bluuebunny/crossref_metadata_2025 huggingface dataset:
Neural Network Based Kalman Filters for the Spatio-Temporal Interpolation of Satellite-Derived Sea Surface Temperature
Authors: Ouala Said , Fablet Ronan , Herzet Cédric , Chapron Bertrand , Pascual Ananda , Collard Fabrice , Gaultier Lucile
Published: November 2018

The forecasting and reconstruction of oceanic dynamics is a crucial challenge. While model driven strategies are still the state-of-the-art approaches in the reconstruction of spatio-temporal dynamics. The ever increasing availability of data collections in oceanography raised the relevance of data-driven approaches as computationally efficient representations of spatio-temporal fields reconstruction. This tools proved to outperform classical state-of-the-art interpolation techniques such as optimal interpolation and DINEOF in the retrievement of fine scale structures while still been computationally efficient comparing to model based data assimilation schemes. However, coupling this data-driven priors to classical filtering schemes limits their potential representativity. From this point of view, the recent advances in machine learning and especially neural networks and deep learning can provide a new infrastructure for dynamical modeling and interpolation within a data-driven framework. In this work we adress this challenge and develop a novel Neural-Network-based (NN-based) Kalman filter for spatio-temporal interpolation of sea surface dynamics. Based on a data-driven probabilistic representation of spatio-temporal fields, our approach can be regarded as an alternative to classical filtering schemes such as the ensemble Kalman filters (EnKF) in data assimilation. Overall, the key features of the proposed approach are two-fold: (i) we propose a novel architecture for the stochastic representation of two dimensional (2D) geophysical dynamics based on a neural networks, (ii) we derive the associated parametric Kalman-like filtering scheme for a computationally-efficient spatio-temporal interpolation of Sea Surface Temperature (SST) fields. We illustrate the relevance of our contribution for an OSSE (Observing System Simulation Experiment) in a case-study region off South Africa. Our numerical experiments report significant improvements in terms of reconstruction performance compared with operational and state-of-the-art schemes (e.g., optimal interpolation, Empirical Orthogonal Function (EOF) based interpolation and analog data assimilation).
Measuring Sedentary Behavior by Means of Muscular Activity and Accelerometry
Authors: Kuster Roman , Huber Mirco , Hirschi Silas , Siegl Walter , Baumgartner Daniel , Hagströmer Maria , Grooten Wim
Published: November 2018

Sedentary Behavior (SB) is among the most frequent human behaviors and is associated with a plethora of serious chronic lifestyle diseases as well as premature death. Office workers in particular are at an increased risk due to their extensive amounts of occupational SB. However, we still lack an objective method to measure SB consistent with its definition. We have therefore developed a new measurement system based on muscular activity and accelerometry. The primary aim of the present study was to calibrate the new-developed 8-CH-EMG+ for measuring occupational SB against an indirect calorimeter during typical desk-based office work activities. In total, 25 volunteers performed nine office tasks at three typical workplaces. Minute-by-minute posture and activity classification was performed using subsequent decision trees developed with artificial intelligence data processing techniques. The 8-CH-EMG+ successfully identified all sitting episodes (AUC = 1.0). Furthermore, depending on the number of electromyography channels included, the device has a sensitivity of 83–98% and 74–98% to detect SB and active sitting (AUC = 0.85–0.91). The 8-CH-EMG+ advances the field of objective SB measurements by combining accelerometry with muscular activity. Future field studies should consider the use of EMG sensors to record SB in line with its definition.
Mapping Mangrove Forests of Dongzhaigang Nature Reserve in China Using Landsat 8 and Radarsat-2 Polarimetric SAR Data
Authors: Zhen Jianing , Liao Jingjuan , Shen Guozhuang
Published: November 2018

Mangrove forests are distributed in intertidal regions that act as a “natural barrier” to the coast. They have enormous ecological, economic, and social value. However, the world’s mangrove forests are declining under immense pressure from anthropogenic and natural disturbances. Accurate information regarding mangrove forests is essential for their protection and restoration. The main objective of this study was to develop a method to improve the classification of mangrove forests using C-band quad-pol Synthetic Aperture Radar (SAR) data (Radarsat-2) and optical data (Landsat 8), and to analyze the spectral and backscattering signatures of mangrove forests. We used a support vector machine (SVM) classification method to classify the land use in Hainan Dongzhaigang National Nature Reserve (HDNNR). The results showed that the overall accuracy using only optical information was 83.5%. Classification accuracy was improved to a varying extent by the addition of different radar data. The highest overall accuracy was 95.0% based on a combination of SAR and optical data. The area of mangrove forest in the reserve was found to be 1981.7 ha, as determined from the group with the highest classification accuracy. Combining optical data with SAR data could improve the classification accuracy and be significant for mangrove forest conservation.
UAV IoT Framework Views and Challenges: Towards Protecting Drones as “Things”
Authors: Lagkas Thomas , Argyriou Vasileios , Bibi Stamatia , Sarigiannidis Panagiotis
Published: November 2018

