bluuebunny/crossref_metadata_2025 huggingface dataset:
Practical Cross-Layer Radio Frequency-Based Authentication Scheme for Internet of Things
Authors: Haenel Arie , Haddad Yoram , Laurent Maryline , Zhang Zonghua
Published: June 2021

The Internet of Things world is in need of practical solutions for its security. Existing security mechanisms for IoT are mostly not implemented due to complexity, budget, and energy-saving issues. This is especially true for IoT devices that are battery powered, and they should be cost effective to be deployed extensively in the field. In this work, we propose a new cross-layer approach combining existing authentication protocols and existing Physical Layer Radio Frequency Fingerprinting technologies to provide hybrid authentication mechanisms that are practically proved efficient in the field. Even though several Radio Frequency Fingerprinting methods have been proposed so far, as a support for multi-factor authentication or even on their own, practical solutions are still a challenge. The accuracy results achieved with even the best systems using expensive equipment are still not sufficient on real-life systems. Our approach proposes a hybrid protocol that can save energy and computation time on the IoT devices side, proportionally to the accuracy of the Radio Frequency Fingerprinting used, which has a measurable benefit while keeping an acceptable security level. We implemented a full system operating in real time and achieved an accuracy of 99.8% for the additional cost of energy, leading to a decrease of only ~20% in battery life.
Graph Representation Integrating Signals for Emotion Recognition and Analysis
Authors: Zawadzka Teresa , Wierciński Tomasz , Meller Grzegorz , Rock Mateusz , Zwierzycki Robert , Wróbel Michał R.
Published: June 2021

Data reusability is an important feature of current research, just in every field of science. Modern research in Affective Computing, often rely on datasets containing experiments-originated data such as biosignals, video clips, or images. Moreover, conducting experiments with a vast number of participants to build datasets for Affective Computing research is time-consuming and expensive. Therefore, it is extremely important to provide solutions allowing one to (re)use data from a variety of sources, which usually demands data integration. This paper presents the Graph Representation Integrating Signals for Emotion Recognition and Analysis (GRISERA) framework, which provides a persistent model for storing integrated signals and methods for its creation. To the best of our knowledge, this is the first approach in Affective Computing field that addresses the problem of integrating data from multiple experiments, storing it in a consistent way, and providing query patterns for data retrieval. The proposed framework is based on the standardized graph model, which is known to be highly suitable for signal processing purposes. The validation proved that data from the well-known AMIGOS dataset can be stored in the GRISERA framework and later retrieved for training deep learning models. Furthermore, the second case study proved that it is possible to integrate signals from multiple sources (AMIGOS, ASCERTAIN, and DEAP) into GRISERA and retrieve them for further statistical analysis.
An Integrated Individual Environmental Exposure Assessment System for Real-Time Mobile Sensing in Environmental Health Studies
Authors: Wang Jue , Kou Lirong , Kwan Mei-Po , Shakespeare Rebecca Marie , Lee Kangjae , Park Yoo Min
Published: June 2021

The effects of environmental exposure on human health have been widely explored by scholars in health geography for decades. However, recent advances in geospatial technologies, especially the development of mobile approaches to collecting real-time and high-resolution individual data, have enabled sophisticated methods for assessing people’s environmental exposure. This study proposes an individual environmental exposure assessment system (IEEAS) that integrates objective real-time monitoring devices and subjective sensing tools to provide a composite way for individual-based environmental exposure data collection. With field test data collected in Chicago and Beijing, we illustrate and discuss the advantages of the proposed IEEAS and the composite analysis that could be applied. Data collected with the proposed IEEAS yield relatively accurate measurements of individual exposure in a composite way, and offer new opportunities for developing more sophisticated ways to measure individual environmental exposure. With the capability to consider both the variations in environmental risks and human mobility in high spatial and temporal resolutions, the IEEAS also helps mitigate some uncertainties in environmental exposure assessment and thus enables a better understanding of the relationship between individual environmental exposure and health outcomes.
A Coalitional Distributed Model Predictive Control Perspective for a Cyber-Physical Multi-Agent Application
Authors: Maxim Anca , Caruntu Constantin-Florin
Published: June 2021

Following the current technological development and informational advancement, more and more physical systems have become interconnected and linked via communication networks. The objective of this work is the development of a Coalitional Distributed Model Predictive Control (C- DMPC) strategy suitable for controlling cyber-physical, multi-agent systems. The motivation behind this endeavour is to design a novel algorithm with a flexible control architecture by combining the advantages of classical DMPC with Coalitional MPC. The simulation results were achieved using a test scenario composed of four dynamically coupled sub-systems, connected through an unidirectional communication topology. The obtained results illustrate that, when the feasibility of the local optimization problem is lost, forming a coalition between neighbouring agents solves this shortcoming and maintains the functionality of the entire system. These findings successfully prove the efficiency and performance of the proposed coalitional DMPC method.
Error Fusion of Hybrid Neural Networks for Mechanical Condition Dynamic Prediction
Authors: Zhang Wentao , Liu Yucheng , Zhang Shaohui , Long Tuzhi , Liang Jinglun
Published: June 2021

