
A New Calibration Circuit Design to Reduce Drift Effect of RuO2 Urea Biosensors
Authors: Kuo Po-Yu , Dong Zhe-Xin
Published: October 2019

The goal of this study was to reduce the drift effect of RuO2 urea biosensors. A new calibration circuit (NCC) based on the voltage regulation technique with the advantage of having a simple structure was presented. To keep its simplicity, the proposed NCC was composed of a non-inverting amplifier and a voltage calibrating circuit. A ruthenium oxide (RuO2) urea biosensor was fabricated to test the calibrating characteristics of the drift rate of the proposed NCC. The experiment performed in this study was divided into two main stages. For the first stage, a sound RuO2 urea biosensor testing environment was set-up. The RuO2 urea sensing film was immersed in the urea solution for 12 h and the response voltage was measured using the voltage-time (V–T) measurement system and the proposed NCC. The results of the first stage showed that the RuO2 urea biosensor has an average sensitivity of 1.860 mV/(mg/dL) and has a linearity of 0.999 which means that the RuO2 urea biosensor had been well fabricated. The second stage of the experiment verified the proposed NCC’s functions, and the results indicated that the proposed NCC reduced the drift rate of RuO2 urea biosensor to 0.02 mV/hr (98.77% reduction).
A Cloud-based Middleware for Self-Adaptive IoT-Collaboration Services
Authors: Park Soojin , Park Sungyong
Published: October 2019

The middleware framework for IoT collaboration services should provide efficient solutions to context awareness and uncertainty issues among multiple collaboration domains. However, existing middleware frameworks are mostly limited to a single system, and developing self-adaptive IoT collaboration services using existing frameworks requires developers to take considerable time and effort. Furthermore, the developed IoT collaboration services are often dependent on a particular domain, which cannot easily be referenced in other domains. This paper proposes a cloud-based middleware framework that provides a set of cloud services for self-adaptive IoT collaboration services. The proposed middleware framework is generic in the sense that it clearly separates domain-dependent components from the layers that leverage existing middleware frameworks. In addition, the proposed framework allows developers to upload domain-dependent components onto the cloud, search for registered components, and launch Virtual Machine (VM) running a new MAPE cycle via a convenient web-based interface. The feasibility of the proposed framework has been shown with a simulation of an IoT collaboration service that traces a criminal suspect. The performance evaluation shows that the proposed middleware framework runs with an overhead of only 6% compared to pure Java-based middleware and is scalable as the number of VMs increases up to 16.
A New Method for Total Fat Detection in Raw Milk Based on Dual Low-Coherence Interferometer
Authors: Gastélum-Barrios Abraham , Soto-Zarazúa Genaro M. , García-Trejo Juan F. , Sierra-Hernandez Juan M. , Jauregui-Vazquez Daniel
Published: October 2019

The present work experimentally demonstrates a multimode fiber optic sensing setup for total fat detection in raw milk samples. The optical fiber arrangement incorporates a low-coherence Fabry–Perot cavity operating in dual response. The system provides a phase modulation for a total fat range from 0.97 to 4.36%. Here, the protein remains constant at ≈3%. The data indicate that maximum sensitivity close to 616 pm/%fat could be achieved at optimal wavelength operation (500 nm). In addition, the system presented a minimal repeatability error measurement of 0.08%, cross-sensitivity between protein and fat of 0.134, and a regression coefficient of r 2 = 0.9763 . A thermal analysis was also performed, which indicate the temperature immunity of the system. The proposed method represents a low-cost alternative to detect minimal fat variations in raw cow milk.
Gas Sensing Properties of Perovskite Decorated Graphene at Room Temperature
Authors: Casanova-Cháfer Juan , García-Aboal Rocío , Atienzar Pedro , Llobet Eduard
Published: October 2019

This paper explores the gas sensing properties of graphene nanolayers decorated with lead halide perovskite (CH3NH3PbBr3) nanocrystals to detect toxic gases such as ammonia (NH3) and nitrogen dioxide (NO2). A chemical-sensitive semiconductor film based on graphene has been achieved, being decorated with CH3NH3PbBr3 perovskite (MAPbBr3) nanocrystals (NCs) synthesized, and characterized by several techniques, such as field emission scanning electron microscopy, transmission electron microscopy and X-ray photoelectron spectroscopy. Reversible responses were obtained towards NO2 and NH3 at room temperature, demonstrating an enhanced sensitivity when the graphene is decorated by MAPbBr3 NCs. Furthermore, the effect of ambient moisture was extensively studied, showing that the use of perovskite NCs in gas sensors can become a promising alternative to other gas sensitive materials, due to the protective character of graphene, resulting from its high hydrophobicity. Besides, a gas sensing mechanism is proposed to understand the effects of MAPbBr3 sensing properties.
Implementation of Sensing and Actuation Capabilities for IoT Devices Using oneM2M Platforms
Authors: Yun Jaeseok , Ahn Il-Yeup , Song JaeSeung , Kim Jaeho
Published: October 2019