Unmanned aerial vehicles (UAVs) have enormous potential in enabling new applications in various areas, ranging from military, security, medicine, and surveillance to traffic-monitoring applications. Lately, there has been heavy investment in the development of UAVs and multi-UAVs systems that can collaborate and complete missions more efficiently and economically. Emerging technologies such as 4G/5G networks have significant potential on UAVs equipped with cameras, sensors, and GPS receivers in delivering Internet of Things (IoT) services from great heights, creating an airborne domain of the IoT. However, there are many issues to be resolved before the effective use of UAVs can be made, including security, privacy, and management. As such, in this paper we review new UAV application areas enabled by the IoT and 5G technologies, analyze the sensor requirements, and overview solutions for fleet management over aerial-networking, privacy, and security challenges. Finally, we propose a framework that supports and enables these technologies on UAVs. The introduced framework provisions a holistic IoT architecture that enables the protection of UAVs as “flying” things in a collaborative networked environment.
Prestress Monitoring of a Steel Strand in an Anchorage Connection Using Piezoceramic Transducers and Time Reversal Method
Authors: Zhang Xiaoyu , Zhang Liuyu , Liu Laijun , Huo Linsheng
Published: November 2018

Steel strands are widely used in cable stay or suspension bridges. The safety and stability of steel strands are important issues during their operation period. Steel strand is subjected to various types of prestress loss which loosens the wedge anchorage system, negatively impacting the stability of the structure and even leading to severe accidents. In this paper, the authors propose a time reversal (TR) method to monitor the looseness status of the wedge anchorage system by using stress wave based active sensing. As a commonly used piezoceramic material, Lead Zirconate Titanate (PZT) with a strong piezoelectric effect is employed. In the proposed active sensing approach, PZT patches are used as sensors and actuators to monitor the steel strand looseness status. One PZT patch is bonded to the steel strand, one PZT patch is bonded to the wedges, and another PZT patch is bonded to the barrel. There are three different interfaces of the wedge anchorage system to monitor the steel strand looseness status. In the first method, the PZT patch on the steel strand is used as an actuator to generate a stress wave and the PZT patch on the wedge is used as a sensor to detect the propagated waves through the wedge anchorage system. In the second method, the PZT patch on the steel strand is used as an actuator to generate a stress wave and the PZT patch on the barrel is used as a sensor to detect the propagated waves through the wedge anchorage system. In the third method, the PZT patch on the wedges is used as an actuator to generate a stress wave and the PZT patches on the barrel is used as a sensor to detect the propagated waves through the wedge anchorage system, of which the looseness will directly impact the stress wave propagation. The TR method is utilized to analyze the transmitted signal between PZT patches through the wedge anchorage system. Compared with the peak values of the TR focused signals, it can be found that the peak value increases as the wedge anchorage system tightness increases. Therefore, the peak value of the TR focused signal can be used to monitor the tightness of the steel strand. In addition, the experimental results demonstrated the time reversal method’s reliability, sensitivity and anti-noise property.
A Regenerative Immunoaffinity Layer Based on the Outer Membrane of Z-Domains Autodisplaying E. coli for Immunoassays and Immunosensors
Authors: Jeon Daseul , Pyun Jae-Chul , Jose Joachim , Park Min
Published: November 2018

Through orientation control of antibodies, Z-domains autodisplaying Escherichia coli outer cell membrane (OM) may be utilized to improve the sensitivity and limit of detection (LOD) of immunoassays and immunosensors. A regenerative immunoaffinity layer based on Z-domains autodisplaying E. coli OM was developed for the surface plasmon resonance (SPR) biosensor. Regeneration conditions for the Z-domains autodisplaying E. coli OM-based immunoassays and immunosensors were optimized by varying pH and detergent concentration. An E. coli cell-based HRP immunoassay was tested and validated in three sequential regenerative immunoassays under optimal conditions. The OM of Z-domains autodisplaying E. coli was isolated and coated on the two-dimensional substrate (microplate). The OM-based HRP immunoassay was tested and validated in four regenerative immunoassays. This regenerative OM layer was applied to the SPR biosensor. Z-domains autodisplaying OM layered onto the gold surface of SPR biosensors was developed, and the OM-based regenerative immunoaffinity layer with orientation control was tested using CRP analyte. The SPR biosensor regenerative immunoaffinity layer demonstrated that CRP biosensing was repeated for five regeneration cycles with less than 2% signal difference. Therefore, the newly developed regenerative immunoaffinity layer with antibody orientation control may improve biosensing sensitivity and reduce the cost of medical diagnosis.
Multiclass Radio Frequency Interference Detection and Suppression for SAR Based on the Single Shot MultiBox Detector
Authors: Yu Junfei , Li Jingwen , Sun Bing , Chen Jie , Li Chunsheng
Published: November 2018