It is important for equipment to operate safely and reliably so that the working state of mechanical parts pushes forward an immense influence. Therefore, in order to enhance the dependability and security of mechanical equipment, to accurately predict the changing trend of mechanical components in advance plays a significant role. This paper introduces a novel condition prediction method, named error fusion of hybrid neural networks (EFHNN), by combining the error fusion of multiple sparse auto-encoders with convolutional neural networks for predicting the mechanical condition. First, to improve prediction accuracy, we can use the error fusion of multiple sparse auto-encoders to collect multi-feature information, and obtain a trend curve representing machine condition as well as a threshold line that can indicate the beginning of mechanical failure by computing the square prediction error (SPE). Then, convolutional neural networks predict the state of the machine according to the original data when the SPE value exceeds the threshold line. It can be seen from this result that the EFHNN method in the prediction of mechanical fault time series is available and superior.
Phoswich Detectors in Sensing Applications
Authors: Min Sujung , Seo Bumkyung , Roh Changhyun , Hong Sangbum , Cheong JaeHak
Published: June 2021

Herein, we review studies of the integration of Phoswich detectors with readout integrated circuits and the associated performance in a radiological sensing application. The basic concept and knowledge of interactions with scintillation materials and the mechanisms and characteristics of radiological detection are extensively discussed. Additionally, we summarize integrated multiple detection systems and Phoswich detectors in radiological measurements for their device performance. Moreover, we further exhibit recent progress and perspective in the future of Phoswich-based radiological detection and measurement. Finally, we provide perspectives to evaluate the detector performance for radiological detection and measurement. We expect this review can pave the way to understanding the recent status and future challenges for Phoswich detectors for radiological detection and measurement.
Texture Analysis of Dried Droplets for the Quality Control of Medicines
Authors: Carreón Yojana J. P. , Díaz-Hernández Orlando , Escalera Santos Gerardo J. , Cipriano-Urbano Ivan , Solorio-Ordaz Francisco J. , González-Gutiérrez Jorge , Zenit Roberto
Published: June 2021

The quality control of medicines guarantees the effectiveness of treatments for diseases. We explore the use of texture analysis of patterns in dried droplets as a tool to readily detect both impurities and changes in drug concentration. Four types of medicines associated with different routes of administration were analyzed: Methotrexate, Ciprofloxacin, Clonazepam, and Budesonide. We use NaCl and a hot substrate at 63 ∘C to promote aggregate formation and to reduce droplet drying time. Depending on the medicine, optical microscopy reveals different complex aggregates such as circular to oval splatters, fern-like islands, crown shapes, crown needle-like and bump-like patterns as well as dendritic branched and star-like crystals. We use some physical features of the stains (as the stain diameter and superficial area) and gray level co-occurrence matrix (GLCM) to characterize patterns of dried droplets. Finally, we show that structural analysis of stains can achieve 95% accuracy in identifying medicines with 30% water dilution, while it achieves 99% accuracy in detecting drugs with 10% other substances.
Characterizing the Impact of Doppler Effects on Body-Centric LoRa Links with SDR
Authors: Ameloot Thomas , Moeneclaey Marc , Van Torre Patrick , Rogier Hendrik
Published: June 2021

Long-range, low-power wireless technologies such as LoRa have been shown to exhibit excellent performance when applied in body-centric wireless applications. However, the robustness of LoRa technology to Doppler spread has recently been called into question by a number of researchers. This paper evaluates the impact of static and dynamic Doppler shifts on a simulated LoRa symbol detector and two types of simulated LoRa receivers. The results are interpreted specifically for body-centric applications and confirm that, in most application environments, pure Doppler effects are unlikely to severely disrupt wireless communication, confirming previous research, which stated that the link deteriorations observed in a number of practical LoRa measurement campaigns would mainly be caused by multipath fading effects. Yet, dynamic Doppler shifts, which occur as a result of the relative acceleration between communicating nodes, are also shown to contribute to link degradation. This is especially so for higher LoRa spreading factors and larger packet sizes.
Optimization of Fiber Bragg Gratings Inscribed in Thin Films Deposited on D-Shaped Optical Fibers
Authors: Imas José Javier , Zamarreño Carlos R. , del Villar Ignacio , Matías Ignacio R.
Published: June 2021