In this paper, we present an implementation work of sensing and actuation capabilities for IoT devices using the oneM2M standard-based platforms. We mainly focus on the heterogeneity of the hardware interfaces employed in IoT devices. For IoT devices (i.e., Internet-connected embedded systems) to perform sensing and actuation capabilities in a standardized manner, a well-designed middleware solution will be a crucial part of IoT platform. Accordingly, we propose an oneM2M standard-based IoT platform (called nCube) incorporated with a set of tiny middleware programs (called TAS) responsible for translating sensing values and actuation commands into oneM2M-defined resources accessible in Web-based applications. All the source codes for the oneM2M middleware platform and smartphone application are available for free in the GitHub repositories. The full details on the implementation work and open-source contributions are described.
Special Issue on “Terrestrial Laser Scanning”: Editors’ Notes
Authors: Rosell-Polo Joan R. , Gregorio Eduard , Llorens Jordi
Published: October 2019

In this editorial, we provide an overview of the content of the special issue on “Terrestrial Laser Scanning”. The aim of this Special Issue is to bring together innovative developments and applications of terrestrial laser scanning (TLS), understood in a broad sense. Thus, although most contributions mainly involve the use of laser-based systems, other alternative technologies that also allow for obtaining 3D point clouds for the measurement and the 3D characterization of terrestrial targets, such as photogrammetry, are also considered. The 15 published contributions are mainly focused on the applications of TLS to the following three topics: TLS performance and point cloud processing, applications to civil engineering, and applications to plant characterization.
3D Reconstruction of Slug Flow in Mini-Channels with a Simple and Low-Cost Optical Sensor
Authors: Li Huajun , Jiang Yandan , Ji Haifeng , Liu Guangyu , Yu Shanen
Published: October 2019

The present work provides a new approach for 3D image reconstruction of gas-liquid two-phase flow (GLF) in mini-channels based on a new optical sensor. The sensor consists of a vertical and a horizontal photodiode array. Firstly, with the optical signals obtained by the vertical array, a measurement model developed by Support Vector Regression (SVR) was used to determine the cross-sectional information. The determined information was further used to reconstruct cross-sectional 2D images. Then, the gas velocity was calculated according to the signals obtained by the horizontal array, and the spatial interval of the 2D images was determined. Finally, 3D images were reconstructed by piling up the 2D images. In this work, the cross-sectional gas-liquid interface was considered as circular, and high-speed visualization was utilized to provide the reference values. The image deformation caused by channel wall was also considered. Experiments of slug flow in a channel with an inner diameter of 4.0 mm were carried out. The results verify the feasibility of the proposed 3D reconstruction method. The proposed method has the advantages of simple construct, low cost, and easily multipliable. The reconstructed 3D images can provide detailed and undistorted information of flow structure, which could further improve the measurement accuracy of other important parameters of gas-liquid two-phase flow, such as void fraction, pressure drop, and flow pattern.
Doppler Differential Positioning Technology Using the BDS/GPS Indoor Array Pseudolite System
Authors: Gan Xingli , Yu Baoguo , Huang Lu , Jia Ruicai , Zhang Heng , Sheng Chuanzhen , Fan Guangwei , Wang Boyuan
Published: October 2019

