bluuebunny/crossref_metadata_2025 huggingface dataset:
Field Scale Assessment of the TsHARP Technique for Thermal Sharpening of MODIS Satellite Images Using VENµS and Sentinel-2-Derived NDVI
Authors: Lacerda Lorena N. , Cohen Yafit , Snider John , Huryna Hanna , Liakos Vasileios , Vellidis George
Published: March 2021

Remotely sensed-based surface temperature is an important tool for crop monitoring and has great potential for improving irrigation management. However, current thermal satellite platforms do not display the fine spatial resolution required for identifying crop water status patterns at the field scale. The thermal sharpening (TsHARP) utility provides a technique for downscaling coarse thermal images to match the finer resolution of images acquired in the visible and near infrared bandwidths. This sharpening method is based on the inverse linear relationship between vegetation fraction calculated from the normalized difference vegetation index (NDVI) and land surface temperature (LST). The current study used the TsHARP method to sharpen low-resolution thermal data from the Moderate Resolution Imaging Spectrometer MODIS (1 km) to the finer resolution of Sentinel-2 (10 m) and Vegetation and Environment New micro-Spacecraft (VENµS) (5 m) visible-near infrared images. The sharpening methodology was evaluated at scene and field scales in southern Georgia and northern Mississippi, USA. A comparison of sharpened temperature was made with reference temperatures from Landsat-8 Operational Land Imager (OLI) in four different spatial resolutions (30, 60, 120, and 240 m) for method validation. Coarse resolution comparison on the dates in which imagery from both sensors were acquired on the same day resulted in average observed mean absolute error (MAE) of 1.63 °C, and R2 variation from 0.34 to 0.74. Temperature errors at the field scale ranged from 0.25 to 3.11 °C using both Sentinel-2 and VENµS. Sharpened maps at 120 and 60 m resolution showed the highest consistency for all fields and dates. Maps sharpened using VENµS images showed comparable or higher accuracy than maps sharpened using Sentinel-2. The superior performance coupled with the better revisit time indicates that the VENµS platform has high potential for frequent in-season crop monitoring. Further research with ground data collection is needed to explore field use limitations of this methodology, but these results give useful insights of potential benefits of implementing the TsHARP technique as a tool for crop stress monitoring.
Long-Term Subsidence Monitoring of the Alluvial Plain of the Scheldt River in Antwerp (Belgium) Using Radar Interferometry
Authors: Declercq Pierre-Yves , Gérard Pierre , Pirard Eric , Walstra Jan , Devleeschouwer Xavier
Published: March 2021

The coupled effects of climate change, sea-level rise, and land sinking in estuaries/alluvial plains prone to inundation and flooding mean that reliable estimation of land movements/subsidence is becoming more crucial. During the last few decades, land subsidence has been monitored by precise and continuous geodetic measurements either from space or using terrestrial techniques. Among them, the Persistent Scaterrer Interferometry (PSInSAR) technique is used on the entire Belgian territory to detect, map and interpret the identified ground movements observed since 1992. Here the research focuses on one of the biggest cities in Belgium that became the second European harbour with giant docks and the deepening of the Scheldt river allowing the navigation of the largest container vessels. The areas along the embankments of the Scheldt river and the harbour facilities are associated to Holocene fluviatile deposits overlain by recent landfills. These sedimentary deposits and human-made landfills are affected by important and ongoing land subsidence phenomena. The land subsidence process is highlighted by an annual average Line of Sight (LOS) velocity of about −3.4 mm/year during the years 1992–2001 (ERS1/2 datasets), followed by an annual average LOS velocity of about −2.71 mm/year and −2.11 mm/year, respectively, during the years 2003–2010 (ENVISAT) and 2016–2019 (Sentinel 1A). The Synthetic Aperture Radar (SAR) imagery data indicate a progressive decrease in the average annual velocities on a global scale independently of important local variations in different districts along the Scheldt river. On the contrary, the city centre and the old historic centre of Antwerp are not affected by negative LOS velocities, indicating stable ground conditions. A geological interpretation of this difference in settlement behaviour between the different areas is provided.
Comparison of Regional Winter Wheat Mapping Results from Different Similarity Measurement Indicators of NDVI Time Series and Their Optimized Thresholds
Authors: Li Fangjie , Ren Jianqiang , Wu Shangrong , Zhao Hongwei , Zhang Ningdan
Published: March 2021

