bluuebunny/crossref_metadata_2025 huggingface dataset:
Adaptive Contrast Enhancement of Optical Imagery Based on Level of Detail (LOD)
Authors: Liu Cheng-Chien
Published: May 2020

The viewing and sharing of remote sensing optical imagery through the World Wide Web is an efficient means for providing information to the general public and decision makers. Since clouds and hazes inevitably limit the contrast and deteriorate visual effects, only cloudless scenes are usually included and presented in existing web mapping services. This work proposes a level-of-detail (LOD) based enhancement approach to present satellite imagery with an adaptively enhanced contrast determined by its viewing LOD. Compared to existing web mapping services, this new approach provides a better visual effect as well as spectral details of satellite imagery for cases partially covered with clouds or cirrocumulus clouds. The full archive of global satellite imagery, either the existing one or the one collected in the future, can be utilized and shared through the Web with the processing proposed in this new approach.
Assimilating SMOS Brightness Temperature for Hydrologic Model Parameters and Soil Moisture Estimation with an Immune Evolutionary Strategy
Authors: Ju Feng , An Ru , Yang Zhen , Huang Lijun , Sun Yaxing
Published: May 2020

Hydrological models play an essential role in data assimilation (DA) systems. However, it is a challenging task to acquire the distributed hydrological model parameters that affect the accuracy of the simulations at a grid scale. Remote sensing data provide an ideal observation for DA to estimate parameters and state variables. In this study, a special assimilation scheme was proposed to jointly estimate parameters and soil moisture (SM) by assimilating brightness temperature (TB) from the Soil Moisture and Ocean Salinity (SMOS) mission. Variable infiltration capacity (VIC) hydrological model and L-band microwave emission of the biosphere model (L-MEB) are coupled as model and observation operators, respectively. The scheme combines two stages of estimators, one for the static model parameters and the other for the dynamic state variables. The estimators approximate the posterior probability distribution of an unknown target through sequential Monte Carlo (SMC) sampling. Markov chain Monte Carlo (MCMC) and immune evolution strategy are embedded in both stages to solve particle impoverishment problems. To evaluate the effectiveness of the scheme, the estimated SM sets are compared with in-situ observations and SMOS products in Maqu on the Tibetan Plateau. Specifically, the root mean square error decreased from 0.126 to 0.087 m3m−3 for surface SM, with a slight impact on the root zone. The temporal correlation between DA results and in-situ measurements increased to 0.808 and 0.755 for surface SM (+0.057) and root zone SM (+0.040), respectively. The results demonstrate that assimilating TB has tremendous potential as an approach to improve the estimation of distributed model parameters and SMs of surface and root zone at a grid scale, and the immune evolution strategy is effective for increasing the accuracy of approximation in sampling.
Biomass Burning in Africa: An Investigation of Fire Radiative Power Missed by MODIS Using the 375 m VIIRS Active Fire Product
Authors: Li Fangjun , Zhang Xiaoyang , Kondragunta Shobha
Published: May 2020

Biomass burning plays a key role in the interaction between the atmosphere and the biosphere. The nearly two-decade-old Moderate Resolution Imaging Spectroradiometer (MODIS) active fire product provides critical information (e.g., fire radiative power or FRP) for characterizing fires and estimating smoke emissions. Due to limitations of sensing geometry, MODIS fire detection capability degrades at off-nadir angles and the sensor misses the observation of fires occurring inside its equatorial swath gaps. This study investigates missing MODIS FRP observations using the 375 m Visible Infrared Imaging Radiometer Suite (VIIRS) active fire data across Africa where fire occurs in the majority of vegetation-covered areas and significantly contributes to global biomass-burning emissions. We first examine the FRP relationship between the two sensors on a continental scale and in grids of seven different resolutions. We find that MODIS misses a considerable number of low-intensity fires across Africa, which results in the underestimation of daily MODIS FRP by at least 42.8% compared to VIIRS FRP. The underestimation of MODIS FRP varies largely with grid size and satellite view angle. Based on comparisons of grid-level FRP from the two sensors, adjustment models are established at seven resolutions from 0.05°–0.5° for mitigating the underestimation of MODIS grid FRP. Furthermore, the investigation of the effect of equatorial swath gaps on MODIS FRP observations reveals that swath gaps could lead to the underestimation of MODIS monthly summed FRP by 12.5%. The quantitative information of missing MODIS FRP helps to improve our understanding of potential uncertainties in the MODIS FRP based applications, especially emissions estimation.
Producing Urban Aerobiological Risk Map for Cupressaceae Family in the SW Iberian Peninsula from LiDAR Technology
Authors: Pecero-Casimiro Raúl , Fernández-Rodríguez Santiago , Tormo-Molina Rafael , Silva-Palacios Inmaculada , Gonzalo-Garijo Ángela , Monroy-Colín Alejandro , Coloma Juan Francisco , Maya-Manzano José María
Published: May 2020

