bluuebunny/crossref_metadata_2025 huggingface dataset:
Linking the Remote Sensing of Geodiversity and Traits Relevant to Biodiversity—Part II: Geomorphology, Terrain and Surfaces
Authors: Lausch Angela , Schaepman Michael E. , Skidmore Andrew K. , Truckenbrodt Sina C. , Hacker Jörg M. , Baade Jussi , Bannehr Lutz , Borg Erik , Bumberger Jan , Dietrich Peter , Gläßer Cornelia , Haase Dagmar , Heurich Marco , Jagdhuber Thomas , Jany Sven , Krönert Rudolf , Möller Markus , Mollenhauer Hannes , Montzka Carsten , Pause Marion , Rogass Christian , Salepci Nesrin , Schmullius Christiane , Schrodt Franziska , Schütze Claudia , Schweitzer Christian , Selsam Peter , Spengler Daniel , Vohland Michael , Volk Martin , Weber Ute , Wellmann Thilo , Werban Ulrike , Zacharias Steffen , Thiel Christian
Published: November 2020

The status, changes, and disturbances in geomorphological regimes can be regarded as controlling and regulating factors for biodiversity. Therefore, monitoring geomorphology at local, regional, and global scales is not only necessary to conserve geodiversity, but also to preserve biodiversity, as well as to improve biodiversity conservation and ecosystem management. Numerous remote sensing (RS) approaches and platforms have been used in the past to enable a cost-effective, increasingly freely available, comprehensive, repetitive, standardized, and objective monitoring of geomorphological characteristics and their traits. This contribution provides a state-of-the-art review for the RS-based monitoring of these characteristics and traits, by presenting examples of aeolian, fluvial, and coastal landforms. Different examples for monitoring geomorphology as a crucial discipline of geodiversity using RS are provided, discussing the implementation of RS technologies such as LiDAR, RADAR, as well as multi-spectral and hyperspectral sensor technologies. Furthermore, data products and RS technologies that could be used in the future for monitoring geomorphology are introduced. The use of spectral traits (ST) and spectral trait variation (STV) approaches with RS enable the status, changes, and disturbances of geomorphic diversity to be monitored. We focus on the requirements for future geomorphology monitoring specifically aimed at overcoming some key limitations of ecological modeling, namely: the implementation and linking of in-situ, close-range, air- and spaceborne RS technologies, geomorphic traits, and data science approaches as crucial components for a better understanding of the geomorphic impacts on complex ecosystems. This paper aims to impart multidimensional geomorphic information obtained by RS for improved utilization in biodiversity monitoring.
mGEODAR—A Mobile Radar System for Detection and Monitoring of Gravitational Mass-Movements
Authors: Köhler Anselm , Lok Lai Bun , Felbermayr Simon , Peters Nial , Brennan Paul V. , Fischer Jan-Thomas
Published: November 2020

Radar measurements of gravitational mass-movements like snow avalanches have become increasingly important for scientific flow observations, real-time detection and monitoring. Independence of visibility is a main advantage for rapid and reliable detection of those events, and achievable high-resolution imaging proves invaluable for scientific measurements of the complete flow evolution. Existing radar systems are made for either detection with low-resolution or they are large devices and permanently installed at test-sites. We present mGEODAR, a mobile FMCW (frequency modulated continuous wave) radar system for high-resolution measurements and low-resolution gravitational mass-movement detection and monitoring purposes due to a versatile frequency generation scheme. We optimize the performance of different frequency settings with loop cable measurements and show the freespace range sensitivity with data of a car as moving point source. About 15 dB signal-to-noise ratio is achieved for the cable test and about 5 dB or 10 dB for the car in detection and research mode, respectively. By combining continuous recording in the low resolution detection mode with real-time triggering of the high resolution research mode, we expect that mGEODAR enables autonomous measurement campaigns for infrastructure safety and mass-movement research purposes in rapid response to changing weather and snow conditions.
A Novel Framework Using Deep Auto-Encoders Based Linear Model for Data Classification
Authors: Karim Ahmad M. , Kaya Hilal , Güzel Mehmet Serdar , Tolun Mehmet R. , Çelebi Fatih V. , Mishra Alok
Published: November 2020

This paper proposes a novel data classification framework, combining sparse auto-encoders (SAEs) and a post-processing system consisting of a linear system model relying on Particle Swarm Optimization (PSO) algorithm. All the sensitive and high-level features are extracted by using the first auto-encoder which is wired to the second auto-encoder, followed by a Softmax function layer to classify the extracted features obtained from the second layer. The two auto-encoders and the Softmax classifier are stacked in order to be trained in a supervised approach using the well-known backpropagation algorithm to enhance the performance of the neural network. Afterwards, the linear model transforms the calculated output of the deep stacked sparse auto-encoder to a value close to the anticipated output. This simple transformation increases the overall data classification performance of the stacked sparse auto-encoder architecture. The PSO algorithm allows the estimation of the parameters of the linear model in a metaheuristic policy. The proposed framework is validated by using three public datasets, which present promising results when compared with the current literature. Furthermore, the framework can be applied to any data classification problem by considering minor updates such as altering some parameters including input features, hidden neurons and output classes.
Damage Proxy Map of the Beirut Explosion on 4th of August 2020 as Observed from the Copernicus Sensors
Authors: Agapiou Athos
Published: November 2020