A fiber Bragg grating patterned on a SnO2 thin film deposited on the flat surface of a D-shaped polished optical fiber is studied in this work. The fabrication parameters of this structure were optimized to achieve a trade-off among reflected power, full width half maximum (FWHM), sensitivity to the surrounding refractive index (SRI), and figure of merit (FOM). In the first place, the influence of the thin film thickness, the cladding thickness between the core and the flat surface of the D-shaped fiber (neck), and the length of the D-shaped zone over the reflected power and the FWHM were assessed. Reflected peak powers in the range from −2 dB to −10 dB can be easily achieved with FWHM below 100 pm. In the second place, the sensitivity to the SRI, the FWHM, and the FOM were analyzed for variations of the SRI in the 1.33–1.4 range, the neck, and the thin-film thickness. The best sensitivities theoretically achieved for this device are next to 40 nm/RIU, while the best FOM has a value of 114 RIU−1.
Design of Dielectric Resonator Antenna Using Dielectric Paste
Authors: Kremer Hauke Ingolf , Leung Kwok Wa , Wong Wai Cheung , Lo Kenneth Kam-Wing , Lee Mike W. K.
Published: June 2021

In this publication, the use of a dielectric paste for dielectric resonator antenna (DRA) design is investigated. The dielectric paste can serve as an alternative approach of manufacturing a dielectric resonator antenna by subsequently filling a mold with the dielectric paste. The dielectric paste is obtained by mixing nanoparticle sized barium strontium titanate (BST) powder with a silicone rubber. The dielectric constant of the paste can be adjusted by varying the BST powder content with respect to the silicone rubber content. The tuning range of the dielectric constant of the paste was found to be from 3.67 to 18.45 with the loss tangent of the mixture being smaller than 0.044. To demonstrate the idea of the dielectric paste approach, a circularly polarized DRA with wide bandwidth, which is based on a fractal geometry, is designed. The antenna is realized by filling a 3D-printed mold with the dielectric paste material, and the prototype was found to have an axial ratio bandwidth of 16.7% with an impedance bandwidth of 21.6% with stable broadside radiation.
A Coarse-to-Fine Method for Estimating the Axis Pose Based on 3D Point Clouds in Robotic Cylindrical Shaft-in-Hole Assembly
Authors: Li Can , Chen Ping , Xu Xin , Wang Xinyu , Yin Aijun
Published: June 2021

In this work, we propose a novel coarse-to-fine method for object pose estimation coupled with admittance control to promote robotic shaft-in-hole assembly. Considering that traditional approaches to locate the hole by force sensing are time-consuming, we employ 3D vision to estimate the axis pose of the hole. Thus, robots can locate the target hole in both position and orientation and enable the shaft to move into the hole along the axis orientation. In our method, first, the raw point cloud of a hole is processed to acquire the keypoints. Then, a coarse axis is extracted according to the geometric constraints between the surface normals and axis. Lastly, axis refinement is performed on the coarse axis to achieve higher precision. Practical experiments verified the effectiveness of the axis pose estimation. The assembly strategy composed of axis pose estimation and admittance control was effectively applied to the robotic shaft-in-hole assembly.
Wearable Activity Monitoring in Day-to-Day Stroke Care: A Promising Tool but Not Widely Used
Authors: Braakhuis Hanneke E. M. , Bussmann Johannes B. J. , Ribbers Gerard M. , Berger Monique A. M.
Published: June 2021

Physical activity monitoring with wearable technology has the potential to support stroke rehabilitation. Little is known about how physical therapists use and value the use of wearable activity monitors. This cross-sectional study explores the use, perspectives, and barriers to wearable activity monitoring in day-to-day stroke care routines amongst physical therapists. Over 300 physical therapists in primary and geriatric care and rehabilitation centers in the Netherlands were invited to fill in an online survey that was developed based on previous studies and interviews with experts. In total, 103 complete surveys were analyzed. Out of the 103 surveys, 27% of the respondents were already using activity monitoring. Of the suggested treatment purposes of activity monitoring, 86% were perceived as useful by more than 55% of the therapists. The most recognized barriers to clinical implementation were lack of skills and knowledge of patients (65%) and not knowing what brand and type of monitor to choose (54%). Of the non-users, 79% were willing to use it in the future. In conclusion, although the concept of remote activity monitoring was perceived as useful, it was not widely adopted by physical therapists involved in stroke care. To date, skills, beliefs, and attitudes of individual therapists determine the current use of wearable technology.
Optimal H∞ Control for Lateral Dynamics of Autonomous Vehicles
Authors: Gagliardi Gianfranco , Lupia Marco , Cario Gianni , Casavola Alessandro
Published: June 2021

This paper presents the design and validation of a model-based H∞ vehicle lateral controller for autonomous vehicles in a simulation environment. The controller was designed so that the position and orientation tracking errors are minimized and so that the vehicle is able to follow a trajectory computed in real-time by exploiting proper video-processing and lane-detection algorithms. From a computational point of view, the controller is obtained by solving a suitable LMI optimization problem and ensures that the closed-loop system is robust with respect to variations in the vehicle’s longitudinal speed. In order to show the effectiveness of the proposed control strategy, simulations have been undertaken by taking advantage of a co-simulation environment jointly developed in Matlab/Simulink © and Carsim 8 ©. The simulation activity shows that the proposed control approach allows for good control performance to be achieved.
Smartphone Screen Integrated Optical Breathalyzer
Authors: Lapointe Jerome , Bécotte-Boutin Hélène-Sarah , Gagnon Stéphane , Levasseur Simon , Labranche Philippe , D’Auteuil Marc , Abdellatif Manel , Li Ming-Jun , Vallée Réal
Published: June 2021