Radio frequency interference (RFI) is known to jam synthetic aperture radar (SAR) measurements, severely degrading the SAR imaging quality. The suppression of RFI in SAR echo signals is usually an underdetermined blind source separation problem. In this paper, we propose a novel method for multiclass RFI detection and suppression based on the single shot multibox detector (SSD). First, an echo-interference dataset is established by randomly combining the target signal with various types of RFI in a simulation, and the time–frequency form of the dataset is obtained by utilizing the short-time Fourier transform (STFT). Next, the time–frequency dataset acts as input data to train the SSD and obtain a network that is capable of detecting, identifying and estimating the interference. Finally, all of the interference signals are exactly reconstructed based on the prediction results of the SSD and mitigated by an adaptive filter. The proposed method can effectively increase the signal-to-interference-noise ratio (SINR) of RFI-contaminated SAR echoes and improve the peak sidelobe ratio (PSLR) after pulse compression. The simulated experimental results validate the effectiveness of the proposed method.
Evaluation of the Characteristics and Coating Film Structure of Polymer/Ceramic Pressure-Sensitive Paint
Authors: Sugioka Yosuke , Arakida Kazuto , Kasai Miku , Nonomura Taku , Asai Keisuke , Egami Yasuhiro , Nakakita Kazuyuki
Published: November 2018

Polymer/ceramic pressure-sensitive paint (PC-PSP), which incorporates a high percentage of particles in the binder layer, is proposed in order to improve the characteristics of PSP. The procedure for embedding particles into the binder layer was modified. In the conventional procedure, dye is adsorbed onto a polymer/ceramic coating film (denoted herein as a dye-adsorbed (D-adsorbed) PSP). In the new procedure, the mixture of a dye and particles is adsorbed onto a polymer coating film (denoted herein as the particle/dye-adsorbed (PD-adsorbed) PSP). The effect of particle mass content on PSP characteristics was investigated. In addition, the effect of solvent on PSP characteristics and film structure were evaluated for the PD-adsorbed PSP. As a result, the difference in the PSP characteristics between the two types of PSP was clarified. Although surface roughness and time response increase with increased mass content of particles for both D- and PD-adsorbed PSPs, the critical pigment volume concentration (CPVC) for the PD-adsorbed PSP is smaller than that of the D-adsorbed PSP (88 wt% and 93 wt%, respectively). The PD-adsorbed PSP has a higher frequency response comparing with the D-adsorbed PSP while maintaining the same surface roughness. Observation by scanning electron microscope showed that the CPVC of the PC-PSP is governed primarily by surface structure. The coating film structure can be roughly classified into two states depending on the particle mass content. One is a state in which the coating film consisted of two layers: a lower particle-rich layer and an upper polymer-rich layer. This type of structure was observed in the PD-adsorbed PSP as well as in the D-adsorbed PSP. In the other state, polymer and particles are homogeneously distributed in the film, and pores are formed. This difference in the coating structure results in a change in the time response.
Human Activity Recognition Based on Symbolic Representation Algorithms for Inertial Sensors
Authors: Sousa Lima Wesllen , De Souza Bragança Hendrio L. , Montero Quispe Kevin G. , Pereira Souto Eduardo J.
Published: November 2018

Mobile sensing has allowed the emergence of a variety of solutions related to the monitoring and recognition of human activities (HAR). Such solutions have been implemented in smartphones for the purpose of better understanding human behavior. However, such solutions still suffer from the limitations of the computing resources found on smartphones. In this sense, the HAR area has focused on the development of solutions of low computational cost. In general, the strategies used in the solutions are based on shallow and deep learning algorithms. The problem is that not all of these strategies are feasible for implementation in smartphones due to the high computational cost required, mainly, by the steps of data preparation and the training of classification models. In this context, this article evaluates a new set of alternative strategies based on Symbolic Aggregate Approximation (SAX) and Symbolic Fourier Approximation (SFA) algorithms with the purpose of developing solutions with low computational cost in terms of memory and processing. In addition, this article also evaluates some classification algorithms adapted to manipulate symbolic data, such as SAX-VSM, BOSS, BOSS-VS and WEASEL. Experiments were performed on the UCI-HAR, SHOAIB and WISDM databases commonly used in the literature to validate HAR solutions based on smartphones. The results show that the symbolic representation algorithms are faster in the feature extraction phase, on average, by 84.81%, and reduce the consumption of memory space, on average, by 94.48%, and they have accuracy rates equivalent to conventional algorithms.
Whisper: Programmable and Flexible Control on Industrial IoT Networks
Authors: Municio Esteban , Marquez-Barja Johann , Latré Steven , Vissicchio Stefano
Published: November 2018

Software Defined Networking (SDN) centralizes network control to improve network programmability and flexibility. Contrary to wired settings, it is unclear how to support SDN in low power and lossy networks like typical Internet of Things (IoT) ones. Challenges encompass providing reliable in-band connectivity between the centralized controller and out-of-range nodes, and coping with physical limitations of the highly resource-constrained IoT devices. In this work, we present Whisper, an enabler for SDN in low power and lossy networks. The centralized Whisper controller of a network remotely controls nodes’ forwarding and cell allocation. To do so, the controller sends carefully computed routing and scheduling messages that are fully compatible with the protocols run in the network. This mechanism ensures the best possible in-band connectivity between the controller and all network nodes, capitalizing on an interface which is already supported by network devices. Whisper’s internal algorithms further reduce the number of messages sent by the controller, to make the exerted control as lightweight as possible for the devices. Beyond detailing Whisper’s design, we discuss compelling use cases that Whisper unlocks, including rerouting around low-battery devices and providing runtime defense to jamming attacks. We also describe how to implement Whisper in current IoT open standards (RPL and 6TiSCH) without modifying IoT devices’ firmware. This shows that Whisper can implement an SDN-like control for distributed low power networks with no specific support for SDN, from legacy to next generation IoT devices. Our testbed experiments show that Whisper successfully controls the network in both the scheduling and routing plane, with significantly less overhead than other SDN-IoT solutions, no additional latency and no packet loss.
Design of Controllable Novel Piezoelectric Components for Microfluidic Applications
Authors: Cekas Elingas , Janusas Giedrius , Guobiene Asta , Palevicius Arvydas , Vilkauskas Andrius , Ponelyte Urbaite Sigita
Published: November 2018