On the 4th of August 2020, a massive explosion occurred in the harbor area of Beirut, Lebanon, killing more than 100 people and damaging numerous buildings in its proximity. The current article aims to showcase how open access and freely distributed satellite data, such as those of the Copernicus radar and optical sensors, can deliver a damage proxy map of this devastating event. Sentinel-1 radar images acquired just prior (the 24th of July 2020) and after the event (5th of August 2020) were processed and analyzed, indicating areas with significant changes of the VV (vertical transmit, vertical receive) and VH (vertical transmit, horizontal receive) backscattering signal. In addition, an Interferometric Synthetic Aperture Radar (InSAR) analysis was performed for both descending (31st of July 2020 and 6th of August 2020) and ascending (29th of July 2020 and 10th of August 2020) orbits of Sentinel-1 images, indicating relative small ground displacements in the area near the harbor. Moreover, low coherence for these images is mapped around the blast zone. The current study uses the Hybrid Pluggable Processing Pipeline (HyP3) cloud-based system provided by the Alaska Satellite Facility (ASF) for the processing of the radar datasets. In addition, medium-resolution Sentinel-2 optical data were used to support thorough visual inspection and Principal Component Analysis (PCA) the damage in the area. While the overall findings are well aligned with other official reports found on the World Wide Web, which were mainly delivered by international space agencies, those reports were generated after the processing of either optical or radar datasets. In contrast, the current communication showcases how both optical and radar satellite data can be parallel used to map other devastating events. The use of open access and freely distributed Sentinel mission data was found very promising for delivering damage proxies maps after devastating events worldwide.
Machine Learning Improvements to Human Motion Tracking with IMUs
Authors: Ribeiro Pedro Manuel Santos , Matos Ana Clara , Santos Pedro Henrique , Cardoso Jaime S.
Published: November 2020

Inertial Measurement Units (IMUs) have become a popular solution for tracking human motion. The main problem of using IMU data for deriving the position of different body segments throughout time is related to the accumulation of the errors in the inertial data. The solution to this problem is necessary to improve the use of IMUs for position tracking. In this work, we present several Machine Learning (ML) methods to improve the position tracking of various body segments when performing different movements. Firstly, classifiers were used to identify the periods in which the IMUs were stopped (zero-velocity detection). The models Random Forest, Support Vector Machine (SVM) and neural networks based on Long-Short-Term Memory (LSTM) layers were capable of identifying those periods independently of the motion and body segment with a substantially higher performance than the traditional fixed-threshold zero-velocity detectors. Afterwards, these techniques were combined with ML regression models based on LSTMs capable of estimating the displacement of the sensors during periods of movement. These models did not show significant improvements when compared with the more straightforward double integration of the linear acceleration data with drift removal for translational motion estimate. Finally, we present a model based on LSTMs that combined simultaneously zero-velocity detection with the translational motion of sensors estimate. This model revealed a lower average error for position tracking than the combination of the previously referred methodologies.
LiDAR Point Cloud Recognition and Visualization with Deep Learning for Overhead Contact Inspection
Authors: Tu Xiaohan , Xu Cheng , Liu Siping , Lin Shuai , Chen Lipei , Xie Guoqi , Li Renfa
Published: November 2020

As overhead contact (OC) is an essential part of power supply systems in high-speed railways, it is necessary to regularly inspect and repair abnormal OC components. Relative to manual inspection, applying LiDAR (light detection and ranging) to OC inspection can improve efficiency, accuracy, and safety, but it faces challenges to efficiently and effectively segment LiDAR point cloud data and identify catenary components. Recent deep learning-based recognition methods are rarely employed to recognize OC components, because they have high computational complexity, while their accuracy needs to be improved. To track these problems, we first propose a lightweight model, RobotNet, with depthwise and pointwise convolutions and an attention module to recognize the point cloud. Second, we optimize RobotNet to accelerate its recognition speed on embedded devices using an existing compilation tool. Third, we design software to facilitate the visualization of point cloud data. Our software can not only display a large amount of point cloud data, but also visualize the details of OC components. Extensive experiments demonstrate that RobotNet recognizes OC components more accurately and efficiently than others. The inference speed of the optimized RobotNet increases by an order of magnitude. RobotNet has lower computational complexity than other studies. The visualization results also show that our recognition method is effective.
Artificial Intelligence-Based Optimal Grasping Control
Authors: Kim Dongeon , Lee Jonghak , Chung Wan-Young , Lee Jangmyung
Published: November 2020