Generally, there is an inconsistency between the total regional crop area that was obtained from remote sensing technology and the official statistical data on crop areas. When performing scale conversion and data aggregation of remote sensing-based crop mapping results from different administrative scales, it is difficult to obtain accurate crop planting area that match crop area statistics well at the corresponding administrative level. This problem affects the application of remote sensing-based crop mapping results. In order to solve the above problem, taking Fucheng County of Hebei Province in the Huanghuaihai Plain of China as the study area, based on the Sentinel-2 normalized difference vegetation index (NDVI) time series data covering the whole winter wheat growth period, the statistical data of the regional winter wheat planting area were regarded as reference for the winter wheat planting area extracted by remote sensing, and a new method for winter wheat mapping that is based on similarity measurement indicators and their threshold optimizations (WWM-SMITO) was proposed with the support of the shuffled complex evolution-University of Arizona (SCE-UA) global optimization algorithm. The accuracy of the regional winter wheat mapping results was verified, and accuracy comparisons with different similarity indicators were carried out. The results showed that the total area accuracy of the winter wheat area extraction by the proposed method reached over 99.99%, which achieved a consistency that was between the regional remote sensing-based winter wheat planting area and the statistical data on the winter wheat planting area. The crop recognition accuracy also reached a high level, which showed that the proposed method was effective and feasible. Moreover, in the accuracy comparison of crop mapping results based on six different similarity indicators, the winter wheat distribution that was extracted by root mean square error (RMSE) had the best recognition accuracy, and the overall accuracy and kappa coefficient were 94.5% and 0.8894, respectively. The overall accuracies of winter wheat that were extracted by similarity indicators, such as Euclidean distance (ED), Manhattan distance (MD), spectral angle mapping (SAM), and spectral correlation coefficient (SCC) were 94.1%, 93.9%, 93.3%, and 92.8%, respectively, and the kappa coefficients were 0.8815, 0.8776, 0.8657, and 0.8558, respectively. The accuracy of the winter wheat results extracted by the similarity indicator of dynamic time warping (DTW) was relatively low. The results of this paper could provide guidance and serve as a reference for the selection of similarity indicators in crop distribution extraction and for obtaining large-scale, long-term, and high-precision remote sensing-based information on a regional crop spatial distribution that is highly consistent with statistical crop area data.
Retrieval of Carbon Dioxide Using Cross-Track Infrared Sounder (CrIS) on S-NPP
Authors: Zhang Xinxin , Zhang Ying , Bai Lu , Tao Jinhua , Chen Liangfu , Zou Mingmin , Han Zongfu , Wang Zhibao
Published: March 2021

The Cross-track Infrared Sounder (CrIS) aboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite is a spaceborne Fourier transform infrared spectrometer. The study aims to retrieve carbon dioxide (CO2) information (the CO2 profile and column-averaged dry-air mole fraction of XCO2) from June 2018 to December 2019 based on the The National Oceanic and Atmospheric Administration (NOAA)-Unique Combined Atmospheric Processing System (NUCAPS) Cloud-Cleared Radiances (CCRs) via the CrIS. The CCRs products for the CrIS with 2223 channels have been available since 22 May 2018. Characteristics of the CO2 weighting functions inform the choice of multiple channels that are around 15 μm in size that differ by latitude and season to maximize retrieval sensitivity to CO2 and minimize sensitivity to other interfering atmospheric parameters. CO2 was retrieved from these channels using an adopted nonlinear optimization algorithm. The temperature, water vapor, and ozone profiles used in the inversion process were gathered from the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5). Validations of CO2 concentrations as retrieved from CrIS showed the following conclusions: (1) The relative error of the retrieved CO2 concentrations, as compared to Civil Aircraft for the Regular Investigation of the atmosphere Based on an Instrument Container (CARIBIC) in situ aircraft measurements, was less than 0.5%, and the root mean square errors (RMSE) were less than 0.7 ppmv (with correlation coefficients of 0.56–0.86); (2) the retrieved XCO2 from June 2018 to December 2019 correlated well with the ground-based Total Carbon Column Observing Network (TCCON) observations, and the differences were within ±0.2 ppmv. Further analysis of the temporal and spatial distribution of the retrieved CO2 at 300 hPa demonstrated a strong seasonal variation of CO2 in 0–60° N in the Northern Hemisphere with the maximum values in June–August and larger amplitudes of seasonal variation in the northeast of Asia and northeastern part of North America. The variations likely occurred due to larger sinks of atmospheric CO2 that are dominated by CO2 uptake in the summer. In the Southern Hemisphere, the CO2 displayed high concentration anomalies in the latitudinal range of 30–60° S in September–November and December–February, which probably occurred due to the lofted smoke plumes from the strong fire seasons in South America and Southern Africa.
Long-Term Snow Height Variations in Antarctica from GNSS Interferometric Reflectometry
Authors: Pinat Elisa , Defraigne Pascale , Bergeot Nicolas , Chevalier Jean-Marie , Bertrand Bruno
Published: March 2021