Given the rise in the global population and the consequently high levels of pollution, urban green areas, such as those that include plants in the Cupressaceae family, are suitable to reduce the pollution levels, improving the air quality. However, some species with ornamental value are also very allergenic species whose planting should be regulated and their pollen production reduced by suitable pruning. The Aerobiological Index to create Risk maps for Ornamental Trees (AIROT), in its previous version, already included parameters that other indexes did not consider, such as the width of the streets, the height of buildings and the geographical characteristics of cities. It can be considered by working with LiDAR (Light Detection and Ranging) data from five urban areas, which were used to create the DEM and DSM (digital elevation and surface models) needed to create one of the parameters. Pollen production is proposed as a parameter (α) based on characteristics and uses in the forms of hedges or trees that will be incorporated into the index. It will allow the comparison of different species for the evaluation of the pruning effect when aerobiological risks are established. The maps for some species of Cupressaceae (Cupressus arizonica, Cupressus macrocarpa, Cupressus sempervirens, Cupressocyparis leylandii and Platycladus orientalis) generated in a GIS (geographic information system) from the study of several functions of Kriging, have been used in cities to identify aerobiological risks in areas of tourist and gastronomic interest. Thus, allergy patients can make decisions about the places to visit depending on the levels of risk near those areas. The AIROT index provides valuable information for allergy patients, tourists, urban planning councillors and restaurant owners in order to structure the vegetation, as well as planning tourism according to the surrounding environmental risks and reducing the aerobiological risk of certain areas.
Reversed Surface-Mass-Balance Gradients on Himalayan Debris-Covered Glaciers Inferred from Remote Sensing
Authors: Bisset Rosie R. , Dehecq Amaury , Goldberg Daniel N. , Huss Matthias , Bingham Robert G. , Gourmelen Noel
Published: May 2020

Meltwater from the glaciers in High Mountain Asia plays a critical role in water availability and food security in central and southern Asia. However, observations of glacier ablation and accumulation rates are limited in spatial and temporal scale due to the challenges that are associated with fieldwork at the remote, high-altitude settings of these glaciers. Here, using a remote-sensing-based mass-continuity approach, we compute regional-scale surface mass balance of glaciers in five key regions across High Mountain Asia. After accounting for the role of ice flow, we find distinctively different altitudinal surface-mass-balance gradients between heavily debris-covered and relatively debris-free areas. In the region surrounding Mount Everest, where debris coverage is the most extensive, our results show a reversed mean surface-mass-balance gradient of −0.21 ± 0.18 m w.e. a−1 (100 m)−1 on the low-elevation portions of glaciers, switching to a positive mean gradient of 1.21 ± 0.41 m w.e. a−1 (100 m)−1 above an average elevation of 5520 ± 50 m. Meanwhile, in West Nepal, where the debris coverage is minimal, we find a continuously positive mean gradient of 1.18 ± 0.40 m w.e. a−1 (100 m)−1. Equilibrium line altitude estimates, which are derived from our surface-mass-balance gradients, display a strong regional gradient, increasing from northwest (4490 ± 140 m) to southeast (5690 ± 130 m). Overall, our findings emphasise the importance of separating signals of surface mass balance and ice dynamics, in order to constrain better their contribution towards the ice thinning that is being observed across High Mountain Asia.
LiDAR-Based Estimates of Canopy Base Height for a Dense Uneven-Aged Structured Forest
Authors: Stefanidou Alexandra , Gitas Ioannis , Korhonen Lauri , Stavrakoudis Dimitris , Georgopoulos Nikos
Published: May 2020

Accurate canopy base height (CBH) information is essential for forest and fire managers since it constitutes a key indicator of seedling growth, wood quality and forest health as well as a necessary input in fire behavior prediction systems such as FARSITE, FlamMap and BEHAVE. The present study focused on the potential of airborne LiDAR data analysis to estimate plot-level CBH in a dense uneven-aged structured forest on complex terrain. A comparative study of two widely employed methods was performed, namely the voxel-based approach and regression analysis, which revealed a clear outperformance of the latter. More specifically, the voxel-based CBH estimates were found to lack correlation with the reference data ( R 2 = 0.15 , r R M S E = 42.36 % ) while most CBH values were overestimated resulting in an r b i a s of − 17.52 % . On the contrary, cross-validation of the developed regression model showcased an R 2 , r R M S E and r b i a s of 0 . 61 , 18.19 % and − 0.09 % respectively. Overall analysis of the results proved the voxel-based approach incapable of accurately estimating plot-level CBH due to vegetation and topographic heterogeneity of the forest environment, which however didn’t affect the regression analysis performance.
Long Term Interferometric Temporal Coherence and DInSAR Phase in Northern Peatlands
Authors: Tampuu Tauri , Praks Jaan , Uiboupin Rivo , Kull Ain
Published: May 2020