A new tactile sensing module was proposed to sense the contact force and location of an object on a robot hand, which was attached on the robot finger. Three air pressure sensors are installed at the tip of the finger to detect the contacting force at the points. To obtain a nominal contact force at the finger from data from the three air pressure sensors, a force estimation was developed based upon the learning of a deep neural network. The data from the three air pressure sensors were utilized as inputs to estimate the contact force at the finger. In the tactile module, the arrival time of the air pressure sensor data has been utilized to recognize the contact point of the robot finger against an object. Using the three air pressure sensors and arrival time, the finger location can be divided into 3 × 3 block locations. The resolution of the contact point recognition was improved to 6 × 4 block locations on the finger using an artificial neural network. The accuracy and effectiveness of the tactile module were verified using real grasping experiments. With this stable grasping, an optimal grasping force was estimated empirically with fuzzy rules for a given object.
Enhancements and Challenges in CoAP—A Survey
Authors: Tariq Muhammad Ashar , Khan Murad , Raza Khan Muhammad Toaha , Kim Dongkyun
Published: November 2020

The Internet of Engineering Task (IETF) developed a lighter application protocol (Constrained Application Protocol (CoAP)) for the constrained IoT devices operating in lossy environments. Based on UDP, CoAP is a lightweight and efficient protocol compared to other IoT protocols such as HTTP, MQTT, etc. CoAP also provides reliable communication among nodes in wireless sensor networks in addition to features such as resource observation, resource discovery, congestion control, etc. These capabilities of CoAP have enabled the implementation of CoAP in various domains ranging from home automation to health management systems. The use of CoAP has highlighted its shortcomings over the time. To overcome shortcomings of CoAP, numerous enhancements have been made in basic CoAP architecture. This survey highlights the shortcomings of basic CoAP architecture and enhancements made in it throughout the time. Furthermore, existing challenges and issue in the current CoAP architecture are also discussed. Finally, some applications with CoAP implementation are mentioned in order to realize the viability of CoAP in real world use cases.
Use of Functional Linear Models to Detect Associations between Characteristics of Walking and Continuous Responses Using Accelerometry Data
Authors: Fadel William F. , Urbanek Jacek K. , Glynn Nancy W. , Harezlak Jaroslaw
Published: November 2020

Various methods exist to measure physical activity. Subjective methods, such as diaries and surveys, are relatively inexpensive ways of measuring one’s physical activity; however, they are prone to measurement error and bias due to self-reporting. Wearable accelerometers offer a non-invasive and objective measure of one’s physical activity and are now widely used in observational studies. Accelerometers record high frequency data and each produce an unlabeled time series at the sub-second level. An important activity to identify from the data collected is walking, since it is often the only form of activity for certain populations. Currently, most methods use an activity summary which ignores the nuances of walking data. We propose methodology to model specific continuous responses with a functional linear model utilizing spectra obtained from the local fast Fourier transform (FFT) of walking as a predictor. Utilizing prior knowledge of the mechanics of walking, we incorporate this as additional information for the structure of our transformed walking spectra. The methods were applied to the in-the-laboratory data obtained from the Developmental Epidemiologic Cohort Study (DECOS).
The Importance of Respiratory Rate Monitoring: From Healthcare to Sport and Exercise
Authors: Nicolò Andrea , Massaroni Carlo , Schena Emiliano , Sacchetti Massimo
Published: November 2020

Respiratory rate is a fundamental vital sign that is sensitive to different pathological conditions (e.g., adverse cardiac events, pneumonia, and clinical deterioration) and stressors, including emotional stress, cognitive load, heat, cold, physical effort, and exercise-induced fatigue. The sensitivity of respiratory rate to these conditions is superior compared to that of most of the other vital signs, and the abundance of suitable technological solutions measuring respiratory rate has important implications for healthcare, occupational settings, and sport. However, respiratory rate is still too often not routinely monitored in these fields of use. This review presents a multidisciplinary approach to respiratory monitoring, with the aim to improve the development and efficacy of respiratory monitoring services. We have identified thirteen monitoring goals where the use of the respiratory rate is invaluable, and for each of them we have described suitable sensors and techniques to monitor respiratory rate in specific measurement scenarios. We have also provided a physiological rationale corroborating the importance of respiratory rate monitoring and an original multidisciplinary framework for the development of respiratory monitoring services. This review is expected to advance the field of respiratory monitoring and favor synergies between different disciplines to accomplish this goal.
Time-Domain Blind ICI Compensation in Coherent Optical FBMC/OQAM System
Authors: Wu Binqi , Lu Jin , Gao Mingyi , Ren Hongliang , Le Zichun , Qin Yali , Guo Shuqin , Hu Weisheng
Published: November 2020