Acquiring reliable estimates of the Antarctic Ice Sheet surface mass balance is essential for trustworthy predictions of its evolution and future contribution to sea level rise. Snow height variations, i.e., the net change of the surface elevation resulting from a combination of surface processes such as snowfall, ablation, and wind redistribution, can provide a unique tool to constrain the uncertainty on mass budget estimations. In this study, GNSS Interferometric Reflectometry (GNSS-IR) is exploited to assess the long-term variations of snow accumulation and ablation processes. Eight antennas belonging to the Polar Earth Observing Network (POLENET) network are considered, together with the ROB1 antenna, deployed in the east part of Antarctica by the Royal Observatory of Belgium. For ROB1, which is located on an ice rise, we highlight an annual variation of snow accumulation in April–May (~30–50 cm) and ablation during spring/summer period. A snow surface elevation velocity of +0.08 ± 0.01 ma−1 is observed in the 2013–2016 period, statistically rejecting the “no trend” null hypothesis. As the POLENET stations are all located on moving glaciers, their associated downhill motion must be corrected for using an elevation model. This induces an increased uncertainty on the snow surface elevation change determined from GNSS-IR. Among the eight stations analyzed, only three of them show a long-term snow height variation larger than the uncertainties. One is located on the Flask Galcier in the Antarctic Peninsula, with a decrease of more than 4 m between 2012 and 2014, with an uncertainty of 2.5 m. The second one is located on the Lower Thwaites Glacier where we observe, between 2010 and 2020, a snow surface drop of 10 m, with a conservative uncertainty of 1 m. The third station, located on the West Antarctic Ice Sheet (WAIS) divide, shows on the opposite an upward motion from 2005 to 2019, of 1.2 m with an uncertainty of 0.4 m. The snow surface change of the other POLENET stations analyzed is smaller than the uncertainty associated with the glacier slope.
Determining the Events in a Glacial Disaster Chain at Badswat Glacier in the Karakoram Range Using Remote Sensing
Authors: Shangguan Donghui , Li Da , Ding Yongjian , Liu Jun , Anjum Muhammad Naveed , Li Yaojun , Guo Wanqin
Published: March 2021

The Karakoram mountain range is prone to natural disasters such as glacial surging and glacial lake outburst flood (GLOF) events. In this study, we aimed to document and reconstruct the sequence of events caused by glacial debris flows that dammed the Immit River in the Hindu Kush Karakoram Range on 17 July 2018. We used satellite remote sensing and field data to conduct the analyses. The order of the events in the disaster chain were determined as follows: glacial meltwater from the G2 glacier (ID: G074052E36491N) transported ice and debris that dammed the meltwater at the snout of the G1 glacier (ID: G074103E36480N), then the debris flow dammed the Immit River and caused Lake Badswat to expand. We surveyed the extent of these events using remote sensing imagery. We analyzed the glaciers’ responses to this event chain and found that the glacial debris flow induced G1 to exhibit accelerating ice flow in parts of the region from 25 July 2018 to 4 August 2018. According to the records from reanalysis data and data from the automatic weather station located 75 km from Lake Badswat, the occurrence of this disaster chain was related to high temperatures recorded after 15 July 2018. The chains of events caused by glacially related disasters makes such hazards more complex and dangerous. Therefore, this study is useful not only for understanding the formation of glacial disaster chains, but also for framing mitigation plans to reduce the risks for vulnerable downstream/upstream residents.
Analysis of the Spatiotemporal Changes in Watershed Landscape Pattern and Its Influencing Factors in Rapidly Urbanizing Areas Using Satellite Data
Authors: Zhu Zhenjie , Liu Bingjun , Wang Hailong , Hu Maochuan
Published: March 2021

Analyzing the spatiotemporal characteristics and causes of landscape pattern changes in watersheds around big cities is essential for understanding the ecological consequence of urbanization and provides a basic reference for the watershed management. This study used a land-use transition matrix and landscape indices to explore the spatiotemporal change of land use and landscape pattern over Liuxihe River basin of Guangzhou in the southeast of China from 1980 to 2015 with multitemporal Landsat satellite data in response to the rapid urbanization process. Primary temporal and spatial influencing factors were first quantitatively identified through grey relation analysis (calculating correlation degree between land use changes and influencing factors) and Geodetector (detecting landscape spatial heterogeneity and its driving factors), respectively. Considerable spatial and temporal differences in land use and landscape pattern changes were observed herein, thus determining the influencing factors of these differences in the Liuxihe River basin. These changes were characterized by a large increase in construction land converted from cropland, particularly in the middle and lower reaches of the basin from 2000 to 2010, causing dramatic fragmentation and homogenization of the landscape pattern there. Meanwhile, the landscape pattern gradually transitioned from an agricultural land use dominant landscape to a construction land use dominant landscape in these regions. Furthermore, the rapid growth of a nonagricultural population and the transformation of industry primarily caused the temporal changes of landscape pattern, and the landscape spatial heterogeneity was mainly caused by the interaction of complicated geomorphology and anthropogenic activities in different spatial locations, particularly after 2000. This study not only provides an improved approach to quantifying the main spatiotemporal influencing factors of landscape pattern changes during different time periods, but also offers a reference for decision-makers to formulate optimal strategies on ecological protection and urban sustainable development of different regions in this study area.
A Blockchain-Based Trusted Edge Platform in Edge Computing Environment
Authors: Zhang Jinnan , Lu Changqi , Cheng Gang , Guo Teng , Kang Jian , Zhang Xia , Yuan Xueguang , Yan Xin
Published: March 2021