A Global Satellite Navigation System (GNSS) cannot provide normal location services in an indoor environment because the signals are blocked by buildings. The Beidou satellite navigation system (BDS)/GPS indoor array pseudolite system is proposed to overcome the problems of indoor positioning with conventional pseudolite, such as time synchronization, ambiguity resolution and base stations. At the same time, an algorithm for Doppler differential positioning is proposed to improve the indoor positioning accuracy and the positioning coverage of the system, which uses the Doppler difference equation and Known Point Initialization (KPI) to determinate the velocity and position of the receiver. Experiments were conducted to verify the proposed system under different conditions; the average positioning error of the Doppler differential positioning algorithm was 7.86 mm in the kinematic test and 2.9 mm in the static test. The results show that BDS/GPS indoor array pseudolite system has the potential to make indoor positioning achieve sub-centimeter precision. Finally, the positioning error of the proposed algorithm is also analyzed, and the data tests show that the dilution of precision (DOP) and cycle- slips have a significant impact on the indoor positioning accuracy; a cycle-slip of a half-wavelength can cause positioning errors of tens of millimeters. Therefore, the Doppler-aided cycle-slip detection method (DACS) is proposed to detect cycle-slips of one cycle or greater than one, and the carrier phase double difference cycle-slip detection method (CPDD) is used to detect cycle slips of a half-wavelength.
Semi-Automatic Calibration Method for a Bed-Monitoring System Using Infrared Image Depth Sensors
Authors: Komagata Hideki , Kakinuma Erika , Ishikawa Masahiro , Shinoda Kazuma , Kobayashi Naoki
Published: October 2019

With the aging of society, the number of fall accidents has increased in hospitals and care facilities, and some accidents have happened around beds. To help prevent accidents, mats and clip sensors have been used in these facilities but they can be invasive, and their purpose may be misinterpreted. In recent years, research has been conducted using an infrared-image depth sensor as a bed-monitoring system for detecting a patient getting up, exiting the bed, and/or falling; however, some manual calibration was required initially to set up the sensor in each instance. We propose a bed-monitoring system that retains the infrared-image depth sensors but uses semi-automatic rather than manual calibration in each situation where it is applied. Our automated methods robustly calculate the bed region, surrounding floor, sensor location, and attitude, and can recognize the spatial position of the patient even when the sensor is attached but unconstrained. Also, we propose a means to reconfigure the spatial position considering occlusion by parts of the bed and also accounting for the gravity center of the patient’s body. Experimental results of multi-view calibration and motion simulation showed that our methods were effective for recognition of the spatial position of the patient.
Hierarchical Classification of Urban ALS Data by Using Geometry and Intensity Information
Authors: Liu Xiaoqiang , Chen Yanming , Li Shuyi , Cheng Liang , Li Manchun
Published: October 2019

Airborne laser scanning (ALS) can acquire both geometry and intensity information of geo-objects, which is important in mapping a large-scale three-dimensional (3D) urban environment. However, the intensity information recorded by ALS will be changed due to the flight height and atmospheric attenuation, which decreases the robustness of the trained supervised classifier. This paper proposes a hierarchical classification method by separately using geometry and intensity information of urban ALS data. The method uses supervised learning for stable geometry information and unsupervised learning for fluctuating intensity information. The experiment results show that the proposed method can utilize the intensity information effectively, based on three aspects, as below. (1) The proposed method improves the accuracy of classification result by using intensity. (2) When the ALS data to be classified are acquired under the same conditions as the training data, the performance of the proposed method is as good as the supervised learning method. (3) When the ALS data to be classified are acquired under different conditions from the training data, the performance of the proposed method is better than the supervised learning method. Therefore, the classification model derived from the proposed method can be transferred to other ALS data whose intensity is inconsistent with the training data. Furthermore, the proposed method can contribute to the hierarchical use of some other ALS information, such as multi-spectral information.
Heart Rate Variability, Neuromuscular and Perceptual Recovery Following Resistance Training
Authors: Flatt Andrew A. , Globensky Liam , Bass Evan , Sapp Brooke L. , Riemann Bryan L.
Published: October 2019

We quantified associations between changes in heart rate variability (HRV), neuromuscular and perceptual recovery following intense resistance training (RT). Adult males (n = 10) with >1 year RT experience performed six sets to failure with 90% of 10 repetition maximum in the squat, bench press, and pull-down. Changes (∆) from pre- to immediately (IP), 24 and 48 h post-RT were calculated for neuromuscular performance markers (counter-movement jump peak power and mean concentric bench press and squat velocity with load corresponding to 1.0 m∙s−1) and perceived recovery and soreness scales. Post-waking natural logarithm of the root-mean square of successive differences (LnRMSSD) in supine and standing positions were recorded pre-RT (5 day baseline), IP and two mornings post-RT. All parameters worsened at IP (p < 0.05). LnRMSSD measures were not different from baseline by 24 h. Neuromuscular markers were not different from pre-RT by 48 h. Perceptual measures remained suppressed at 48 h. No significant associations among ∆ variables were observed (p = 0.052–0.978). These data show varying timeframes of recovery for HRV, neuromuscular and perceptual markers at the group and individual level. Thus, post-RT recovery testing should be specific and the status of one metric should not be used to infer that of another.
Public Support Agencies for Innovation in Multilevel Governance Systems: Exploring the Existence of Signs of Complementarity and Substitution
Authors: González-Blanco Jennifer , Vila-Alonso Mercedes , Guisado-González Manuel
Published: October 2019