This paper reviews recent investigations and achievements in the design of controllable functional components for improving microfluidic systems, its effectiveness, and functionality. The main purpose was to design novel microstructures with piezoelectric properties (microresonators), which enable one to control the effectiveness of fluid flow in micro-hydro-mechanical devices for biomedical/biochemical purposes. Controllable properties were obtained by incorporating different types of binders in a piezoelectric ceramic matrix (lead zirconate titanate): polyvinyl butyral (PVB), poly methyl methacrylate (PMMA), and polystyrene (PS). The change in chemical composition of PZT helps to manipulate the piezoelectric characteristics, surface morphology, mechanical properties, etc., of the designed microfluidic element with the microstructure in it.
Intersection Intelligence: Supporting Urban Platooning with Virtual Traffic Lights over Virtualized Intersection-Based Routing
Authors: Saiáns-Vázquez José Víctor , Ordóñez-Morales Esteban Fernando , López-Nores Martín , Blanco-Fernández Yolanda , Bravo-Torres Jack Fernando , Pazos-Arias José Juan , Gil-Solla Alberto , Ramos-Cabrer Manuel
Published: November 2018

The advent of the autonomous car is paving the road to the realization of ideas that will help optimize traffic flows, increase safety and reduce fuel consumption, among other advantages. We present one proposal to bring together Virtual Traffics Lights (VTLs) and platooning in urban scenarios, leaning on vehicle-to-vehicle (V2V) communication protocols that turn intersections into virtual containers of data. Newly-introduced protocols for the combined management of VTLs and platoons are validated by simulation, comparing a range of routing protocols for the vehicular networks with the baseline given by common deployments of traditional traffic lights ruled by state-of-the-art policies. The simulation results show that the combination of VTLs and platoons can achieve significant reductions in travel times and fuel consumption, provided that proper algorithms are used to handle the V2V communications.
Evaluation of Object Surface Edge Profiles Detected with a 2-D Laser Scanning Sensor
Authors: Yan Tingting , Wang Xiaochan , Zhu Heping , Ling Peter
Published: November 2018

Canopy edge profile detection is a critical component of plant recognition in variable-rate spray control systems. The accuracy of a high-speed 270° radial laser sensor was evaluated in detecting the surface edge profiles of six complex-shaped objects. These objects were toy balls with a pink smooth surface, light brown rectangular cardboard boxes, black and red texture surfaced basketballs, white smooth cylinders, and two different sized artificial plants. Evaluations included reconstructed three-dimensional (3-D) images for the object surfaces with the data acquired from the laser sensor at four different detection heights (0.25, 0.50, 0.75, and 1.00 m) above each object, five sensor travel speeds (1.6, 2.4, 3.2, 4.0, and 4.8 km h−1), and 8 to 15 horizontal distances to the sensor ranging from 0 to 3.5 m. Edge profiles of the six objects detected with the laser sensor were compared with images taken with a digital camera. The edge similarity score (ESS) was significantly affected by the horizontal distances of the objects, and the influence became weaker when the objects were placed closer to each other. The detection heights and travel speeds also influenced the ESS slightly. The overall average ESS ranged from 0.38 to 0.95 for all the objects under all the test conditions, thereby providing baseline information for the integration of the laser sensor into future development of greenhouse variable-rate spray systems to improve pesticide, irrigation, and nutrition application efficiencies through watering booms.
Validation of Finite Element Model by Smart Aggregate-Based Stress Monitoring
Authors: Zhang Haibin , Hou Shuang , Ou Jinping
Published: November 2018

Concrete compressive strength is an important parameter of material properties for assessing seismic performance of reinforced concrete (RC) structures, which has a certain level of uncertainty due to its inherent variability. In this paper, the method of concrete strength validation of finite element model using smart aggregate (SA)-based stress monitoring is proposed. The FE model was established using Open System for Earthquake Engineering Simulation (OpenSEES) platform. The concrete strengths obtained from the material test, peak stress of SA, and estimated concrete strength based on SA stress were employed in FE models. The lateral displacement monitored by Liner variable differential transformer and vertical axial load monitored by load cell in the experiment are applied in the model. By comparing the global response (i.e., lateral reaction force and hysteretic loop), local response (i.e., concrete stress, rebar strain, and cross-section moment) and corresponding root-mean-square error obtained from experiment and numerical analysis, the capabilities of validation of FE model using SA-based stress monitoring method were demonstrated.
Characterization of Sicilian Honeys Pollen Profiles Using a Commercial E-Tongue and Melissopalynological Analysis for Rapid Screening: A Pilot Study
Authors: Di Rosa Ambra R. , Marino Anna M. F. , Leone Francesco , Corpina Giuseppe G. , Giunta Renato P. , Chiofalo Vincenzo
Published: November 2018