Edge computing is a product of the evolution of IoT and the development of cloud computing technology, providing computing, storage, network, and other infrastructure close to users. Compared with the centralized deployment model of traditional cloud computing, edge computing solves the problems of extended communication time and high convergence traffic, providing better support for low latency and high bandwidth services. With the increasing amount of data generated by users and devices in IoT, security and privacy issues in the edge computing environment have become concerns. Blockchain, a security technology developed rapidly in recent years, has been adopted by many industries, such as finance and insurance. With the edge computing capability, deploying blockchain platforms/applications on edge computing platforms can provide security services for network edge environments. Although there are already solutions for integrating edge computing with blockchain in many IoT application scenarios, they slightly lack scalability, portability, and heterogeneous data processing. In this paper, we propose a trusted edge platform to integrate the edge computing framework and blockchain network for building an edge security environment. The proposed platform aims to preserve the data privacy of the edge computing client. The design based on the microservice architecture makes the platform lighter. To improve the portability of the platform, we introduce the Edgex Foundry framework and design an edge application module on the platform to improve the business capability of Edgex. Simultaneously, we designed a series of well-defined security authentication microservices. These microservices use the Hyperledger Fabric blockchain network to build a reliable security mechanism in the edge environment. Finally, we build an edge computing network using different hardware devices and deploy the trusted edge platform on multiple network nodes. The usability of the proposed platform is demonstrated by testing the round-trip time (RTT) of several important workflows. The experimental results demonstrate that the platform can meet the availability requirements in real-world usage scenarios.
INTEGRATION Large-Scale Modeling Framework of Direct Cellular Vehicle-to-All (C-V2X) Applications
Authors: Farag Mohamed M. G. , Rakha Hesham A. , Mazied Emadeldin A. , Rao Jayanthi
Published: March 2021

The transportation system has evolved into a complex cyber-physical system with the introduction of wireless communication and the emergence of connected travelers and connected automated vehicles. Such applications create an urgent need to develop high-fidelity transportation modeling tools that capture the mutual interaction of the communication and transportation systems. This paper addresses this need by developing a high-fidelity, large-scale dynamic and integrated traffic and direct cellullar vehicle-to-vehicle and vehicle-to-infrastructure (collectively known as V2X) modeling tool. The unique contributions of this work are (1) we developed a scalable implementation of the analytical communication model that captures packet movement at the millisecond level; (2) we coupled the communication and traffic simulation models in real-time to develop a fully integrated dynamic connected vehicle modeling tool; and (3) we developed scalable approaches that adjust the frequency of model coupling depending on the number of concurrent vehicles in the network. The proposed scalable modeling framework is demonstrated by running on the Los Angeles downtown network considering the morning peak hour traffic demand (145,000 vehicles), running faster than real-time on a regular personal computer (1.5 h to run 1.86 h of simulation time). Spatiotemporal estimates of packet delivery ratios for downtown Los Angeles are presented. This novel modeling framework provides a breakthrough in the development of urgently needed tools for large-scale testing of direct (C-V2X) enabled applications.
Module for Monitoring the Probe-Skin Contact Force in the Study of Vibration Perception on the Wrist
Authors: Czopek Dorota , Barański Robert , Wiciak Jerzy
Published: March 2021

This paper presents a module for monitoring the contact force between a probe for measuring vibration perception on the wrist and the skin. The module was designed for an original measuring stand for the automatic testing of the vibrotactile discrimination thresholds using the psychophysical adaptive method of 1 up–2 down with two or three interval forced choices (2IFC, 3IFC). Measurement methods were implemented in LabVIEW software. The inspiration for the project was the need to check the possibility of building a vibrating interface for transmitting information through vibrations delivered to the wrist via a bracelet. The test procedure on the wrist is not standardized; however, during its development, the recommendations of the Polish Norm–International Organization for Standardization PN-ISO 13091-1, 2006 were adopted. This standard contains methods for measuring vibration sensation thresholds on the fingertips for the assessment of neural dysfunction. The key to the repeatability of measurements seems to be the ability to continuously control the pressure of the measuring probe on the skin. This article compares two solutions for measuring the contact force along with an analysis of their accuracy and the impact of vibrations on the measured values. Moreover, the results of measurements of vibrotactile amplitude and frequency discrimination thresholds obtained on the ventral wrist at five frequencies (25, 32, 63, 125 and 250 Hz) are presented.
Advances in Plant Disease Detection and Monitoring: From Traditional Assays to In-Field Diagnostics
Authors: Buja Ilaria , Sabella Erika , Monteduro Anna Grazia , Chiriacò Maria Serena , De Bellis Luigi , Luvisi Andrea , Maruccio Giuseppe
Published: March 2021