A blind discrete-cosine-transform-based phase noise compensation (BD-PNC) is proposed to compensate the inter-carrier-interference (ICI) in the coherent optical offset-quadrature amplitude modulation (OQAM)-based filter-bank multicarrier (CO-FBMC/OQAM) transmission system. Since the phase noise sample can be approximated by an expansion of the discrete cosine transform (DCT) in the time-domain, a time-domain compensation model is built for the transmission system. According to the model, phase noise compensation (PNC) depends only on its DCT coefficients. The common phase error (CPE) compensation is firstly performed for the received signal. After that, a pre-decision is made on a part of compensated signals with low decision error probability, and the pre-decision results are used as the estimated values of transmitted signals to calculate the DCT coefficients. Such a partial pre-decision process reduces not only decision error but also the complexity of the BD-PNC method while keeping almost the same performance as in the case of the pre-decision of all compensated signals. Numerical simulations are performed to evaluate the performance of the proposed scheme for a 30 GBaud CO-FBMC/OQAM system. The simulation results show that its bit error rate (BER) performance is improved by more than one order of magnitude through the mitigation of the ICI in comparison with the traditional blind PNC scheme only aiming for CPE compensation.
Semantic Distributed Data for Vehicular Networks Using the Inter-Planetary File System
Authors: Ortega Victor , Monserrat Jose F.
Published: November 2020

Vehicular networks provide means to distribute data among intelligent vehicles, increasing their efficiency and the safety of their occupants. While connected to these networks, vehicles have access to various kinds of information shared by other vehicles and road-side units (RSUs). This information includes helpful resources, such as traffic state or remote sensors. An efficient and fast system to get access to this information is important but unproductive if the data are not appropriately structured, accessible, and easy to process. This paper proposes the creation of a semantic distributed network using content-addressed networking and peer-to-peer (P2P) connections. In this open and collaborative network, RSUs and vehicles use ontologies to semantically represent information and facilitate the development of intelligent autonomous agents capable of navigating and processing the shared data. In order to create this P2P network, this paper makes use of the Inter-Planetary File System (IPFS), an open source solution that provides secure, reliable, and efficient content-addressed distributed storage over standard IP networks using the new QUIC protocol. This paper highlights the feasibility of this proposal and compares it with the state-of-the-art. Results show that IPFS is a promising technology that offers a great balance between functionality, performance, and security.
Low-Power RFED Wake-Up Receiver Design for Low-Cost Wireless Sensor Network Applications
Authors: Galante-Sempere David , Ramos-Valido Dailos , Lalchand Khemchandani Sunil , del Pino Javier
Published: November 2020

The development of wake-up receivers (WuR) has recently received a lot of interest from both academia and industry researchers, primarily because of their major impact on the improvement of the performance of wireless sensor networks (WSNs). In this paper, we present the development of three different radiofrequency envelope detection (RFED) based WuRs operating at the 868 MHz industrial, scientific and medical (ISM) band. These circuits can find application in densely populated WSNs, which are fundamental components of Internet-of-Things (IoT) or Internet-of-Everything (IoE) applications. The aim of this work is to provide circuits with high integrability and a low cost-per-node, so as to facilitate the implementation of sensor nodes in low-cost IoT applications. In order to demonstrate the feasibility of implementing a WuR with commercially available off-chip components, the design of an RFED WuR in a PCB mount is presented. The circuit is validated in a real scenario by testing the WuR in a system with a pattern recognizer (AS3933), an MCU (MSP430G2553 from TI), a transceiver (CC1101 from TI) and a T/R switch (ADG918). The WuR has no active components and features a sensitivity of about −50 dBm, with a total size of 22.5 × 51.8 mm2. To facilitate the integration of the WuR in compact systems and low-cost applications, two designs in a commercial UMC 65 nm CMOS process are also explored. Firstly, an RFED WuR with integrated transformer providing a passive voltage gain of 18 dB is demonstrated. The circuit achieves a sensitivity as low as −62 dBm and a power consumption of only 528 nW, with a total area of 634 × 391 μm2. Secondly, so as to reduce the area of the circuit, a design of a tuned-RF WuR with integrated current-reuse active inductor is presented. In this case, the WuR features a sensitivity of −55 dBm with a power consumption of 43.5 μW and a total area of 272 × 464 μm2, obtaining a significant area reduction at the expense of higher power consumption. The alternatives presented show a very low die footprint with a performance in line with most of the state-of-the-art contributions, making the topologies attractive in scenarios where high integrability and low cost-per-node are necessary.
IR Imaging of Solid Lubricant Coatings on Concealed/Disjointed Surfaces for Transparent Polymer Delivery Device Applications
Authors: Walsh Anton , Rebrova Natalia , Darby Steven , Barton Killian , Wolfe Raymond , Buckley Finbarr , Lewis Liam , McAuliffe Michael
Published: November 2020