Peatlands of northern temperate and cold climates are significant pools of stored carbon. Understanding seasonal dynamics of peatland surface height and volume, often referred to as mire breathing or oscillation, is the key to improve spatial models of material flow and gas exchange. The monitoring of this type of dynamics over large areas is only feasible by remote sensing instruments. The objective of this study is to examine the applicability of Sentinel-1 synthetic aperture radar interferometry (InSAR) to characterize seasonal dynamics of peatland surface height and water table (WT) over open raised bog areas in Endla mire complex in central Estonia, characteristic for northern temperate bogs. Our results show that InSAR temporal coherence, sufficient for differential InSAR (DInSAR), is preserved in the open bog over more than six months of temporal baseline. Moreover, the coherence which is lost in a dry summer, make a recovery in autumn correlate with WT dynamics. The relationship between the coherence from a single master image and the corresponding WT difference is described by the second degree polynomial regression model (Root Mean Squared Error RMSE = 0.041 for coherence magnitude). It is also demonstrated that DInSAR phase is connected to bog surface dynamics and reveals differences between bogs and for ecotopes within a bog. These findings suggest that InSAR long term temporal coherence could be used to describe seasonal bog WT dynamics and differentiate between mire types and ecotopes within a bog. Moreover, DInSAR analysis has the potential to characterize seasonal mire surface oscillation which may be important for assessing the capacity of water storage or restoration success in northern temperate bogs.
Detection of Anomalous Behavior in Modern Smartphones Using Software Sensor-Based Data
Authors: Vlădăreanu Victor , Voiculescu Valentin-Gabriel , Grosu Vlad-Alexandru , Vlădăreanu Luige , Travediu Ana-Maria , Yan Hao , Wang Hongbo , Ruse Laura
Published: May 2020

This paper describes the steps involved in obtaining a set of relevant data sources and the accompanying method using software-based sensors to detect anomalous behavior in modern smartphones based on machine-learning classifiers. Three classes of models are investigated for classification: logistic regressions, shallow neural nets, and support vector machines. The paper details the design, implementation, and comparative evaluation of all three classes. If necessary, the approach could be extended to other computing devices, if appropriate changes were made to the software infrastructure, based upon mandatory capabilities of the underlying hardware.
A Systematic Review of Closed-Loop Feedback Techniques in Sleep Studies—Related Issues and Future Directions
Authors: Choi Jinyoung , Kwon Moonyoung , Jun Sung Chan
Published: May 2020

Advances in computer processing technology have enabled researchers to analyze real-time brain activity and build real-time closed-loop paradigms. In many fields, the effectiveness of these closed-loop protocols has proven to be better than that of the simple open-loop paradigms. Recently, sleep studies have attracted much attention as one possible application of closed-loop paradigms. To date, several studies that used closed-loop paradigms have been reported in the sleep-related literature and recommend a closed-loop feedback system to enhance specific brain activity during sleep, which leads to improvements in sleep’s effects, such as memory consolidation. However, to the best of our knowledge, no report has reviewed and discussed the detailed technical issues that arise in designing sleep closed-loop paradigms. In this paper, we reviewed the most recent reports on sleep closed-loop paradigms and offered an in-depth discussion of some of their technical issues. We found 148 journal articles strongly related with ‘sleep and stimulation’ and reviewed 20 articles on closed-loop feedback sleep studies. We focused on human sleep studies conducting any modality of feedback stimulation. Then we introduced the main component of the closed-loop system and summarized several open-source libraries, which are widely used in closed-loop systems, with step-by-step guidelines for closed-loop system implementation for sleep. Further, we proposed future directions for sleep research with closed-loop feedback systems, which provide some insight into closed-loop feedback systems.
Hyperspectral Inversion of Soil Organic Matter Content Based on a Combined Spectral Index Model
Authors: Wei Lifei , Yuan Ziran , Wang Zhengxiang , Zhao Liya , Zhang Yangxi , Lu Xianyou , Cao Liqin
Published: May 2020

Soil organic matter (SOM) refers to all carbon-containing organic matter in soil and is one of the most important indicators of soil fertility. The hyperspectral inversion analysis of SOM traditionally relies on laboratory chemical testing methods, which have the disadvantages of being inefficient and time-consuming. In this study, 69 soil samples were collected from the Honghu farmland area and a mining area in northwest China. After pretreatment, 10 spectral indicators were obtained. Ridge regression, kernel ridge regression, Bayesian ridge regression, and AdaBoost algorithms were then used to construct the SOM hyperspectral inversion model based on the characteristic bands, and the accuracy of the models was compared. The results showed that the AdaBoost algorithm based on a grid search had the best accuracy in the different regions. For the mining area in northwest China, R p 2 = 0.91, R M S E p = 0.22, and M A E p = 0.2. For the Honghu farmland area, R p 2 = 0.86, R M S E p = 0.72, and M A E p = 0.56. The detection of SOM content using hyperspectral technology has the characteristics of a high detection precision and high speed, which will be of great significance for the rapid development of precision agriculture.
Collaborative Neural Network Algorithm for Event-Driven Deployment in Wireless Sensor and Robot Networks
Authors: Zhuang Yaoming , Wu Chengdong , Wu Hao , Zhang Zuyuan , Gao Yuan , Li Li
Published: May 2020