Honey is usually classified as “unifloral” or “multifloral”, depending on whether a dominating pollen grain, originating from only one particular plant, or no dominant pollen type in the sample is found. Unifloral honeys are usually more expensive and appreciated than multifloral honeys, which highlights the importance of honey authenticity. Melissopalynological analysis is used to identify the botanical origin of honey, counting down the number of pollens grains of a honey sample, and calculating the respective percentages of the nectariferous pollens. In addition, sensory properties are also very important for honey characterization, and electronic senses emerged as useful tools for honey authentication. In this work, a comparison of the results obtained from melissopalynological analysis with those provided by a potentiometric electronic tongue is given, resulting in a 100% match between the two techniques.
Enhancement of Localization Systems in NLOS Urban Scenario with Multipath Ray Tracing Fingerprints and Machine Learning
Authors: N. de Sousa Marcelo , S. Thomä Reiner
Published: November 2018

A hybrid technique is proposed to enhance the localization performance of a time difference of arrival (TDOA) deployed in non-line-of-sight (NLOS) suburban scenario. The idea was to use Machine Learning framework on the dataset, produced by the ray tracing simulation, and the Channel Impulse Response estimation from the real signal received by each sensor. Conventional localization techniques mitigate errors trying to avoid NLOS measurements in processing emitter position, while the proposed method uses the multipath fingerprint information produced by ray tracing (RT) simulation together with calibration emitters to refine a Machine Learning engine, which gives an extra layer of information to improve the emitter position estimation. The ray-tracing fingerprints perform the target localization embedding all the reflection and diffraction in the propagation scenario. A validation campaign was performed and showed the feasibility of the proposed method, provided that the buildings can be appropriately included in the scenario description.
A 40-MHz Ultrasound Transducer with an Angled Aperture for Guiding Percutaneous Revascularization of Chronic Total Occlusion: A Feasibility Study
Authors: Lee Junsu , Chang Jin Ho
Published: November 2018

Complete blockage of a coronary artery, called chronic total occlusion (CTO), frequently occurs due to atherosclerosis. To reopen the obstructed blood vessels with a stent, guidewire crossing is performed with the help of angiography that can provide the location of CTO lesions and the image of guidewire tip. Since angiography is incapable of imaging inside a CTO lesion, the surgeons are blind during guidewire crossing. For this reason, the success rate of guidewire crossing relies upon the proficiency of the surgeon, which is considerably reduced from 69.0% to 32.5% if extensive calcification, not penetrated by a guidewire, exists in CTO lesions. In this paper, a recently developed 40-MHz forward-looking intravascular ultrasound (FL–IVUS) transducer to visualize calcification within CTO lesions is reported. This transducer consists of a single element angled aperture and a guidewire passage. The aperture is spherically deformed to have a focal length of 3 mm in order to improve spatial resolution of FL–IVUS images. The angle between the beam direction and the axis of rotation is designed to be 30° to effectively visualize calcification within a CTO lesion as well as the blood vessel wall. The experimental results demonstrated that the developed FL–IVUS transducer facilitates visualization of calcification within CTO lesions and makes it possible to help the surgeon make decisions about whether to push the guidewire in order to cross the lesion or to change the surgical procedure.
Correntropy Based Divided Difference Filtering for the Positioning of Ships
Authors: Liu Xi , Chen Badong , Wang Shiyuan , Du Shaoyi
Published: November 2018

In this paper, robust first and second-order divided difference filtering algorithms based on correntropy are proposed, which not only retain the advantages of divided difference filters, but also exhibit robustness in the presence of non-Gaussian noises, especially when the measurements are contaminated by heavy-tailed noises. The proposed filters are then applied to the problem of ship positioning. In order to improve the accuracy and reliability of ship positioning, the positioning method combines the Dead Reckoning (DR) algorithm and the Global Positioning System (GPS). Experimental results of an illustrative example show the superior performance of the new algorithms when applied to ship positioning.
Adaptive Dynamic Programming-Based Multi-Sensor Scheduling for Collaborative Target Tracking in Energy Harvesting Wireless Sensor Networks
Authors: Liu Fen , Xiao Wendong , Chen Shuai , Jiang Chengpeng
Published: November 2018