One third of fatal car accidents and so many tragedies are due to alcohol abuse. These sad numbers could be mitigated if everyone had access to a breathalyzer anytime and anywhere. Having a breathalyzer built into a phone or wearable technology could be the way to get around reluctance to carry a separate device. With this goal, we propose an inexpensive breathalyzer that could be integrated in the screens of mobile devices. Our technology is based on the evaporation rate of the fog produced by the breath on the phone screen, which increases with increasing breath alcohol content. The device simply uses a photodiode placed on the side of the screen to measure the signature of the scattered light intensity from the phone display that is guided through the stress layer of the Gorilla glass screen. A part of the display light is coupled to the stress layer via the evanescent field induced at the edge of the breath microdroplets. We demonstrate that the intensity signature measured at the detector can be linked to blood alcohol content. We fabricated a prototype in a smartphone case powered by the phone’s battery, controlled by an application installed on the smartphone, and tested it in real-world environments. Limitations and future work toward a fully operational device are discussed.
Data Clustering Using Moth-Flame Optimization Algorithm
Authors: Singh Tribhuvan , Saxena Nitin , Khurana Manju , Singh Dilbag , Abdalla Mohamed , Alshazly Hammam
Published: June 2021

A k-means algorithm is a method for clustering that has already gained a wide range of acceptability. However, its performance extremely depends on the opening cluster centers. Besides, due to weak exploration capability, it is easily stuck at local optima. Recently, a new metaheuristic called Moth Flame Optimizer (MFO) is proposed to handle complex problems. MFO simulates the moths intelligence, known as transverse orientation, used to navigate in nature. In various research work, the performance of MFO is found quite satisfactory. This paper suggests a novel heuristic approach based on the MFO to solve data clustering problems. To validate the competitiveness of the proposed approach, various experiments have been conducted using Shape and UCI benchmark datasets. The proposed approach is compared with five state-of-art algorithms over twelve datasets. The mean performance of the proposed algorithm is superior on 10 datasets and comparable in remaining two datasets. The analysis of experimental results confirms the efficacy of the suggested approach.
A Fully Convolutional Network-Based Tube Contour Detection Method Using Multi-Exposure Images
Authors: Cheng Xiaoqi , Sun Junhua , Zhou Fuqiang
Published: June 2021

The tube contours in two-dimensional images are important cues for optical three-dimensional reconstruction. Aiming at the practical problems encountered in the application of tube contour detection under complex background, a fully convolutional network (FCN)-based tube contour detection method is proposed. Multi-exposure (ME) images are captured as the input of FCN in order to get information of tube contours in different dynamic ranges, and the U-Net type architecture is adopted by the FCN to achieve pixel-level dense classification. In addition, we propose a new loss function that can help eliminate the adverse effects caused by the positional deviation and jagged morphology of tube contour labels. Finally, we introduce a new dataset called multi-exposure tube contour dataset (METCD) and a new evaluation metric called dilate inaccuracy at optimal dataset scale (DIA-ODS) to reach an overall evaluation of our proposed method. The experimental results show that the proposed method can effectively improve the integrity and accuracy of tube contour detection in complex scenes.
Asymmetric Diffraction in Plasmonic Meta-Gratings Using an IT-Shaped Nanoslit Array
Authors: Jeong Hee-Dong , Moon Seong-Won , Lee Seung-Yeol
Published: June 2021

Diffraction is a fundamental phenomenon that reveals the wave nature of light. When a plane wave is transmitted or reflected from a grating or other periodic structures, diffracted light waves propagate at several angles that are specified by the period of the given structure. When the optical period is shorter than the wavelength, constructive interference of diffracted light rays from the subwavelength-scale grating forms a uniform plane wave. Many studies have shown that through the appropriate design of meta-atom geometry, metasurfaces can be used to control light properties. However, most semitransparent metasurfaces are designed to perform symmetric operation with regard to diffraction, meaning that light diffraction occurs identically for front- and back-side illumination. We propose a simple single-layer plasmonic metasurface that achieves asymmetric diffraction by optimizing the transmission phase from two types of nanoslits with I- and T-shaped structures. As the proposed structure is designed to have a different effective period for each observation side, it is either diffractive or nondiffractive depending on the direction of observation. The designed structure exhibits a diffraction angle of 54°, which can be further tuned by applying different period conditions. We expect the proposed asymmetric diffraction meta-grating to have great potential for the miniaturized optical diffraction control systems in the infrared band and compact optical diffraction filters for integrated optics.
Incivility in Higher Education: Challenges of Inclusion for Neurodiverse Students with Traumatic Brain Injury in Ireland
Authors: Shiels Teresa , Kenny Neil , Shiels Roy , Mannix-McNamara Patricia
Published: June 2021