Wireless sensor and robot networks (WSRNs) often work in complex and dangerous environments that are subject to many constraints. For obtaining a better monitoring performance, it is necessary to deploy different types of sensors for various complex environments and constraints. The traditional event-driven deployment algorithm is only applicable to a single type of monitoring scenario, so cannot effectively adapt to different types of monitoring scenarios at the same time. In this paper, a multi-constrained event-driven deployment model is proposed based on the maximum entropy function, which transforms the complex event-driven deployment problem into two continuously differentiable single-objective sub-problems. Then, a collaborative neural network (CONN) event-driven deployment algorithm is proposed based on neural network methods. The CONN event-driven deployment algorithm effectively solves the problem that it is difficult to obtain a large amount of sensor data and environmental information in a complex and dangerous monitoring environment. Unlike traditional deployment methods, the CONN algorithm can adaptively provide an optimal deployment solution for a variety of complex monitoring environments. This greatly reduces the time and cost involved in adapting to different monitoring environments. Finally, a large number of experiments verify the performance of the CONN algorithm, which can be adapted to a variety of complex application scenarios.
Smartphone-Based Electrochemical Potentiostat Detection System Using PEDOT: PSS/Chitosan/Graphene Modified Screen-Printed Electrodes for Dopamine Detection
Authors: Shen Xiaoyan , Ju Feng , Li Guicai , Ma Lei
Published: May 2020

In this work, a smartphone-based electrochemical detection system was designed and developed for rapid and real-time detection of dopamine (DA). The system included a screen-printed electrode (SPE) used as a sensor, a hand-held electrochemical potentiostat and a smart phone with a specially designed app. During the detection period, the SPEs modified with poly(3,4-ethylenedioxythiophene) (PEDOT), chitosan (CS) and graphene (G) were used to convert and amplify the electrochemical reaction signals. The electrochemical potentiostat was used to generate excitation electrical signals and collect the electrical signals converted from the sensor. The smartphone—connected to the detector via Bluetooth-was used to control the detector for tests, further process the uploaded data, and plot graphs in real time. Experimental results showed that the self-designed sensing system could be employed for highly selective detection of DA in the presence of interfering substances such as ascorbic acid (AA) and uric acid (UA). CV was carried out to characterize the electrochemical properties of the modified SPEs and the electrochemical behaviors of DA on the modified SPEs. Finally, according to the analysis of DPV responses of DA, the system could detect DA with a detection sensitivity of 0.52 ± 0.01 μA/μM and a limit of detection of 0.29 μM in the linear range of DA concentrations from 0.05 to 70 μM.
Deep Learning Based Switching Filter for Impulsive Noise Removal in Color Images
Authors: Radlak Krystian , Malinski Lukasz , Smolka Bogdan
Published: May 2020

Noise reduction is one of the most important and still active research topics in low-level image processing due to its high impact on object detection and scene understanding for computer vision systems. Recently, we observed a substantially increased interest in the application of deep learning algorithms. Many computer vision systems use them, due to their impressive capability of feature extraction and classification. While these methods have also been successfully applied in image denoising, significantly improving its performance, most of the proposed approaches were designed for Gaussian noise suppression. In this paper, we present a switching filtering technique intended for impulsive noise removal using deep learning. In the proposed method, the distorted pixels are detected using a deep neural network architecture and restored with the fast adaptive mean filter. The performed experiments show that the proposed approach is superior to the state-of-the-art filters designed for impulsive noise removal in color digital images.
Investigation of Copper-Less Gas Electron Multiplier Detectors Responses to Soft X-rays
Authors: Mindur Bartosz , Fiutowski Tomasz , Koperny Stefan , Wiącek Piotr , Dąbrowski Władysław
Published: May 2020

In this paper, we report on the systematic study of different variants of X-ray detectors based on Gas Electron Multiplier (GEM) technology using modified GEM foils with greatly reduced amount of copper. The main goal of this study was understanding the performance of such detectors applied in X-Ray Fluorescence (XRF) elemental analysis. Reduction of the amount of copper in the detector structure is crucial for suppression of XRF background from copper, but one has to ensure that key detector parameters are not affected by such modification. The tested detector variants include detectors with different types of copper-less GEM foils, which have been manufactured starting from standard copper-clad foils and removing partially the copper layer in additional post-processing steps. The results are analyzed and discussed with a particular focus on the energy resolution, uniformity of gas gain and energy resolution across the detector area, and on the long-term stability of the gas gain. Long-term stability tests performed for selected detectors do not indicate for any accelerated aging of the copper-less detectors compared to standard detectors using copper-clad GEM foils. The presented results lead us to conclude that the copper-less GEM detectors are promising devices to suppress the XRF background.
Newly Developed Correlations to Predict the Rheological Parameters of High-Bentonite Drilling Fluid Using Neural Networks
Authors: Gowida Ahmed , Elkatatny Salaheldin , Abdelgawad Khaled , Gajbhiye Rahul
Published: May 2020