Collaborative target tracking is one of the most important applications of wireless sensor networks (WSNs), in which the network must rely on sensor scheduling to balance the tracking accuracy and energy consumption, due to the limited network resources for sensing, communication, and computation. With the recent development of energy acquisition technologies, the building of WSNs based on energy harvesting has become possible to overcome the limitation of battery energy in WSNs, where theoretically the lifetime of the network could be extended to infinite. However, energy-harvesting WSNs pose new technical challenges for collaborative target tracking on how to schedule sensors over the infinite horizon under the restriction on limited sensor energy harvesting capabilities. In this paper, we propose a novel adaptive dynamic programming (ADP)-based multi-sensor scheduling algorithm (ADP-MSS) for collaborative target tracking for energy-harvesting WSNs. ADP-MSS can schedule multiple sensors for each time step over an infinite horizon to achieve high tracking accuracy, based on the extended Kalman filter (EKF) for target state prediction and estimation. Theoretical analysis shows the optimality of ADP-MSS, and simulation results demonstrate its superior tracking accuracy compared with an ADP-based single-sensor scheduling scheme and a simulated-annealing based multi-sensor scheduling scheme.
Consequences of Increases in Wild Boar-Vehicle Accidents 2003–2016 in Sweden on Personal Injuries and Costs
Authors: Jägerbrand Annika K. , Gren Ing-Marie
Published: November 2018

This study examined whether the rising trends of wild boar (Sus scrofa)-vehicle accidents in Sweden are accompanied by a higher amount of personal injuries and costs. Temporal trends in accident frequencies and the number of persons injured in wild boar-vehicle accidents were examined for 2003–2016, and the cost of wild boar-vehicle accidents was calculated. Results show increases in the number of personal injuries, and increased costs, particularly after 2010–2012. The total number of wild boar accidents correlated with the number of injured persons as well as with the number of accidents with personal injuries. Approximately one person (1.13%) is injured per 100 wild boar-vehicle accidents, and approximately one accident per 200 wild boar-vehicle accidents will result in one or more persons with injuries (0.5%). However, most of the persons injured have slighter injuries. Although the number of wild boar-vehicle accidents and the number of persons injured in the accidents have increased, the frequency of accidents resulting in personal injuries is still at low levels in comparison with, for example, frequencies of personal injuries for moose accidents. The cost for wild boar-vehicle accidents has increased between 2003 to 2016 and is currently estimated to vary between approximately EUR 9.66–12.31 million per year.
Addressing Adverse Childhood Experiences: It’s All about Relationships
Authors: Zeanah Paula , Burstein Karen , Cartier Jeanne
Published: November 2018

Recognition that economic, environmental, and social adversity affects health is not new; adversity may result from social determinants such as poverty, community violence, or poor nutrition; from within the family/caregiving environment; or interactions between these complex environs. However, compelling new research demonstrating the profound impact of cumulative early adversity and toxic stress on development and adult health is leading to the mobilization of global prevention and intervention efforts to attain and assure better health for populations across the world. In this paper, we begin with a global population perspective on adversity and discuss priorities for global health. We then turn to studies of adverse childhood experiences to consider current understanding of how early experiences impact brain development and short- and long-term health. Factors that build resilience and buffer the effects of toxic stress and adversity are described, with emphasis on the foundationally protective role of safe and nurturing caregiving relationships. We discuss the implications of these findings in terms of community health and present a participatory research paradigm as a relationship-based method to improve community engagement in identifying and mitigating the impact of adverse childhood experiences on health.
Driver Use and Perceptions of Refueling Stations Near Freeways in a Developing Infrastructure for Alternative Fuel Vehicles
Authors: Kelley Scott
Published: November 2018

There is growing agreement that refueling station location plans that aim to encourage public adoption of alternative fuel vehicles (AFVs) should include sites near freeways in urban areas. Little is known, though, about the refueling behavior of early AFV adopters in these locations, which can involve travel on complex and congested roadways. To address this, an intercept travel survey collected data from 158 drivers of compressed natural gas (CNG) vehicles who refueled at CNG stations near freeways in greater Los Angeles, California. Results show that these stations met refueling demand from across the majority of the metropolitan area, and the distribution of local and distant refueling demand was consistent except for the downtown station. Drivers also considered these stations to be safe and accessible. Nearly half of drivers did not include another local stop in conjunction with their refueling trip that required leaving and returning to the freeway. These respondents refueled on longer trips with lower fuel tank levels, while refueling at the station that minimized deviation. Refueling downtown negatively influenced refueling in this manner. These findings should be considered when recommending station sites near freeways in future AFV infrastructure plans.
Achieving China’s Long-Term Carbon Emission Abatement Targets: A Perspective from Regional Disparity
Authors: Bian Yong , Yu Zhi , Zeng Xuelan , Feng Jingchun , He Chao
Published: November 2018

As China is the largest greenhouse gas emitter and has the characteristics of significant regional disparity, the issue of regional low-carbon development strategy is of vital importance for the achievement of the country’s long-term emission targets. This work focused on China’s long-term carbon emission abatement from the perspective of regional disparity. We firstly analyzed the national emission trajectories consistent with the current Intended Nationally Determined Contributions (INDCs), 2 °C, and 1.5 °C goals in two economic growth pathways by 2050 using a linear programming model, then classified the provinces into three categories, and compared results of different scenarios of regional disparity patterns, economic growth rates, and emission targets. Results showed that different regional patterns led to different required carbon reduction targets for all categories, and the regional emission reduction measures had to be stronger in a higher growth rate or a more stringent emission target, especially for the developed areas. A scheme of regionally coordinated low-carbon development was then recommended for the formulation of long-term regional emission targets, and carbon reduction strategies for categories were proposed in terms of energy mix optimization, industrial transformation, and technology innovation, which is of great policy implication for China in regional development and national emission targets enhancement.
A Local Gap in Sustainable Food Procurement: Organic Vegetables in Berlin’s School Meals
Authors: Braun Charis , Rombach Meike , Häring Anna , Bitsch Vera
Published: November 2018