This paper explores the lived experience of incivility for neurodiverse students with traumatic brain injury (TBI) in Ireland. The higher education (HE) environment can be challenging for students with TBI. Incivility is common in higher education, and students with disabilities such as TBI are often marginalized within academia, making them more vulnerable to incivility. For this paper, data are drawn from the first author’s autoethnographic study, and is supplemented with semi-structured interviews from a sample of HE seven students also with TBI. Results revealed that participants’ experiences of incivility were common and were linked to the organizational culture of higher education. Our experiences point to a need for better responsiveness when interactions are frequently uncivil, despite there being policies that recognize diversity and equality. This is the first paper of its kind to explore this particular experience in Ireland and the purpose of this paper is to raise awareness of the challenges of neurodiverse students and how they are exacerbated by organizational and interpersonal incivility.
Research on the Relationship between Transport Infrastructure and Performance in Rail and Road Freight Transport—A Case Study of Japan and Selected European Countries
Authors: Gnap Jozef , Senko Šimon , Kostrzewski Mariusz , Brídziková Mária , Cződörová Renáta , Říha Zdeněk
Published: June 2021

Transport is key for our economy and society, as good transport infrastructure helps to improve the mobility of citizens and the flow of goods. The European Union intends to maintain support for the development of transport infrastructure in the individual Member States. The aim of this study was to use correlation analysis to compare selected parameters of the road and railway infrastructure of Japan and selected EU countries. The significance of the correlations between various parameters characterizing the transport infrastructure of Japan and selected EU countries was tested. Correlation analysis is not typical in transport-oriented research. Several studies have employed such analysis; however, the majority of them have focused on passenger transport and correlations concerning the behavior of the customers of this mode of transport. The aim of this study was to answer the following research question: is there any correlation between transport performance and infrastructure or investment in infrastructure in relation to the mentioned countries, and, if so, is there a connection between the selected countries where this correlation occurs? Greater investment can also be expected in the construction of high-speed railways, given the decisions of some EU Member States not to resume national air transport where there is good railway infrastructure, even after the end of the COVID-19 pandemic.
Tourism-Based Alternative Livelihoods for Small Island Communities Transitioning towards a Blue Economy
Authors: Praptiwi Radisti A. , Maharja Carya , Fortnam Matt , Chaigneau Tomas , Evans Louisa , Garniati Leuserina , Sugardjito Jito
Published: June 2021

Tourism development has been promoted as an alternative livelihood to reduce the dependence of small island communities on declining marine resources. It is often central to emerging agendas around marine planning and the blue economy. However, relatively little is known about how communities perceive tourism development as an alternative and potentially sustainable livelihood in their area and its implications. This qualitative study tracks a governance system in transition and analyzes the factors perceived by stakeholders to be driving and hindering the adoption of tourism-based livelihoods on small islands in UNESCO’s Taka Bonerate Kepulauan Selayar Biosphere Reserve (Indonesia). The findings indicate that, despite a series of tourism-enhancing investments and initiatives and the positive attitudes of local communities towards it, tourism is not a direct route towards sustainability for small island communities. The benefits of tourism are perceived to be unequally distributed. The lack of education and skills limits participation in new job opportunities, and the incentives to continue destructive fishing inhibits livelihood transition to tourism. The article concludes that tourism cannot be assumed to generate simultaneous benefits for conservation and development without more equitable benefit sharing, the meeting of basic needs in communities, and addressing the drivers of unsustainable livelihoods.
Innovations in Sustainable Groundwater and Salinity Management in California’s San Joaquin Valley
Authors: Quinn Nigel W. T. , Oster James D.
Published: June 2021

The Sustainable Groundwater Management Act (SGMA) of 2014 and the Central Valley Salinity Alternatives for Long-Term Sustainability (CVSALTS) initiative were conceived to reverse years of inaction on the over-pumping of groundwater and salination of rivers that both threaten agricultural sustainability in the State of California. These largely stakeholder-led, innovative policy actions were supported by modern tools of remote sensing and Geographic Information System technology that allowed stakeholders to make adjustments to existing resource management and jurisdictional boundaries to form policy-mandated Groundwater Sustainability Agencies (GSAs) and Salinity Management Areas (SMAs) to address future management responsibilities. Additional resources mobilized by the California Department of Water Resources (CDWR) and other water resource and water quality management agencies have been effective in encouraging the use of spreadsheet accounting and numerical simulation models to develop robust and coherent quantitative understanding of the current state and likely problems that will be encountered to achieve resource sustainability. This activity has revealed flaws and inconsistencies in the conceptual models underpinning this activity. Two case studies are described that illustrate the disparity in the challenges faced by GSAs in subregions charged with developing consensus-based Groundwater Sustainability Plans (GSPs). These case studies also illustrate the unique aspect of SGMA: that alongside mandates and guidelines being imposed statewide, local leadership and advocacy can play an important role in achieving long-term SGMA and CVSALTS goals.
Closed-Loop Supply Chain Design and Pricing in Competitive Conditions by Considering the Variable Value of Return Products Using the Whale Optimization Algorithm
Authors: Shabbir Muhammad Salman , Siddiqi Ahmed Faisal , Yapanto Lis M. , Tonkov Evgeny E. , Poltarykhin Andrey Leonidovich , Pilyugina Anna Valeryevna , Petrov Aleksandr Mikhailovich , Foroughi Amin , Valiullina Dinara A.
Published: June 2021