Human activities significantly contribute to worldwide spread of phytopathological adversities. Pathogen-related food losses are today responsible for a reduction in quantity and quality of yield and decrease value and financial returns. As a result, “early detection” in combination with “fast, accurate, and cheap” diagnostics have also become the new mantra in plant pathology, especially for emerging diseases or challenging pathogens that spread thanks to asymptomatic individuals with subtle initial symptoms but are then difficult to face. Furthermore, in a globalized market sensitive to epidemics, innovative tools suitable for field-use represent the new frontier with respect to diagnostic laboratories, ensuring that the instruments and techniques used are suitable for the operational contexts. In this framework, portable systems and interconnection with Internet of Things (IoT) play a pivotal role. Here we review innovative diagnostic methods based on nanotechnologies and new perspectives concerning information and communication technology (ICT) in agriculture, resulting in an improvement in agricultural and rural development and in the ability to revolutionize the concept of “preventive actions”, making the difference in fighting against phytopathogens, all over the world.
Three-Dimensional Reconstruction with a Laser Line Based on Image In-Painting and Multi-Spectral Photometric Stereo
Authors: Lu Liang , Zhu Hongbao , Dong Junyu , Ju Yakun , Zhou Huiyu
Published: March 2021

This paper presents a multi-spectral photometric stereo (MPS) method based on image in-painting, which can reconstruct the shape using a multi-spectral image with a laser line. One of the difficulties in multi-spectral photometric stereo is to extract the laser line because the required illumination for MPS, e.g., red, green, and blue light, may pollute the laser color. Unlike previous methods, through the improvement of the network proposed by Isola, a Generative Adversarial Network based on image in-painting was proposed, to separate a multi-spectral image with a laser line into a clean laser image and an uncorrupted multi-spectral image without the laser line. Then these results were substituted into the method proposed by Fan to obtain high-precision 3D reconstruction results. To make the proposed method applicable to real-world objects, a rendered image dataset obtained using the rendering models in ShapeNet has been used for training the network. Evaluation using the rendered images and real-world images shows the superiority of the proposed approach over several previous methods.
A Robust Road Vanishing Point Detection Adapted to the Real-world Driving Scenes
Authors: Khac Cuong Nguyen , Choi Yeongyu , Park Ju H. , Jung Ho-Youl
Published: March 2021

Vanishing point (VP) provides extremely useful information related to roads in driving scenes for advanced driver assistance systems (ADAS) and autonomous vehicles. Existing VP detection methods for driving scenes still have not achieved sufficiently high accuracy and robustness to apply for real-world driving scenes. This paper proposes a robust motion-based road VP detection method to compensate for the deficiencies. For such purposes, three main processing steps often used in the existing road VP detection methods are carefully examined. Based on the analysis, stable motion detection, stationary point-based motion vector selection, and angle-based RANSAC (RANdom SAmple Consensus) voting are proposed. A ground-truth driving dataset including various objects and illuminations is used to verify the robustness and real-time capability of the proposed method. The experimental results show that the proposed method outperforms the existing motion-based and edge-based road VP detection methods for various illumination conditioned driving scenes.
Multi-Level Context Pyramid Network for Visual Sentiment Analysis
Authors: Ou Haochun , Qing Chunmei , Xu Xiangmin , Jin Jianxiu
Published: March 2021

Sharing our feelings through content with images and short videos is one main way of expression on social networks. Visual content can affect people’s emotions, which makes the task of analyzing the sentimental information of visual content more and more concerned. Most of the current methods focus on how to improve the local emotional representations to get better performance of sentiment analysis and ignore the problem of how to perceive objects of different scales and different emotional intensity in complex scenes. In this paper, based on the alterable scale and multi-level local regional emotional affinity analysis under the global perspective, we propose a multi-level context pyramid network (MCPNet) for visual sentiment analysis by combining local and global representations to improve the classification performance. Firstly, Resnet101 is employed as backbone to obtain multi-level emotional representation representing different degrees of semantic information and detailed information. Next, the multi-scale adaptive context modules (MACM) are proposed to learn the sentiment correlation degree of different regions for different scale in the image, and to extract the multi-scale context features for each level deep representation. Finally, different levels of context features are combined to obtain the multi-cue sentimental feature for image sentiment classification. Extensive experimental results on seven commonly used visual sentiment datasets illustrate that our method outperforms the state-of-the-art methods, especially the accuracy on the FI dataset exceeds 90%.
LoRaWAN and Urban Waste Management—A Trial
Authors: Cruz Nuno , Cota Nuno , Tremoceiro João
Published: March 2021