Transparent polymer delivery devices often contain a solid lubricant coating on a stronger bulk polymer. The distribution of lubricant coating must be monitored for device optimisation appraisals and to ensure consistency during mass production. However, coating evaluation is difficult to perform as surfaces are often concealed and/or disjointed. Dye stain analysis, which is destructive and time-consuming, is the current industry standard. We present a prototype IR transmission microscope to evaluate micron-level coating coverage of polyurethane and/or polyvinylpyrrolidone on a poly(propylene)-based delivery device. The device has a common industrial configuration, containing a duct and bevel. Inferred absorption of the coating was used to identify coating coverage and a multivariate analysis was used to remove the effects of absorption and scattering by the bulk. Coverage on concealed and disjointed surfaces was imaged and evaluated from a single camera viewpoint and ≈50 μm defects were detectable. The industrial applicability of the prototype was demonstrated using comparisons with dye stain analysis by estimating water dilution of coating and identifying artifacts in coating, which may indicate machine malfunction. The sensitivity and speed of the IR technique makes it a favourable alternative to the current industry standard.
Correction: Seno, A.H.; Ferri Aliabadi, M.H. Impact Localisation in Composite Plates of Different Stiffness Impactors under Simulated Environmental and Operational Conditions. Sensors 2019, 19, 3659
Authors: Seno Aldyandra Hami , Aliabadi M.H. Ferri
Published: November 2020

The author wishes to make the following correction to this paper [...]
Blind Estimation Methods for BPSK Signal Based on Duffing Oscillator
Authors: Wang Ke , Yan Xiaopeng , Zhu Zhiqiang , Hao Xinhong , Li Ping , Yang Qian
Published: November 2020

To realize the blind estimation of binary phase shift keying (BPSK) signal, this paper describe a new relational expression among the state of Duffing oscillator excited by BPSK signal, the pseudo-random code of BPSK signal, and the difference frequency between the to-be-detect signal and internal drive force signal of Duffing oscillator. Two output characteristics of Duffing oscillators excited by BPSK signals named implied periodicity and pilot frequency array synchronization are presented according to the different chaotic states of Duffing oscillator. Then two blind estimation methods for the carrier frequency and pseudo-random sequence of the BPSK signal are proposed based on these two characteristics, respectively. These methods are shown to have a significant effect on the parameter estimation of BPSK signals with no prior knowledge, even at very low signal-to-noise ratios (SNRs).
A Hybrid Recommendation System for Marine Science Observation Data Based on Content and Literature Filtering
Authors: Song Xiaoyang , Guo Yonggang , Chang Yongguo , Zhang Fei , Tan Junfeng , Yang Jie , Shi Xiaolong
Published: November 2020

With the development of ocean exploration technology and the rapid growth in the amount of marine science observation data, people are faced with a great challenge to identify valuable data from the massive ocean observation data. A recommendation system is an effective method to improve retrieval capabilities to help users obtain valuable data. The two most popular recommendation algorithms are collaborative filtering algorithms and content-based filtering algorithms, which may not work well for marine science observation data given the complexity of data attributes and lack of user information. In this study, an approach was proposed based on data similarity and data correlation. Data similarity was calculated by analyzing the subject, source, spatial, and temporal attributes to obtain the recommendation list. Then, data correlation was calculated based on the literature on marine science data and ranking of the recommendation list to obtain the re-rank recommendation list. The approach was tested by simulated datasets collected from multiple marine data sharing websites, and the result suggested that the proposed method exhibits better effectiveness.
Effect of Filtered Back-Projection Filters to Low-Contrast Object Imaging in Ultra-High-Resolution (UHR) Cone-Beam Computed Tomography (CBCT)
Authors: Choi Sunghoon , Seo Chang-Woo , Cha Bo Kyung
Published: November 2020

In this study, the effect of filter schemes on several low-contrast materials was compared using standard and ultra-high-resolution (UHR) cone-beam computed tomography (CBCT) imaging. The performance of the UHR-CBCT was quantified by measuring the modulation transfer function (MTF) and the noise power spectrum (NPS). The MTF was measured at the radial location around the cylindrical phantom, whereas the NPS was measured in the eight different homogeneous regions of interest. Six different filter schemes were designed and implemented in the CT sinogram from each imaging configuration. The experimental results indicated that the filter with smaller smoothing window preserved the MTF up to the highest spatial frequency, but larger NPS. In addition, the UHR imaging protocol provided 1.77 times better spatial resolution than the standard acquisition by comparing the specific spatial frequency (f50) under the same conditions. The f50s with the flat-top window in UHR mode was 1.86, 0.94, 2.52, 2.05, and 1.86 lp/mm for Polyethylene (Material 1, M1), Polystyrene (M2), Nylon (M3), Acrylic (M4), and Polycarbonate (M5), respectively. The smoothing window in the UHR protocol showed a clearer performance in the MTF according to the low-contrast objects, showing agreement with the relative contrast of materials in order of M3, M4, M1, M5, and M2. In conclusion, although the UHR-CBCT showed the disadvantages of acquisition time and radiation dose, it could provide greater spatial resolution with smaller noise property compared to standard imaging; moreover, the optimal window function should be considered in advance for the best UHR performance.
Challenges in Resource-Constrained IoT Devices: Energy and Communication as Critical Success Factors for Future IoT Deployment
Authors: Pereira Felisberto , Correia Ricardo , Pinho Pedro , Lopes Sérgio I. , Carvalho Nuno Borges
Published: November 2020