In today’s competitive environment, organizations, in addition to trying to improve their production conditions, have a special focus on their supply chain components. Cooperation between supply chain members always reduces unforeseen costs and speeds up the response to customer demand. In the new situation, according to the category of return products and their reprocessing, supply chains have found a closed-loop structure. In this research, the aim was to design a closed-loop supply chain in competitive conditions. For this purpose, the key decisions of this chain included locating retail centers, adjusting the inventory of chain members, and selling prices of final products, optimally determined. For this purpose, a nonlinear integer mathematical model is presented. One of the most important innovations of this research was considering the variable value for return products. Then, in order to solve the proposed model, a whale optimization algorithm was developed. Numerical results from the sample examples showed that the whale algorithm had a very good performance in terms of response quality and speed-of-action in finding the optimal solution to this problem.
Knowledge Sharing in R&D Teams: An Evolutionary Game Model
Authors: Xiao Jiuling , Bao Yuting , Wang Jiankang , Yu Haiyun , Ma Zhenzhong , Jing Lei
Published: June 2021

Knowledge sharing plays an important role in promoting innovation and helping improve R&D team performance in the digital age. Based on the evolutionary game theory, this study develops an evolutionary game model of knowledge sharing in R&D teams in order to explore its system evolution path, the evolutionary stability strategy, and the influencing mechanism in knowledge sharing. Then using a simulation model, this study examines the dynamic evolution process of knowledge sharing within R&D teams. The results show that the effectiveness of knowledge sharing in the R&D teams can be promoted by R&D team members’ cognitive ability, knowledge absorption ability, knowledge transformation ability, knowledge innovation ability, and the degree of knowledge complementarity within teams. The simulation results further show that reducing the environmental risk can also effectively improve R&D teams’ innovation performance. The findings of this study thus provide evidence for knowledge sharing as an important route to sustainable development.
The Use of Decomposition Methods to Understand the Economic Growth Gap between Latin America and East Asia
Authors: Barrado Beatriz , Gimenez Gregorio , Sanaú Jaime
Published: June 2021

Understanding how growth factors contribute to explaining the large differences in growth rates across countries remains an important research agenda. The common approach to exploring this issue is based on the use of multiple linear regression analyses. This work contributes to growth literature by applying a new perspective based on the use of variance decomposition procedures: Shapley–Owen–Shorrocks and Oaxaca–Blinder. These methodologies have four main advantages with respect to traditional methodologies: they make possible the quantification of the relative contribution of each factor to economic growth, they allow us to estimate the efficiency in the use of the endowments of each factor, they can be used with any functional form and they can be used with estimation methods that are robust regarding endogeneity issues. We illustrate these advantages by analyzing the causes of the economic growth gap between Latin America and East Asia over the period 1980–2014. We find that the economic growth divergence between the two regions can be primarily explained by the differences in institutions and physical capital. In addition, the results indicate that the higher East Asian performance is not only due to its higher levels of endowments in these factors, but also to the higher efficiency in its use. We connect our results with the 2030 Agenda for Sustainable Development.
Condition-Based Maintenance Strategies to Enhance the Durability of ETICS
Authors: Ferreira Cláudia , Silva Ana , de Brito Jorge , Dias Ilídio S. , Flores-Colen Inês
Published: June 2021

The increase of awareness with sustainability and the desire of reducing the energy consumption in the construction sector haved increased the application of External Thermal Insulation Composite Systems (ETICS) across Europe in the last decades. Nevertheless, the implementation of appropriate maintenance strategies is still neglected. The aim of this study is to analyse the impact of different maintenance strategies. For that purpose, a condition-based maintenance model, based on Petri nets, is used to evaluate three maintenance strategies: MS1—total replacement only; MS2—combination of minor intervention and total replacement; and MS3—combination of cleaning operations, minor intervention, and total replacement. In the end, a multi-criteria analysis is used to discuss the impact of the three maintenance strategies proposed, evaluating the remaining service life, the global costs over time, the ETICS’ degradation condition, and the number of replacements (end of service life) over the time horizon. For this purpose, a sample of 378 ETICS was analysed, based on in situ visual inspections, carried out in Portugal. The results from this study reveal that maintenance plays an important role to increase the durability of ETICS, and therefore their sustainability. Regular maintenance can promote the extension of the ETICS’s service life between 88% and 159% (between 15 to 27 years), improve the global degradation condition of the ETICS, and reduce the impact on users by reducing the number of deeper interventions. Further research is essential to optimise the maintenance strategies (time interval between inspections, stakeholders’ performance criteria, and environmental exposure).
An Analysis of Game Design Elements Used in Digital Game-Based Language Learning
Authors: Govender Terence , Arnedo-Moreno Joan
Published: June 2021