The city of Lisbon, as any other capital of a European country, has a large number of issues regarding managing waste and recycling containers spread throughout the city. This document presents the results of a study promoted by the Lisbon City Council for trialing LPWAN (Low-Power Wide-Area Network) technology for the waste management vertical under the Lisbon Smart City initiative. Current waste management is done using GSM (Global System for Mobile communications) sensors, and the municipality aims to use LPWAN in order to improve range and reduce costs and provisioning times when changing the communications provider. After an initial study, LoRa (Long Range) and LoRAWAN (LoRa Wide Area Network) as its network counterpart, were selected as the LPWAN technology for trials considering several use cases, exploring multiple distances, types of recycling waste containers, placements (underground or surface) and kinds of commercially available waste level measurement LoRa sensors. The results showed that the underground waste containers proved to be, as expected, the most difficult to operate correctly, where the container itself imposed attenuation levels of 26 dB on the LoRa link budget. The successful results were used to promote the deployment of a city-wide LoRa network, available to all the departments inside the Lisbon City Council. Considering the network capacity, the municipality also decided to make the network freely available to citizens.
Artificial Intelligence-Based Wearable Robotic Exoskeletons for Upper Limb Rehabilitation: A Review
Authors: Vélez-Guerrero Manuel Andrés , Callejas-Cuervo Mauro , Mazzoleni Stefano
Published: March 2021

Processing and control systems based on artificial intelligence (AI) have progressively improved mobile robotic exoskeletons used in upper-limb motor rehabilitation. This systematic review presents the advances and trends of those technologies. A literature search was performed in Scopus, IEEE Xplore, Web of Science, and PubMed using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology with three main inclusion criteria: (a) motor or neuromotor rehabilitation for upper limbs, (b) mobile robotic exoskeletons, and (c) AI. The period under investigation spanned from 2016 to 2020, resulting in 30 articles that met the criteria. The literature showed the use of artificial neural networks (40%), adaptive algorithms (20%), and other mixed AI techniques (40%). Additionally, it was found that in only 16% of the articles, developments focused on neuromotor rehabilitation. The main trend in the research is the development of wearable robotic exoskeletons (53%) and the fusion of data collected from multiple sensors that enrich the training of intelligent algorithms. There is a latent need to develop more reliable systems through clinical validation and improvement of technical characteristics, such as weight/dimensions of devices, in order to have positive impacts on the rehabilitation process and improve the interactions among patients, teams of health professionals, and technology.
Developing Educational Games for Preschool Children to Improve Dietary Choices and Exercise Capacity
Authors: Piziak Veronica
Published: March 2021

This article describes the processes used to develop two different types of games used to improve the consumption of healthful foods and increase exercise in preschool Hispanic populations. They were created to meet criteria for effectiveness: age and culturally appropriate, fun, and foster family participation. The first, a pictorial bilingual food bingo game, emphasized vegetable and water consumption and the limitation of sugar-sweetened beverages. A population was selected to study the effectiveness in changing dietary habits, and we were able to show a significantly improved consumption of vegetables at home after using the game during the school year. Next, we developed bilingual video games used to teach nutrition and enhance exercise. The animal characters and narrative were created to allow immersion. The concept was that the animals needed the children’s help to obtain food, exercise tasks were assigned, and nutritional foods were discussed. Focus groups were reviewed for the effectiveness of the concept, ease of usability, and appropriateness for the target audience. The videos were tested in a summer session, and teachers concluded that after two viewings the children enhanced their exercise, bonded to the animals, and were answering the nutrition questions correctly.
The Relationship between Learning Styles and Academic Performance: Consistency among Multiple Assessment Methods in Psychology and Education Students
Authors: Maya Jesús , Luesia Juan F. , Pérez-Padilla Javier
Published: March 2021

Universities strive to ensure quality education focused on the diversity of the student body. According to experiential learning theory, students display different learning preferences. This study has a three-fold objective: to compare learning styles based on personal and educational variables, to analyze the association between learning styles, the level of academic performance, and consistency of performance in four assessment methods, and to examine the influence of learning dimensions in students with medium-high performance in the assessment methods. An interdisciplinary approach was designed involving 289 psychology, early childhood education and primary education students at two universities in Spain. The Learning Style Inventory was used to assess learning styles and dimensions. The assessment methods used in the developmental psychology course included the following question formats: multiple-choice, short answer, creation-elaboration and an elaboration question on the relationship between theory and practice. Univariate analysis, multivariate analysis, and binomial logistic models were computed. The results reveal Psychology students to be more assimilative (theoretical and abstract), while early childhood and primary education students were evenly distributed among styles and were more divergent and convergent (practical) in absolute terms. In addition, high scores in perception (abstract conceptualization) were associated with a high level of performance on the multiple-choice tests and the elaboration question on the relationship between theory and practice. Abstract conceptualization was also associated with medium-high performance in all assessment methods and this variable predicted consistent high performance, independent of the assessment method. This study highlights the importance of promoting abstract conceptualization. Recommendations for enhancing this learning dimension are presented.
Emergency Medical Providers’ Knowledge Regarding Disasters during Mass Gatherings in Saudi Arabia
Authors: Al-Wathinani Ahmed , Hertelendy Attila J. , Mobrad Abdulmajeed M. , Alhazmi Riyadh , Althunayyan Saqer , Molloy Michael S. , Goniewicz Krzysztof
Published: March 2021