Internet of Things (IoT) has been developing to become a free exchange of useful information between multiple real-world devices. Already spread all over the world in the most varied forms and applications, IoT devices need to overcome a series of challenges to respond to the new requirements and demands. The main focus of this manuscript is to establish good practices for the design of IoT devices (i.e., smart devices) with a focus on two main design challenges: power and connectivity. It groups IoT devices in passive, semi-passive, and active, giving details on multiple research topics. Backscatter communication, Wireless Power Transfer (WPT), Energy Harvesting (EH), chipless devices, Simultaneous Wireless Information and Power Transfer (SWIPT), and Wake-Up Radio (WUR) are some examples of the technologies that will be explored in this work.
High-Sensitivity Cuboid Interferometric Fiber-Optic Hydrophone Based on Planar Rectangular Film Sensing
Authors: Wang Wenrui , Pei Yeye , Ye Lingyun , Song Kaichen
Published: November 2020

Interferometric fiber-optic hydrophones are an important means in the field of underwater acoustic detection. The design of the hydrophone sensor head is the key technology related to its detection sensitivity. In this paper, a high-sensitivity cuboid interferometric fiber-optic hydrophone based on planar rectangular film sensing is proposed, and the sensitivity of the sensor is compared with that of the widely used air-backed mandrel hydrophone under the same conditions. The acoustic characteristic models of the two types of sensors were established by theoretical calculation and simulation analysis to obtain the theoretical pressure sensitivity. Some experiments were performed to examine the theory and design. According to the experiment results, the mean phase sensitivity of the mandrel type was −112.85 dB re 1 rad/μPa in the operating frequency range of 10–300 Hz, and that of the cuboid type was −84.50 dB re 1 rad/μPa. The latter was 28.35 dB higher than the former was. These results are useful for improving hydrophone sensitivity.
Reactive Navigation on Natural Environments by Continuous Classification of Ground Traversability
Authors: Martínez Jorge L. , Morales Jesús , Sánchez Manuel , Morán Mariano , Reina Antonio J. , Fernández-Lozano J. Jesús
Published: November 2020

Reactivity is a key component for autonomous vehicles navigating on natural terrains in order to safely avoid unknown obstacles. To this end, it is necessary to continuously assess traversability by processing on-board sensor data. This paper describes the case study of mobile robot Andabata that classifies traversable points from 3D laser scans acquired in motion of its vicinity to build 2D local traversability maps. Realistic robotic simulations with Gazebo were employed to appropriately adjust reactive behaviors. As a result, successful navigation tests with Andabata using the robot operating system (ROS) were performed on natural environments at low speeds.
Improving Health Professionals’ Involvement Whilst Sustaining Work–Life Balance: Evidence from an Empirical Analysis
Authors: Palumbo Rocco
Published: November 2020

Most sustainability studies applied to healthcare primarily focus on external viability. In particular, they look at the ability of healthcare institutions to establish an economic, environmental, social, and political consonance with their context. Conversely, limited attention has been paid to issues related to internal sustainability. The article discusses health professionals’ involvement as a human resource management practice which contributes to the viability of healthcare organizations. A sequential mediation analysis was designed to shed light on the effects of employees’ involvement on work–life balance, which is an essential ingredient of the recipe for internal sustainability. The study findings suggest that health professionals’ involvement may determine an intensification and an extensification of work efforts, which undermine their work–life balance. Nevertheless, the implications of employees’ involvement on work–life balance are positively and significantly mediated by supportive relationships at work and positive organizational climate. From this standpoint, health professionals’ involvement may act as an effective strategy to enhance the internal sustainability of health care organizations if matched with better relationships with supervisors and improved organizational climate. Whilst calling for further research to enlighten issues and challenges related to internal sustainability, the article stresses that health professionals’ involvement should be paired with an improvement of the organizational climate to contribute to an increased viability of health care institutions.
The Use of a Cooperative-Learning Activity with University Students: A Gender Experience
Authors: Baena-Morales Salvador , Jerez-Mayorga Daniel , Fernández-González Francisco Tomás , López-Morales Juan
Published: November 2020

The UN Sustainable Development Goals (SDG) show how education is essential for creating values in students. In particular, SDG 4 (quality education) and SDG 5 (gender equality) indicate how co-education should be a sustainable benchmark. Co-educational methodologies have been studied for decades. Among them, cooperative learning is considered a valid technique for developing social relations and competences. This study aims to describe and characterize the gender differences between university students regarding their impressions and behaviors when working cooperatively. One hundred and seventy-seven university students (98 women and 79 men), from Physical Education and Primary Education degree courses, worked with Aronson’s Jigsaw technique. After its completion, they completed a questionnaire to analyze cooperative work in higher education (ACOES). The results are organized into seven dimensions. The main gender differences found show that women gave a higher evaluation to relating cooperative learning to future teaching roles (p = 0.017) and to understanding the need for cooperative tasks (p = 0.035). Additionally, female students prefer groups to be organized according to academic criteria and that they should remain stable throughout the academic period. Both genders value Aronson’s Jigsaw as a good method for developing social competences, although they are more neutral when considering it effective at improving academic performance. These findings help to generate a gender-cooperation profile that will enable future research to discuss results more accurately.
Defining Smart Mobility Service Levels via Text Mining
Authors: So Jaehyun (Jason) , An Hyunju , Lee Changju
Published: November 2020