High-bentonite mud (HBM) is a water-based drilling fluid characterized by its remarkable improvement in cutting removal and hole cleaning efficiency. Periodic monitoring of the rheological properties of HBM is mandatory for optimizing the drilling operation. The objective of this study is to develop new sets of correlations using artificial neural network (ANN) to predict the rheological parameters of HBM while drilling using the frequent measurements, every 15 to 20 min, of mud density (MD) and Marsh funnel viscosity (FV). The ANN models were developed using 200 field data points. The dataset was divided into 70:30 ratios for training and testing the ANN models respectively. The optimized ANN models showed a significant match between the predicted and the measured rheological properties with a high correlation coefficient (R) higher than 0.90 and a maximum average absolute percentage error (AAPE) of 6%. New empirical correlations were extracted from the ANN models to estimate plastic viscosity (PV), yield point (YP), and apparent viscosity (AV) directly without running the models for easier and practical application. The results obtained from AV empirical correlation outperformed the previously published correlations in terms of R and AAPE.
On-Demand Channel Bonding in Heterogeneous WLANs: A Multi-Agent Deep Reinforcement Learning Approach
Authors: Qi Hang , Huang Hao , Hu Zhiqun , Wen Xiangming , Lu Zhaoming
Published: May 2020

In order to meet the ever-increasing traffic demand of Wireless Local Area Networks (WLANs), channel bonding is introduced in IEEE 802.11 standards. Although channel bonding effectively increases the transmission rate, the wider channel reduces the number of non-overlapping channels and is more susceptible to interference. Meanwhile, the traffic load differs from one access point (AP) to another and changes significantly depending on the time of day. Therefore, the primary channel and channel bonding bandwidth should be carefully selected to meet traffic demand and guarantee the performance gain. In this paper, we proposed an On-Demand Channel Bonding (O-DCB) algorithm based on Deep Reinforcement Learning (DRL) for heterogeneous WLANs to reduce transmission delay, where the APs have different channel bonding capabilities. In this problem, the state space is continuous and the action space is discrete. However, the size of action space increases exponentially with the number of APs by using single-agent DRL, which severely affects the learning rate. To accelerate learning, Multi-Agent Deep Deterministic Policy Gradient (MADDPG) is used to train O-DCB. Real traffic traces collected from a campus WLAN are used to train and test O-DCB. Simulation results reveal that the proposed algorithm has good convergence and lower delay than other algorithms.
Tomographic Ultrasound and LED-Based Photoacoustic System for Preclinical Imaging
Authors: Francis Kalloor Joseph , Booijink Richell , Bansal Ruchi , Steenbergen Wiendelt
Published: May 2020

Small animals are widely used as disease models in medical research. Noninvasive imaging modalities with functional capability play an important role in studying the disease state and treatment progress. Photoacoustics, being a noninvasive and functional modality, has the potential for small-animal imaging. However, the conventional photoacoustic tomographic systems use pulsed lasers, making it expensive, bulky, and require long acquisition time. In this work, we propose the use of photoacoustic and ultrasound tomographic imaging with LEDs as the light source and acoustic detection using a linear transducer array. We have demonstrated full-view tomographic imaging of a euthanized mouse and a potential application in liver fibrosis research.
Optimal Design of Switchable Wearable Antenna Array for Wireless Sensor Networks
Authors: Januszkiewicz Łukasz , Di Barba Paolo , Hausman Sławomir
Published: May 2020

In the paper, we present a novel approach to the optimum design of wearable antenna arrays intended for off-body links of wireless body area networks. Specifically, we investigate a four-element array that has a switchable radiation pattern able to direct its higher gain towards a signal source and a lower gain towards an interference. The aim is to increase the signal to interference ratio. We apply a genetic algorithm to optimize both the spatial placement and the feed phasing of the elementary on-body antennas. We propose a simplified, computationally efficient model for the simulation of the array radiation pattern. The model is based on full-wave simulations obtained with a simplified cylindrical model of the human body. We also propose, implement, and evaluate four objective functions based on signal to interference ratio, i.e., min-max, nadir point distance maximization, utopia point distance minimization, and full Pareto-like. Our optimized design obtained with this approach exhibits a significant performance improvement in comparison to the initial heuristic design.
Moxifloxacin Hydrochloride Electrochemical Detection at Gold Nanoparticles Modified Screen-Printed Electrode
Authors: Shehata M. , Fekry Amany M. , Walcarius Alain
Published: May 2020