The Hajj is a recurring annual mass gathering event with over three million attendants taking place at the same site for six days. During such events, major incidents and disasters can occur. It is crucial that Emergency Medical Services providers are sufficiently trained regarding disaster preparedness to respond appropriately. EMS-providers of the Saudi Red Crescent Authority who worked during the Hajj in 2016 were asked to complete a web-based survey, utilizing predetermined responses with 5-point Likert scale responses. Seven hundred respondents identified real disasters as the most common source of information about disaster preparedness and also indicated that a disaster management course was the most desired course for improving knowledge. The study has also highlighted a list of Life Support Courses providers feel should be offered as part of a disaster response training package. These findings highlight the importance of continuing education, which may be obtained through short, focused courses, or for small numbers of specialists through higher educational degrees, such as masters or doctorates. This study also examines the importance of media and its impact on increasing knowledge and awareness for EMS-providers. Consideration should be given to pairing novice providers with experienced personnel to disseminate knowledge and practical experience during Hajj missions. Simulated disaster drilling should be considered to introduce novices to the stress of mass casualty disaster response.
An Internet of Things Approach for Water Efficiency: A Case Study of the Beverage Factory
Authors: Jagtap Sandeep , Skouteris George , Choudhari Vilendra , Rahimifard Shahin , Duong Linh Nguyen Khanh
Published: March 2021

There is a lack of knowledge among food manufacturers about adopting the Internet of Things (IoT)-based water monitoring system and its ability to support water minimisation activities. It is therefore necessary to investigate the applicability of IoT-based real-time water monitoring systems in a real food manufacturing environment to pursue water-saving opportunities accordingly. This article aims to propose an architecture of an IoT-based water-monitoring system needed for real-time monitoring of water usage, and address any water inefficiencies within food manufacturing. This article looks at a study conducted in a food beverage factory where an IoT-based real-time water monitoring system is implemented to analyse the complete water usage in order to devise solutions and address water overconsumption/wastage during the manufacturing process. The successful implementation of an IoT-based real-time water monitoring system offered the beverage factory a detailed analysis of the water consumption and insights into the water hotspots that needed attention. This action initiated several water-saving project opportunities, which contributed to the improvement of water sustainability and led to an 11% reduction in the beverage factory’s daily water usage.
Multi-Criteria Approach for Prioritizing and Managing Public Investment in Urban Spaces. A Case Study in the Triple Frontier
Authors: Villegas Flores Noé , Saldeño Madero Yelinca , Torres Parra Camilo Alberto , Fasolino Isidoro , Rondón Quintana Hugo Alexander
Published: March 2021

The aspirations of public administrations to meet quality parameters and standards in urban spaces have fostered new strategies and tools that allow users to give safety and well-being. The participation and interaction of different actors during decision-making in the context of allocation of public resources implies a significant degree of complexity when prioritizing actions in public works. The objective of the study focuses on obtaining an urban street condition index (USCI) that allows an efficient diagnosis of urban infrastructure. The study provides an innovation component for decision-making through the construction of guidelines to prioritize spending on investment in urban infrastructure. The case study has been developed in three countries, Brazil, Paraguay and Argentina (Triple Border) with the aim of drawing management guidelines during the process in public entities. The results for Brazil and Argentina present streets with satisfactory USCI. Paraguay reflects a significant lack of urban infrastructure and compliance of accessibility regulations. Regarding the city of Foz de Iguazú, it has been observed that 50% of the roads require prevailing actions to improve the mobility of the roads; 40% of these reflect reduced mobility and deterioration of urban components, configured as an urgent action, and only 10% of the roads studied reflect adequate mobility conditions.
Public Opinions about Online Learning during COVID-19: A Sentiment Analysis Approach
Authors: Bhagat Kaushal Kumar , Mishra Sanjaya , Dixit Alakh , Chang Chun-Yen
Published: March 2021

The aim of this study was to analyze public opinion about online learning during the COVID-19 (Coronavirus Disease 2019) pandemic. A total of 154 articles from online news and blogging websites related to online learning were extracted from Google and DuckDuckGo. The articles were extracted for 45 days, starting from the day the World Health Organization (WHO) declared COVID-19 a worldwide pandemic, 11 March 2020. For this research, we applied the dictionary-based approach of the lexicon-based method to perform sentiment analysis on the articles extracted through web scraping. We calculated the polarity and subjectivity scores of the extracted article using the TextBlob library. The results showed that over 90% of the articles are positive, and the remaining were mildly negative. In general, the blogs were more positive than the newspaper articles; however, the blogs were more opinionated compared to the news articles.
Study on the Contradiction between Population and Cultivated Land and the Priority Protection of Cultivated Land in the Policy of Poverty Alleviation: A Case Study of the Upper Reaches of Min River, Sichuan Province, China
Authors: Chen Li , Wang Qing
Published: March 2021