The concept of smart mobility depends on a country’s or city’s visions and surroundings, such as traffic issues and available transportation modes. This study, therefore, proposes a clear and consistent set of definitions for smart mobility, in the context of past, present, and future, based on investigations of smart mobility practices in South Korea and overseas. In addition, smart mobility definitions are collected from various written sources and analyzed via text mining to define levels of smart mobility beyond the present service level. This study therefore defines smart mobility in six stages: level 0, base infrastructure; level 1, individual digitization; level 2, partial integration; level 3, full integration; level 4, personalized integration; and level 5, mobility transformation. The definition of each stage includes the scope of transportation modes to be integrated, required technology level, mobility operations, and user convenience. This definition of smart mobility by stage will be beneficial for setting the targeted levels of smart mobility services in projects and for setting goals not only in the present context but also for the future of smart mobility, which will be utilized as a roadmap for the implementation of smart mobility in many countries and cities.
A Systematic Review for Urban Regeneration Effects Analysis in Urban Cores
Authors: Tiboni Michela , Botticini Francesco , Sousa Sílvia , Jesus-Silva Natacha
Published: November 2020

In this article, we aim to promote a methodology to analyze the effects of urban regeneration in historical sites. Different case studies are observed in depth, and they allow us to understand certain aspects concerning ex-post and ex-ante assessments. This methodology, which is supported by Geographic Information System (GIS) software and an online database, is based on different phases: the first is the quantification of the resources employed within the process, giving attention to the policies that are the basis for social and environmental changes. Then, the analysis moves to the effects of the interventions. In particular, the goal of the methodology was to understand how different urban operations can contribute to creating public value, and importance was given to the available tools for public bodies to develop partnerships and to capture that value. With the ex-post assessment, it was feasible to compare the situations before and after the realization of the projects, whereas, with the ex-ante assessment, it was viable to assess different possible development scenarios and compare them with the baseline of the current situation. The methodology was tested for the ex-post assessment case study of the city of Porto (PT) and for the ex-ante assessment case study of the city of Brescia (IT).
ESG (Environmental, Social and Governance) Performance and Board Gender Diversity: The Moderating Role of CEO Duality
Authors: Romano Mauro , Cirillo Alessandro , Favino Christian , Netti Antonio
Published: November 2020

According to the 2030 Agenda, gender equality plays a central role in achieving social development, expanding economic growth and improving business performance. From this perspective, many studies claim that a more balanced presence of women on Board of Directors (BoD) could have a positive impact on firms’ financial performance, but the effect of such diversity on sustainability performance is still underexplored. The purpose of this paper is to investigate how gender composition of BoD affects the corporate sustainability practices. In particular, we focused on the relationship between board gender composition and ESG (Environmental, Social and Governance) performance, by verifying if and to what extent there is a moderation effect due to the presence of CEO duality. We used the ESG index, provided by Bloomberg Data Service, as a proxy of sustainability performance and the Blau index as a measure of gender diversity in the BoD. The empirical analysis was carried out on a sample of Italian non-financial companies listed on Mercato Telematico Azionario (MTA) and includes a total of 128 observations. Results has shown that a greater gender diversity on BoD has an overall positive influence on ESG performance, while CEO duality negatively moderates the foregoing relationship.
Using a General Ordered Logit Model to Explain the Influence of Hotel Facilities, General and Sustainability-Related, on Customer Ratings
Authors: Abrudan Ioana-Nicoleta , Pop Ciprian-Marcel , Lazăr Paul-Sorin
Published: November 2020

The hotel market has become extremely competitive over the past years. Hotels try to differentiate themselves through their services and facilities. To make the best choice when searching for accommodation, guests increasingly use rating systems of booking sites. Using an ordered logit model (OLM), we identify, in our study, a sample that comprises of 635 hotels from Romania. These are the hotel facilities that significantly influence customer review scores (as an expression of customer satisfaction) on booking.com, the most widespread rating system. We also identify whether their impact on intervals of satisfaction levels vary. Some explanatory variables invalidate the Brant test for proportional odds assumption. Thus, for the final estimates, we use a generalized ordered logit model (GOLOGIT). The results show that food-related facilities, restaurants, and complimentary breakfasts, are very significant for customer ratings. Relevant hotel common facilities are the pool and parking spaces, while for the room—the flat-screen TV. It is interesting to note the negative influence of pets, which seem to disturb other tourists. In the sustainability category, only facilities for disabled people and electric vehicle charging stations are relevant.
Earthworm Burrowing Activity and Its Effects on Soil Hydraulic Properties under Different Soil Moisture Conditions from the Loess Plateau, China
Authors: Wen Shuhai , Shao Ming’an , Wang Jiao
Published: November 2020