Organic and local food plays an important role in the discussion of sustainable public procurement for school catering services. The present study investigates the value chain supplying school catering with organic produce, using the organic vegetable industry in the Berlin-Brandenburg region in Germany as an example. The qualitative case study employs a structuration theory approach to explore value chain actors’ perspectives and their practices. Data is collected by conducting 14 in-depth interviews with actors on different supply chain levels (farming, wholesale, and catering) and analyzed by means of qualitative content analysis. The results suggest that, while organic food is generally important in school catering in Berlin, locally produced organic vegetables play only a minor role. A constraining factor is the lack of incentives for the use of locally produced organic food in the procurement guidelines, combined with a very limited budget for sourcing. Also, there are no preprocessing facilities in the region, while work organization in school catering services depends heavily on preprocessed food. From a farmers’ perspective, focusing on process grade vegetables is rarely a common marketing strategy.
Non-Formal Environmental Education in a Vulnerable Region: Insights from a 20-Year Long Engagement in Petrópolis, Rio de Janeiro, Brazil
Authors: Calvente Atila , Kharrazi Ali , Kudo Shogo , Savaget Paulo
Published: November 2018

Environmental education is essential in the diffusion of the ethics, values, and skills that are critical to sustainable transformations. This paper presents the experience of non-formal environmental education approaches held in schools in the Petrópolis region of Rio de Janeiro, Brazil between 1997–2016. This paper adds to the literature on the relevant approaches and effectives of non-formal environmental education, especially in the vulnerable areas of low and middle-income regions that face critical environmental challenges. Specifically, to set up the context, this paper intends to firstly convey the commonly identified environmental sustainability challenges that the communities of the Petrópolis region are facing. Secondly, this report aims to convey key insights on how non-formal environmental education practices can strengthen gardening skills, environmental ethics, and sustainable food practices. These approaches have the potential to enhance the capacity of students toward sustainable transformations through encouraging them to be engaged with local social-environmental challenges. This paper adds new insights to the growing literature on non-formal environmental education, and it is hoped to inspire new educational approaches among sustainability educators.
Adsorption of Hexavalent Chromium Using Banana Pseudostem Biochar and Its Mechanism
Authors: Xu Shuang , Yu Weiguang , Liu Sen , Xu Congying , Li Jihui , Zhang Yucang
Published: November 2018

A low-cost biochar was prepared through slow pyrolysis of banana pseudostem biowaste at different temperatures, and characterized by surface area and porosity analysis, scanning electron microscopy (SEM), Fourier-transform infrared (FTIR) spectroscopy, and X-ray photoelectron spectroscopy (XPS). It was shown that the biochar prepared at low pyrolysis temperature was rich in oxygen-containing groups on the surface. Adsorption experiments revealed that the biochar prepared at 300 °C (BB300) was the best adsorbent for Cr(VI) with 125.44 mg/g maximum adsorption capacity at pH 2 and 25 °C. All the adsorption processes were well described by pseudo-second-order and Langmuir models, indicating a monolayer chemiadsorption. Furthermore, it was demonstrated that adsorption of Cr(VI) was mainly attributed to reduction of Cr(VI) to Cr(III) followed by ion exchange and complexation with the biochar.
A Bi-Objective Vehicle-Routing Problem with Soft Time Windows and Multiple Depots to Minimize the Total Energy Consumption and Customer Dissatisfaction
Authors: Wang Shijin , Wang Xiaodong , Liu Xin , Yu Jianbo
Published: November 2018

In recent years, the impact of the energy crisis and environment pollution on quality of life has forced industry to actively participate in the development of a sustainable society. Simultaneously, customer satisfaction improvement has always been a goal of businesses. It is recognized that efficient technologies and advanced methods can help transportation companies find a better balance between progress in energy saving and customer satisfaction. This paper investigates a bi-objective vehicle-routing problem with soft time windows and multiple depots, which aims to simultaneously minimize total energy consumption and customer dissatisfaction. To address the problem, we first develop mixed-integer programming. Then, an augmented ϵ -constraint method is adopted to obtain the optimal Pareto front for small problems. It is very time consuming for the augmented ϵ -constraint method to precisely solve even medium-sized problems. For medium- and large-sized problems, two Non-dominated Sorting Genetic Algorithm-II (NSGA-II)-based heuristics with different rules for generating initial solutions and offspring are designed. The performance of the proposed methods is evaluated by 100 randomly generated instances. Computational results show that the second NSGA-II-based heuristic is highly effective in finding approximate non-dominated solutions for small-size and medium-size instances, and the first one is performs better for the large-size instances.
Understanding Travelers’ Behavior for Sustainable Smart Tourism: A Technology Readiness Perspective
Authors: Pradhan Meena Kumari , Oh Jungjoo , Lee Hwansoo
Published: November 2018