The contradiction between population and cultivated land has always been an urgent global problem, and one that is particularly prominent in China. Based on the spatial–temporal evolution of cultivated land, this paper discusses the human–land contradiction and its development trend. Then, according to the threshold of human–land contradiction and different protection objectives, the priority protection area of cultivated land was simulated. The results showed that: (1) the cellular automata (CA)–Markov model is suitable for the study area. The cultivated land in the study area increased at a rate of 4.40 sq km per year; (2) the spatial and temporal change in the cultivated land in Songpan was the largest. The center of gravity of cultivated land is moving to the northeast, and the moving rate is increasing year on year; (3) 90% of the study area was in the human–land coordination and the change in the ratio of accumulation and cultivation in some areas (such as Songpan) is increasing, making the human–land contradiction worse; (4) under a protection target of 25–100%, the priority protection area of cultivated land increased from 2.05 × 103 km2 to 3.46 × 103 km2, and the patch aggregation degree was strengthened. This study was of great significance for optimizing the distribution of cultivated land and promoting the sustainable development of land resources.
Renewable Energy Perspectives of Pakistan and Turkey: Current Analysis and Policy Recommendations
Authors: Uddin Riaz , Shaikh Abdurrahman Javid , Khan Hashim Raza , Shirazi Muhammad Ayaz , Rashid Athar , Qazi Saad Ahmed
Published: March 2021

To a great extent, Pakistan and Turkey rely on imported fossil fuels to meet their energy demands. Pakistan is moving in the right direction, placing focus on renewable energy resources in its current infrastructure in order to address the energy shortage. Several projects (e.g., wind power and solar PV (photovoltaic) technologies) are operational or under development; they are intended to reduce energy challenges in Pakistan. The new government in Pakistan aims to increase the share of renewable energy in total power generation to 30% by 2030. On the other hand, Turkey surpasses Pakistan in renewable energy resources; for example, there are 186 operational wind energy power plants across the country. In addition, Turkey utilizes solar energy—mainly for residential usage. Turkey’s Vision 2023 energy agenda aims to supply 30% of their power demands from modern renewable energy resources. Turkey has implemented solar PV, solar buildings, wind power plants, geothermal energy resources, and biomass technology for heating, cooling and electricity generation. At present, Turkey’s supply to meet energy demands in the country is 56% fossil fuel energy resources and 44% renewable energy, including hydropower. Accessible details reveal that geothermal energy resources have been continuously neglected in Pakistan by the Ministry of Energy (power division); this is in contrast to the Turkish case, in which utilization of geothermal energy resources for heating and cooling purposes is efficient. With all the facts and figures under consideration, in this paper, comparative analyses are performed which reveal that the production of electricity from geothermal energy technologies is lower than the massive potential in both countries. Recommendations are made for important policies to promote renewable energy technologies, which could effectively support energy decentralization by providing electricity to rural areas and the national grid.
Knowledge Management for Sustainable Development in the Era of Continuously Accelerating Technological Revolutions: A Framework and Models
Authors: Russ Meir
Published: March 2021

This conceptual, interdisciplinary paper will start by introducing the commencement of a new era in which human society faces continuously accelerating technological revolutions, named the Post Accelerating Data and Knowledge Online Society, or ‘Padkos’ (“food for the journey; prog; provisions for journey”—in Afrikaans) for short. In this context, a conceptual model of sustainable development with a focus on knowledge management and sharing will be proposed. The construct of knowledge management will be unpacked into a new three-layer model with a focus on the knowledge-human and data-machine spheres. Then, each sphere will be discussed with concentration on the learning and decision- making processes, the digital supporting systems and the human actors’ aspects. Moreover, the recombination of new knowledge development and contemporary knowledge management into one amalgamated construct will be proposed. The holistic conceptual model of knowledge management for sustainable development is comprised by time, cybersecurity and two alternative humanistic paradigms (Homo Technologicus and Homo Sustainabiliticus). Two additional particular models are discussed in depth. First, a recently proposed model of quantum organizational decision-making is elaborated. Next, a boundary management and learning process is deliberated. The paper ends with a number of propositions and several implications for the future based on the deliberations in the paper and the models discussed and with conclusions.
The Unsustainable Use of Sand: Reporting on a Global Problem
Authors: Leal Filho Walter , Hunt Julian , Lingos Alexandros , Platje Johannes , Vieira Lara , Will Markus , Gavriletea Marius
Published: March 2021

Sand is considered one of the most consumed natural resource, being essential to many industries, including building construction, electronics, plastics, and water filtration. This paper assesses the environmental impact of sand extraction and the problems associated with its illegal exploitation. The analysis indicates that extracting sand at a greater rate than that at which it is naturally replenished has adverse consequences for fauna and flora. Further, illicit mining activities compound environmental damages and result in conflict, the loss of taxes/royalties, illegal work, and losses in the tourism industry. As sea-level rise associated with climate change threatens coastal areas, sand in coastal areas will play an increasingly greater role in determining the amount of damage from floods and erosion. The present analysis points to the need for swift action to regulate sand mining, monitoring, law enforcement, and international cooperation.