The aim of this paper is to analyze the existence of indications of complementarity/substitutability between the innovation agencies operating in Spain (regional, national, European, and Seventh Framework Programme), which will allow us to determine the corresponding asymmetries in the implementation of the so-called subsidiarity principle. The data used in the study come from the Panel de Innovación Tecnológica 2015 and 2016 (Spain). The empirical analysis has been carried out by the so-called adoption approach, having previously corrected the selection biases that may be present in the sample. The results obtained indicate that there are indications of substitution between the two Spanish agencies (regional and national), while other relationships between agencies exhibit indications of complementarity. These indications of complementarity/substitutability show that the implementation of the principle of subsidiarity between the two Spanish agencies seem to work correctly, while this implementation is much more diffuse between the two Spanish agencies and the two European agencies. Therefore, these results reveal that there is an obvious asymmetry in the implementation of the principle of subsidiarity between the different agencies. These findings may be an important guide in the decision making of managers. Knowing which agencies are substitutes and which are complementary is extremely relevant information, since it allows the advance determination of which combinations of agencies should be avoided. It also provides policy makers with relevant information for the design of more efficient innovation promotion policies. Finally, this research uses a new methodology for the evaluation of the interaction that takes place between the different public agencies for the promotion of innovation, thus contributing to policy analysts and academics, who conduct such evaluations, have at their disposal a new tool for analysis.
Sustainable Improvement of the Crack Resistance of Cohesive Soils
Authors: Izzo Michael Z. , Miletić Marta
Published: October 2019

Desiccation cracking of cohesive soils is the development of cracks on the soil surface as a result of a reduction in the soil moisture content. The decrease in soil surface area owing to the desiccation of cohesive soils has an undesirable impact on the mechanical, hydrological, thermal, and physico-chemical properties. Many efforts have been made to improve the desiccation crack resistance of cohesive soils, but the current solutions raise a number of environmental issues, increasing the demand for sustainable soil improvement alternatives. Therefore, the main objective of this study is to investigate novel eco-friendly soil improvement techniques, such as recycled carpet fibers and a gelatin-based bioplastic, and their effect on desiccation cracking in cohesive soils. The improvement of soil crack resistance was studied by conducting desiccation cracking tests on plain and improved soils. In addition, image processing was conducted to quantitatively describe the effect of soil improvement type on the geometrical characteristics of crack patterns. Each soil improvement technique enhanced the soil strength and reduced cracking at room temperature, at an elevated temperature, and when subjecting to cyclic wetting and drying. The addition of bioplastics proved to be the most effective solution, thus demonstrating a viable option to advance future sustainable engineering practices.
Corporate Social Responsibility and Sustainable Development for Creating Value for FMCG Sector Enterprises
Authors: Liczmańska-Kopcewicz Katarzyna , Mizera Katarzyna , Pypłacz Paula
Published: October 2019

In recent years, attention has been increasingly paid to social-, environmental-, and ecology-related issues in the areas of diverse business operations. The concept of sustainable development of enterprises is an attempt to integrate a diverse set of requirements for the development of companies in the long-term future. The concept, which is set in a contradictory context of economic, social, and environmental aspects, is an attempt to balance fundamentally divergent requirements and aspirations. Sustainable enterprise development can be a source of competitiveness, provided the opportunities related to it are identified and implemented in a proper way. The research objective of this study is to diagnose the relationship between the company’s orientation towards the implementation of sustainability assumptions, the degree of implementation of the objectives of the corporate social responsibility (CSR) strategy, as well as the creation of value in a sustainable enterprise. The survey was conducted on a sample of 165 FMCG (fast-moving consumer goods) sector enterprises. The results indicate the existence of a positive correlation between the variables analysed in the surveyed enterprises. Entrepreneurs guided by sustainable development pursue economic and non-economic values and have a more comprehensive set of appropriate measures necessary to create value in a sustainable enterprise, which consists of achieving economic, ecological, and social goals.