Considerable changes have occurred in language learning with the introduction of gameful approaches in the classroom and the increase in the popularity of language applications like Duolingo. A review of existing studies on such approaches to language learning shows that gamification tends to be the most popular approach. However, this popularity has been achieved at the expense of other gameful approaches, such as the use of digital games. To gain a clearer picture of the developments and gaps in the digital game-based learning research, this paper examines and categorizes observations about game elements used in published papers (n = 114) where serious and digital games were tested in language education settings. Game element analysis reveals that (1) the most frequently occurring elements in digital game-based language learning (DGBLL) are feedback, theme, points, narrative, and levels; (2) even though there was significant variance in the number of elements observed in DGBLL, both the bespoke and off-the-shelf games show similar high-frequency elements; (3) DGBLL has been applied to vocabulary acquisition and retention in many cases, but lacks implementation and testing in input and output language skills; (4) although there is some consensus on the most frequent elements, the design patterns of common elements according to age group and target language skill show considerable variance; (5) more research is needed on less common design elements that have shown promise in encouraging language acquisition. The synthesis of information from the collected papers contributes to knowledge regarding DGBLL application design and will help formulate guidelines and detect efficacy patterns as the field continues to grow.
Agri-Food Contexts in Mediterranean Regions: Contributions to Better Resources Management
Authors: Martinho Vítor João Pereira Domingues
Published: June 2021

The agri-food frameworks have specific characteristics (production units with small dimensions and in great number with implications in the respective markets) that call for adjusted approaches, even more so when they are considered in Mediterranean contexts (where global warming will have relevant impacts). In fact, the Mediterranean regions and countries have particular specificities (due to their climate conditions) that distinguish them from their neighbours. This is particularly true in Europe, for example, where the southern countries present socioeconomic dynamics (associated with the respective public debt) that are different from those identified in the northern regions. From this perspective, it seems pertinent to analyse the several dimensions of the agri-food systems in the Mediterranean area. To achieve these objectives, a search was carried out on 26 December 2020 on the scientific databases Web of Science Core Collection (WoS) and Scopus for the topics “agr*-food” and “Mediterranean”. These keywords were selected after a previous literature survey and to capture the agri-food contexts in Mediterranean regions. The keyword “agr*-food” was considered in this way to allow for a wider search (including “agri-food”, “agro-food”, etc.). Considering only articles (excluding proceeding papers, book chapters, and books, because in some cases it is difficult to access the entire content of the document), 100 and 117 documents were obtained from the WoS and Scopus, respectively. After removing the duplicated studies and taking into account the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach, 137 documents were surveyed through a literature review. As main insights, several dimensions embedded in the concept of agri-food were highlighted, from those related to heritage subjects to natural assets. On the other hand, the following subtopics were identified: agri-food dynamics and sustainability, agriculture and agri-food systems, agri-chains and food consumption, and food production and composition impact on agri-chains. Stressing the gaps in the scientific literature, related to the topics here addressed, there are possibilities to better explore the several dimensions and solutions offered by the new developments associated with smart agriculture and agriculture 4.0, specifically for the Mediterranean contexts and their challenges. Finally, to complement the PRISMA methodologies, an MB2MBA2 (Methodology Based on Benchmarking of Metadata, from scientific databases, and Bibliometric Assessment and Analysis) approach is suggested to carry out systematic literature reviews, based on bibliometric analysis.
Driving Sustainability through Engineering Management and Systems Engineering
Authors: Philbin Simon P.
Published: June 2021

The COVID-19 pandemic has highlighted the somewhat precarious nature of our lives, including the way we work and our lifestyles [...]
Determination of Soil Hydraulic Parameters and Evaluation of Water Dynamics and Nitrate Leaching in the Unsaturated Layered Zone: A Modeling Case Study in Central Croatia
Authors: Defterdarović Jasmina , Filipović Lana , Kranjčec Filip , Ondrašek Gabrijel , Kikić Diana , Novosel Alen , Mustać Ivan , Krevh Vedran , Magdić Ivan , Rubinić Vedran , Bogunović Igor , Dugan Ivan , Čopec Krešimir , He Hailong , Filipović Vilim
Published: June 2021