It appeared that either the carbon paste or the screen-printed carbon electrodes that were modified with gold nanoparticles (AuNPs) gave rise to the largest current responses after a rapid screening of various nanomaterials as modifiers of carbon composite electrodes in view of designing an electrochemical sensor for Moxifloxacin Hydrochloride (Moxi). The screen-printed electrode (SPE) support was preferred over the carbon paste one for its ability to be used as disposable single-use sensor enabling the circumvention of the problems of surface fouling encountered in the determination of Moxi. The response of AuNPs modified SPE to Moxi was investigated by cyclic voltammetry (CV) (including the effect of the potential scan rate and the pH of the medium), chronoamperometry, and differential pulse voltammetry (DPV) after morphological and physico-chemical characterization. DPV was finally applied to Moxi detection in phosphate buffer at pH 7, giving rise to an accessible concentration window ranging between 8 µM and 0.48 mM, and the detection and quantification limits were established to be 11.6 µM and 38.6 µM, correspondingly. In order to estimate the applicability of Moxi identification scheme in actual trials, it was practiced in a human baby urine sample with excellent recoveries between 99.8 % and 101.6 % and RSDs of 1.1–3.4%, without noticeable interference.
Blockchain Mechanism and Symmetric Encryption in A Wireless Sensor Network
Authors: Guerrero-Sanchez Alma E. , Rivas-Araiza Edgar A. , Gonzalez-Cordoba Jose Luis , Toledano-Ayala Manuel , Takacs Andras
Published: May 2020

The Internet of Things (IoT) paradigm allows the connection and exchange of information between millions of smart devices. This paradigm grows and develops exponentially as do the risks and attacks on IoT infrastructures. Security, privacy, reliability, and autonomy are the most important requirements in IoT Systems. If these issues are not guaranteed, the IoT system could be susceptible to malicious users and malicious use. In centralized IoT systems, attacks and risks are greater, especially when data is transmitted between devices and shared with other organizations. To avoid these types of situations, this work presents a decentralized system that guarantees the autonomy and security of an IoT system. The proposed methodology helps to protect data integrity and availability based on the security advantages provided by blockchain and the use of cryptographic tools. The accuracy of the proposed methodology was measured on a temperature and humidity sensing IoT-based Wireless Sensor Network (WSN). The obtained results prove that the proposal fulfils the main requirements of an IoT system. It is autonomous, secure to share and send information between devices and users, has privacy, it is reliable, and the information is available in the infrastructure. Furthermore, this research demonstrates that the proposal is less susceptible to the most frequent attacks against IoT systems, such as linking attack, man in the middle, and Distributed Denial of Service (DDoS) attack.
Ultrasonic Transducers Shaped in Archimedean and Fibonacci Spiral: A Comparison
Authors: Fiorillo Antonino S. , Pullano Salvatore Andrea , Bianco Maria Giovanna , Critello Costantino Davide
Published: May 2020

We developed and investigated a particular geometry of transducers, emulating the shape of bats’ cochlea, to transmit and receive ultrasounds in the air. Their design involved the use of polyvinylidene fluoride (PVDF) as a piezoelectric material, thanks to its excellent conformability and flexibility. This material offers the primary requirements for sensing devices in applications such as sonar system or energy harvesting technology. The piezo film was folded according to both the Archimedean and Fibonacci spirals, and their performances were investigated in the frequency range from 20 kHz up to more than 80 kHz. The finite element analysis (FEA) of the proposed transducers highlighted the presence of multiple resonance vibrations, proved by the experimental measurements of the equivalent electric impedance and frequency response. Far-field radiation patterns demonstrated, horizontally and vertically, omnidirectional properties both as transmitters and receivers. All was enough to establish the best validity of the spiral shaped transducers for applications based on the bio sonar principle.
Normative Power Europe as an Ingroup Projection? The EU’s Response to the Arab Uprising
Authors: Tapia-León Juan José , Galdeano-Gómez Emilio
Published: May 2020

This paper aims to understand the social-psychological dimension of the Normative Power Europe discourse using ingroup projection as a discursive/cognitive practice of othering. It takes issue with most poststructuralist studies that conduct analyses of Normative Power Europe based on the dependence of identity on difference through the discursive tendency to construct reality by opposites. Ingroup projection is based both on the need for differentiation to obtain positive distinctiveness and on the natural tendency for categorization processes by which groups share a common higher-order category. In this way, groups tend to project (ingroup projection) their traits and distinctive values onto this higher-order category to legitimate intergroup status differences. The EU’s response to the Arab uprisings serves as an empirical test for this argument, insofar as the uprisings implied a cognitive change of the EU’s “other” in the construction of the Mediterranean. Through ingroup projection, the EU (ingroup) differentiates itself from this new Arab Mediterranean other (outgroup) and projects EU’s idealized identity onto the Mediterranean region (higher-order category) to legitimate its new policies after the uprising.
Costs and Benefits of Electrifying and Automating Bus Transit Fleets
Authors: Quarles Neil , Kockelman Kara M. , Mohamed Moataz
Published: May 2020