Earthworm activity has become more important in the Loess Plateau, where hydrological processes are crucial for ecosystem sustainability. In this study, we conducted a laboratory microcosm experiment to determine the various burrowing activities of Eisenia fetida and their impact on the soil hydraulic properties in response to different levels of soil moisture (50%, 70%, 90% of field capacity) in two common soil types (loessial and Lou soil) obtained from the Loess Plateau. Burrowing activity of E. fetida increased with higher soil moisture and was greater in loessial than in Lou soil. Most burrowing activities occurred within the top 5 cm and decreased with increasing soil depth. Macropores and burrow branching, which are highly related to the earthworm burrowing, were more prevalent in wetter soil. Earthworms significantly altered the formation of large soil aggregates (AGL, diameter >2 mm) under different soil moistures and depths. Distinct earthworm burrowing activities, controlled by soil moisture, altered soil hydraulic properties. However, soil saturated hydraulic conductivity (Ks) showed little differences between different treatments due to the horizontal and high–branched burrows of E. fetida, although higher burrowing activities were found in wetter soil. Soil field capacity was highest in drier soil due to the less macropores and burrowing activities.
Indigenous Knowledge and Acceptability of Treated Effluent in Agriculture
Authors: Okem Andrew Emmanuel , Odindo Alfred Oduor
Published: November 2020

The twin challenges of lack of access to improved sanitation and food insecurity remain critical, particularly in the global south. With cognizance of the nutrient potential of human excreta, there has been increasing interest in linking sanitation innovations with agriculture by using nutrients recovered from human excreta for crop production, thus, closing the nutrient loop. While studies and field trials have explored and validated the technical feasibility of reusing nutrients recovered from human excreta in agriculture, there is still limited knowledge of its social acceptability. This study examined whether indigenous knowledge can be leveraged to increase the acceptability of human-excreta-derived plant nutrient sources such as treated effluent in agriculture. A qualitative research design comprising seven focus group interviews (five in rural areas and two in peri-urban areas) was conducted in KwaZulu Natal, South Africa. Findings from the focus groups reveal a willingness to grow and consume food using treated effluent. Additionally, participants made references to indigenous practices that encourage recycling and reuse of human excreta. Given the potential to simultaneously address issues of food insecurity and sanitation that characterize many peri-urban and rural areas in South Africa, we recommend further studies in this area.
Resilience–Vulnerability Analysis: A Decision-Making Framework for Systems Assessment
Authors: Skondras Nikolaos A. , Tsesmelis Demetrios E. , Vasilakou Constantina G. , Karavitis Christos A.
Published: November 2020

The terms ‘resilience’ and ‘vulnerability’ have been widely used, with multiple interpretations in a plethora of disciplines. Such a variety may easily become confusing, and could create misconceptions among the different users. Policy makers who are bound to make decisions in key spatial and temporal points may especially suffer from these misconceptions. The need for decisions may become even more pressing in times of crisis, where the weaknesses of a system are exposed, and immediate actions to enhance the systemic strengths should be made. The analysis framework proposed in the current effort, and demonstrated in hypothetical forest fire cases, tries to focus on the combined use of simplified versions of the resilience and vulnerability concepts. Their relations and outcomes are also explored, in an effort to provide decision makers with an initial assessment of the information required to deal with complex systems. It is believed that the framework may offer some service towards the development of a more integrated and applicable tool, in order to further expand the concepts of resilience and vulnerability. Additionally, the results of the framework can be used as inputs in other decision making techniques and approaches. This increases the added value of the framework as a tool.
Cycling along a River: New Access, New Values?
Authors: Adam Matthieu , Cottet Marylise , Morardet Sylvie , Vaudor Lise , Coussout Laure , Rivière-Honegger Anne
Published: November 2020

The ViaRhôna is an 815 km cycle route running along the Rhône River from Lake Geneva to the Mediterranean Sea. We examine the influence of this type of cycle route on the relationship between route users (including the local population, itinerant cyclists and foreign tourists) and the river landscapes. This relationship is approached from the angle of the use of the riverbanks as well as the perceived image, the value, and the knowledge associated with the river and its landscapes. Our survey based on interviews (n = 16) and questionnaires (n = 546) produced the following results. The features of the cycle route and the related activities that it makes possible drain a special segment of the population that, in spite of its diverse sociological composition, shares similar tastes. The creation of the cycle route has led to an increase in use of the riverbanks both by tourists and local people. The experience that it offers contributes to enhancing the value that users place on the river. This is due to a change in the image of the river following the (re)discovery of its natural environments. On the other hand, knowledge of one’s natural environments is not modified. These results raise the question of possible changes in the degree to which users support policies targeting the preservation and restoration of the river.