Smart tourism has contributed to making people’s travels easier and more enjoyable, but sometimes has a negative impact on their travel experience. The challenges travelers face while using smart devices have not been researched in detail and are relatively unknown. While most studies have considered the usefulness of smart devices in tourism, negative perceptions of smart tourism have rarely been discussed. Thus, this study investigates travelers’ risk perceptions of smart tourism from a technology readiness perspective. It examines the impact of optimism, innovativeness, insecurity, and discomfort on travelers’ usage intentions of smart devices through their perceived risks and benefits. To test the proposed model and corresponding hypotheses, a partial least squares analysis was performed on data collected from 250 survey respondents. The results showed that the perceived benefits of smart devices had a significant effect on usage intentions of smart devices while traveling. It was also confirmed that the influence of perceived risks depends on the characteristics of travelers. This study is significant as it is the first empirical study applying the TRI (Technology Readiness Index) model that examines the negative effects of smart devices on tourists during travel. The results of this study provide meaningful insights into smart tourism to companies and governments.
The Hotel Industry in the Metropolitan Region of Rio De Janeiro: An Analysis of the Legacy of Accessibility in Civil Construction Projects Post Mega Events
Authors: Soares Carlos Alberto , Longo Orlando , Alcoforado Luciane , Ramos Thiago , Camello Noelle
Published: November 2018

This article aims to analyze the civil construction projects of the hotel industry in the Metropolitan Region of Rio de Janeiro, Brazil, through statistical modeling, regarding the issue of accessibility. The key point of the study was to diagnose how these hotel construction projects were prepared to receive disabled tourists during the period of Mega events. The methodology used is based on an analysis of the data obtained through the Inventory of the Tourist Offer of the State of Rio de Janeiro in the counties of Rio de Janeiro and Niterói, applied to the quantitative of approximately 400 hotel units. From the point of view of civil construction projects, an accurate diagnosis of accessibility was possible, pointing to the development of a benchmarking model. The relevance of the study is also to contribute to raising awareness of the tourist and civil engineering markets relating to people with disabilities or reduced mobility and the possibility of reversing the current scenario in Rio de Janeiro, since it can be emphasized that the investigated hotels do not show the necessary accessibility, due to the small number of hotels that reach the accessibility requirements of Brazilian Association of Technical Standards (ABNT NBR 9050: 2015). For civil construction, there is the accurate confirmation that the hotel industry of the Metropolitan Region is not accessible. For society in general, it has been observed that the Mega events that occurred in the city did not leave a legacy of accessibility.
Alternative Divulgation of the Local Sculptural Heritage: Construction of Paper Toys and Use of the Minecraft Video Game
Authors: Meier Cecile , Saorín Jose Luis , De la Torre-Cantero Jorge , Díaz-Alemán Manuel Drago
Published: November 2018

At present it is easy to digitalize sculptural heritage in 3D. Three-dimensional models allow for visualization of the work from all angles. The result can be seen in three-dimensional visors, in virtual reality, or by means of 3D-printed replicas. However, the recipient continues to be, as is also the case in books and videos, a passive spectator of the cultural patrimony. In order to promote participation and to increase interest in local heritage, alternative methods for promotion of the digital patrimony have been developed. In this article, two means of publicizing local (less-known) heritage in an active manner have been described. On the one hand, the transformation of 3D models into cut-outs (paper toys) where it is necessary to make the sculptures by hand, and on the other hand, the incorporation of the models into the video game Minecraft, an immersed 3D world which permits visiting or generating content. To validate these alternatives, two examples based on the sculptures of Santa Cruz de Tenerife (Spain) have been created, and they have been used in pilot studies in schools in order to obtain a first appraisal of user satisfaction.
Current Status and Willingness to Adopt Renewable Energy Technologies in Saudi Arabia
Authors: Mosly Ibrahim , Makki Anas A.
Published: November 2018

The purpose of this research study is to reveal the current status of and the willingness to adopt renewable energy technologies in the western region of Saudi Arabia. The main contribution of this work is the revealed levels of background knowledge presented on six types of renewable technologies, as well as five willingness perspectives on adoption by different sociodemographics. This was achieved following a quantitative research study to randomly collect cross-sectional data from 416 participants using a carefully designed questionnaire survey. Descriptive and inferential statistics were used to analyze the collected data. Results of the study provided and ranked the background knowledge of participants’ viewpoints on six renewable energy sources. It was revealed that education is paramount in increasing the level of awareness of renewable energy technologies. The results also ranked the five willingness perspectives to adopting renewable energy technologies. It was revealed that the economic factor is the main factor influencing the willingness to adoption. The analysis also showed that age was an important factor influencing the adoption of these technologies. This research study acts as a guide assisting energy policy-makers, government agencies, and investors in designing better-targeted public awareness and marketing campaigns on renewable energy technologies. This is in turn will assist in achieving the energy efficiency and production targets of Vision 2030 in Saudi Arabia.