Diesel-powered, human-driven buses currently dominate public transit options in most U.S. cities, yet they produce health, environmental, and cost concerns. Emerging technologies may improve fleet operations by cost-effectively reducing emissions. This study analyzes both battery-electric buses and self-driving (autonomous) buses from both cost and qualitative perspectives, using the Capital Metropolitan Transportation Authority’s bus fleet in Austin, Texas. The study predicts battery-electric buses, including the required charging infrastructure, will become lifecycle cost-competitive in or before the year 2030 at existing U.S. fuel prices ($2.00/gallon), with the specific year depending on the actual rate of cost decline and the diesel bus purchase prices. Rising diesel prices would result in immediate cost savings before reaching $3.30 per gallon. Self-driving buses will reduce or eliminate the need for human drivers, one of the highest current operating costs of transit agencies. Finally, this study develops adoption schedules for these technologies. Recognizing bus lifespans and driver contracts, and assuming battery-electric bus adoption beginning in year-2020, cumulative break-even (neglecting extrinsic benefits, such as respiratory health) occurs somewhere between 2030 and 2037 depending on the rate of battery cost decline and diesel-bus purchase prices. This range changes to 2028 if self-driving technology is available for simultaneous adoption on new electric bus purchases beginning in 2020. The results inform fleet operators and manufacturers of the budgetary implications of converting a bus fleet to electric power, and what cost parameters allow electric buses to provide budgetary benefits over their diesel counterparts.
Difficulties with Use of Cocoa Bean Shell in Food Production and High Voltage Electrical Discharge as a Possible Solution
Authors: Barišić Veronika , Jozinović Antun , Flanjak Ivana , Šubarić Drago , Babić Jurislav , Miličević Borislav , Doko Kristina , Ačkar Đurđica
Published: May 2020

The cocoa and chocolate industries have huge problems with the utilization of waste generated during the production process. Waste material generated during production include cocoa pod husk, pulp, and cocoa bean shell. Cocoa shell is a by-product that has great potential because of its composition. It consists of dietary fibers, proteins, polyphenols, methylxanthines, etc. However, despite its favorable composition, cocoa shell often cannot be used directly in food production because it may contain components that are harmful for human health. Cocoa shell can carry mycotoxins, different microorganisms, polycyclic aromatic hydrocarbons, and heavy metals. High voltage electrical discharge presents a novel non-thermal method that has great potential for the decontamination of waste materials and can also be used for extraction of valuable compounds from cocoa shell.
Mapping Research on Sustainable Supply-Chain Management
Authors: Lis Andrzej , Sudolska Agata , Tomanek Mateusz
Published: May 2020

The aim of the paper is to map the thematic landscape of the sustainable supply-chain management (SSCM) research field and contribute to exploring “relationships among specific constructs” in the field. The use of bibliometric methodology and the focus given to relationships among topics categorized into thematic clusters within the field are the features which differ the study from other reviews in the research field. The operational objectives of the study are as follows: (1) to profile the development of the SSCM research field and its scientific output, (2) to identify leading thematic areas in the field and explore their composition and relationships among them, (3) to identify ‘hot’, emerging topics in the field. The analysis of change in the number of publications and citations related to the SSCM concept supports the study of research productivity in the field. General publication profiling focuses on the identification of subject areas and leading contributors to the research field, i.e., countries, research institutions, source titles and authors. Keywords co-occurrence analysis is employed to identify and explore leading and emerging topics. The study points out that the main thematic areas in the SSCM research field are: (1) economy and management in the context of the environment, (2) supply chain in the context of sustainability, (3) sustainable supply chains—process approach, (4) decision making for SSCM, (5) the practice context of supply-chain management, and (6) competition and social responsibility (SR) issues. The most up-to-date topics of scientific inquiry in the field focus around the following issues: (1) human aspects, (2) sustainable supplier selection, (3) manufacturing, (4) circular economy, (5) efficiency, (6) sustainable practices, (7) commerce, (8) costs, (9) environmental impact, and (10) the textile industry.
Optimization of Airport Capacity Efficiency by Selecting Optimal Aircraft and Airline Business Model
Authors: Štimac Igor , Vidović Andrija , Mihetec Tomislav , Drljača Miroslav
Published: May 2020

This paper analyses the impact of airline business models on airport infrastructure and operational capacity and answers the question how to optimize capacity in order to achieve maximum efficiency and profitability as well as how to maintain an adequate level of service quality. As part of the research, a new model was created as an integral part of the Airport Management Strategy Software (AMSS) application. The purpose of the application is to enable the airport management to review and optimize operations in terms of maximum technical and technological capacity utilization. In addition, the application can be used to fill the available slots according to the specifics of the airline’s business model without compromising the security, flexibility, and profitability of airport operations. The validation of the application was conducted at Zagreb Airport, which generated traffic of 3.4 million passengers in 2019. The result of the research is a model which, based on the calculation of the existing capacity of the airport infrastructure and ground handling equipment, enables the simulation of new airline business models and aircraft type implementation. Furthermore, the model also analyses their impact on the utilization of the airport infrastructure and equipment. The research demonstrated the interdependence between airport capacity optimization and optimal slot allocation, and the specifics of airline business models and aircraft types in their fleets. By adopting this model, airport managers can prevent mistakes that arise during negotiations with airlines, which can result in the under capacity of the infrastructure, equipment, and human resources as well as cause lower levels of security, numerous delays, reduced quality of service and, ultimately, negative financial effects.
Can Companies Survive a Multi-Brand Crisis? Research on Consumer Scapegoating
Authors: Zhang Xuan , Zhang Hongxia , Lei Jill , Gao Hongzhi
Published: May 2020