Nitrate leaching through soil layers to groundwater may cause significant degradation of natural resources. The aims of this study were: (i) to estimate soil hydraulic properties (SHPs) of the similar soil type with same management on various locations; (ii) to determine annual water dynamics; and (iii) to estimate the impact of subsoil horizon properties on nitrate leaching. The final goal was to compare the influence of different SHPs and layering on water dynamics and nitrate leaching. The study was conducted in central Croatia (Zagreb), at four locations on Calcaric Phaeozem, Calcaric Regosol, and Calcaric Fluvic Phaeozem soil types. Soil hydraulic parameters were estimated using the HYPROP system and HYPROP-FIT software. Water dynamics and nitrate leaching were evaluated using HYDRUS 2D/3D during a period of 365 days. The amount of water in the soil under saturated conditions varied from 0.422 to 0.535 cm3 cm−3 while the hydraulic conductivity varied from 3 cm day−1 to 990.9 cm day−1. Even though all locations have the same land use and climatic conditions with similar physical properties, hydraulic parameters varied substantially. The amount and velocity of transported nitrate (HYDRUS 2D/3D) were affected by reduced hydraulic conductivity of the subsoil as nitrates are primarily transported via advective flux. Despite the large differences in SHPs of the topsoil layers, the deeper soil layers, having similar SHPs, imposed a buffering effect preventing faster nitrate downward transport. This contributed to a very similar distribution of nitrates through the soil profile at the end of simulation period. This case study indicated the importance of carefully selecting relevant parameters in multilayered soil systems when evaluating groundwater pollution risk.
Artificial Intelligence Applications for Increasing Resource Efficiency in Manufacturing Companies—A Comprehensive Review
Authors: Waltersmann Lara , Kiemel Steffen , Stuhlsatz Julian , Sauer Alexander , Miehe Robert
Published: June 2021

Sustainability improvements in industrial production are essential for tackling climate change and the resulting ecological crisis. In this context, resource efficiency can directly lead to significant advancements in the ecological performance of manufacturing companies. The application of Artificial Intelligence (AI) also plays an increasingly important role. However, the potential influence of AI applications on resource efficiency has not been investigated. Against this background, this article provides an overview of the current AI applications and how they affect resource efficiency. In line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, this paper identifies, categorizes, and analyzes seventy papers with a focus on AI tasks, AI methods, business units, and their influence on resource efficiency. Only a minority of papers was found to address resource efficiency as an explicit objective. Subsequently, typical use cases of the identified AI applications are described with a focus on predictive maintenance, production planning, fault detection and predictive quality, as well as the increase in energy efficiency. In general, more research is needed that explicitly considers sustainability in the development and use phase of AI solutions, including Green AI. This paper contributes to research in this field by systematically examining papers and revealing research deficits. Additionally, practitioners are offered the first indications of AI applications increasing resource efficiency.
Conceptual Comparison of Internal Audit and Internal Control in the Marketing Environment
Authors: Kupec Václav , Písař Přemysl , Lukáč Michal , Pajtinková Bartáková Gabriela
Published: June 2021

There is a conceptual problem in the adequate application of internal audit and internal control in the real business of the marketing environment. Although both of these managerial tools are theoretically defined, they are practically interchangeable in business. This limits their application. It is therefore necessary to focus on both concepts and make the theory and practice more precise or remove any overlaps. The aim of this paper is therefore a theoretical and practical comparison of internal audit and internal control concepts in the marketing environment. To fulfil this purpose and verify the hypotheses, this paper uses computer assisted self interviewing. The research was conducted in Q1 2021 with a sample of 3052 small and medium enterprises from the international environment of the EU 27. The research conclusions show a strong correlation of the theoretical perception of the terms of internal audit and internal control. At the same time, they show a weak correlation with the audit and control tools used in practice. They also define audit as planned independent assurance (soft consultation) and control as operational managerial assurance (hard comparison). This defines and clarifies scientific theories for managerial practice, thus enhancing and increasing the efficiency of internal audits and internal control in the business environment.
Community-Based Tourism through Food: A Proposal of Sustainable Tourism Indicators for Isolated and Rural Destinations in Mexico
Authors: Sosa Mariana , Aulet Silvia , Mundet Lluis
Published: June 2021

Purpose: this article presents a conceptual framework for examining community tourism as a sustainable livelihood through food tourism, considering the significant increase in community-based tourism in Mexico and the impact this activity has on rural and vulnerable destinations. The main aim of this research is to generate a proposal for a set of sustainable tourism indicators for rural and isolated communities through food strategies geared towards tourism development. Methodology: this information can then be used to generate a first list of indicators for creating and evaluating community tourism proposals in a region. Said theoretical list includes four dimensions (socio-cultural, environmental, tourist, and economic), which comprise 27 indicators in total. Findings: the results, validated by different participants related to the tourism sector, show that a lack of information for quantifying indicators is one of the main limitations when evaluating a vulnerable destination and that participation by the private sector and public administrations will be essential in generating these data. Approach: this research will therefore contribute to the development of new action strategies that allow not only the strengthening of the current localized agri-food systems, but also the revaluation of forgotten food systems.