Compared with single-brand crises, multi-brand crises have broader and deeper influence. However, there is only a limited amount of research regarding this field, especially for the phenomenon of consumer scapegoating. This research aims to further explore the consumer scapegoating effect and its psychological mechanism in the context of a multi-brand crisis. Through two experimental studies, this research discusses the influence of a multi-brand crisis and also the emergence of a scapegoat brand on two brand categories, the crisis brand category and the competing brand category. Furthermore, the current research also explores the mechanism of the consumer scapegoating effect. Results show that when a multi-brand crisis happens, consumer brand trust in the crisis brand category decreases because of assimilation, and consumer brand trust in the competing brand category increases because of contrast effect. Besides, from the perspective of the crisis brand category, the emergence of a scapegoat brand could be treated by consumers as a signal that the crisis is over, especially for a severe crisis. Results also support that cognitive dissonance mediates the process that the emergence of a scapegoat brand leads to an increase in consumer brand trust in the crisis brand category and a decrease of consumer brand trust in the competing brand category.
Sustainability of Vehicle Fuel Biomethane Produced from Grass Silage in Finland
Authors: Rasi Saija , Timonen Karetta , Joensuu Katri , Regina Kristiina , Virkajärvi Perttu , Heusala Hannele , Tampio Elina , Luostarinen Sari
Published: May 2020

Increasing demand of fossil-free fuels in the transport sector drives towards using new biomass sources in fuel production. Municipal waste as a substrate is used in many countries in biomethane production, but the amount of waste can cover only a small portion of the fuel used. In Europe, the new renewable energy directive (RED II) was established December 2018 to ensure the sustainability of renewable fuels. The directive includes typical and default greenhouse gas (GHG) emissions for several potential substrates, such as biogas from manure or maize silage, which the biogas plants can use to verify their emissions directly or to calculate their emissions using the methods provided. However, such default value for grass silage as biogas substrate is lacking. We defined the conditions needed to fulfil the sustainability criteria of the directive when producing biomethane for vehicle fuel using grass silage as the feedstock in Finland. The emission reduction targets are not easy to achieve in Finland when using grass cultivated exclusively for energy production. The reduction targets can be achieved, however, if the grass is cultivated due to an improved crop rotation, where the grass is co-digested with manure and/or energy sources with zero emissions for the process can be applied.
Sensitive Factors Identification and Scenario Simulation of Water Demand in the Arid Agricultural Area Based on the Socio-Economic-Environment Nexus
Authors: Ma Weijing , Meng Lihong , Wei Feili , Opp Christian , Yang Dewei
Published: May 2020

Water scarcity has seriously threatened the sustainable development of Zhangjiakou City, an arid agricultural area in North China, and the ecological security of its neighboring areas. In this study, a system dynamics model is established based on variable sensitivity analysis and is employed to simulate water demand (2015–2035) in four designed alternative development scenarios in Zhangjiakou City. The results show that: (1) the variables related to irrigation farmland are the main driving factors of water demand, especially the area and water use quota. (2) The total water demand will rise continually in the current development scenario and economic priority scenario, and the proportion of agricultural water demand will drop to 67% and 63%, respectively. It will decline continually in the water-saving priority scenario and balanced development scenario, and the proportion of agricultural water demand will drop to 56% and 57%, respectively. (3) Water consumption per ten thousand yuan of GDP will fall to around 20 m3 in 2035 in each scenario, indicating that the reduction of water demand only by slowing down economic growth cannot improve the efficiency of water use. The research results will be beneficial to extract feasible strategies and policies for balancing economic development and water conservation.
Downloading Europe: A Regional Comparison in the Uptake of the EU Forest Action Plan
Authors: Aggestam Filip , Pülzl Helga
Published: May 2020

The first EU Forest Strategy was adopted in 1998 to provide general guidelines for an EU forest policy designed to coordinate other EU forest-relevant policies. The implementation of the first strategy was done under the auspices of the EU Forest Action Plan, covering the period from 2007 to 2011. The Forest Action Plan was a tool that facilitated voluntary cooperation between EU Member States (no enforcement capabilities), with some coordinating actions being implemented by the European Commission. The reason for returning to the Forest Action Plan in this article is to provide further insight into how it was employed by EU Member States—in contrast to the majority of similar articles on the topic, which are primarily concerned with an examination of EU forest-relevant policies by either analyzing the impact of EU decision-making on forestry at the national level or studying EU Member States’ influence on the EU rather than how EU Member States actually react to EU strategies. This paper addresses this empirical gap and highlights the significant variations of the Europeanization effects on EU Member States when deciding upon and implementing a non-legally binding policy instrument when compared to legally binding policy instruments. Individual Member States exhibit varied strategies when implementing a soft policy instrument, as their respective decision spaces are substantially different, particularly when the costs and benefits of complying are not comparable to those of a legally binding instrument. These results highlight the need for a more nuanced and varied approach to the implementation of soft policy instruments by the EU, with the additional implementation strategies suggested in this article being presented to assist in meeting this need for variation.